initial import: @mikefreno/omp-deepi-research (omp port)

2026-08-10 09:46:09 -04:00
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+node_modules/
+dist/
+.pi-lens/
+AGENTS.md
+package-lock.json
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+MIT License
+
+Copyright (c) 2026 Michael Freno
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
--- a/README.md
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+# Deep Research
+
+Multi-round deep web research powered by Firecrawl with iterative query refinement.
+
+Deep Research is a local omp extension under `~/.omp/agent/extensions/deepi-research/`.
+Omp loads it via `omp.extensions` in `package.json` (entry `./index.ts`).
+
+## Features
+
+- **Multi-round iteration**: Each round generates follow-up queries based on previous findings (depth 1-3)
+- **Parallel query expansion**: Multiple diverse search queries per round (breadth 1-5) covering technical, practical, comparative, critical, and forward-looking angles
+- **Sub-question decomposition**: Broad questions are broken into focused sub-topics before query generation (depth > 1)
+- **Round-robin parallel execution**: Searches and analyses run concurrently within each round using bounded-concurrency worker pools, dramatically reducing total research time
+- **LLM-driven analysis**: Each query's results are analyzed by its own agent session (per-query provenance) to extract structured findings with confidence ratings
+- **Source authority scoring**: Every source is scored by domain authority; low-quality SEO domains are penalized with a hard floor; findings are ranked by authority × confidence before synthesis
+- **Cross-query corroboration**: A finding is corroborated only when its sources were independently surfaced by multiple different search queries
+- **Citation integrity**: References are rebuilt from the authoritative bibliography (never the LLM's), and hallucinated inline citation numbers are stripped
+- **Near-duplicate detection**: Syndicated copies of the same article are removed by title similarity, and duplicate findings across rounds are merged
+- **Automatic deduplication**: Search results are deduplicated by URL across all queries
+- **Robust LLM output parsing**: JSON output with code fences, prose prefixes, or trailing commas is parsed reliably
+- **Graceful degradation**: Individual search or analysis failures don't crash the full research — partial results are preserved, with retry-with-backoff for transient Firecrawl errors
+- **Progress streaming**: Real-time progress widget with spinner, phase indicators, and progress bar
+- **Abort support**: Research can be cancelled mid-flight via `AbortSignal`
+- **Rich TUI rendering**: Compact collapsed view and detailed expanded view in the terminal UI
+- **Fallback resilience**: Built-in fallback query generation and report synthesis when LLM calls fail
+
+## Usage
+
+### Tool (LLM-callable)
+
+Registers the `deep_research` tool for AI agent use:
+
+```
+deep_research — multi-round deep web research via Firecrawl with iterative query refinement
+```
+
+Parameters:
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `question` | string | — | The research question to investigate |
+| `depth` | integer (1-3) | 2 | Number of research rounds |
+| `breadth` | integer (1-5) | 3 | Search queries per round |
+| `format` | "markdown" \| "structured" | "markdown" | Output format for the report |
+| `audience` | "general" \| "expert" \| "executive" | "general" | Tone and depth for the report audience |
+| `details.showRoundDetails` | boolean | false | Include per-round search metadata (incl. failed searches) in output |
+
+### Command (interactive)
+
+```
+/deepi-research <your research question>
+```
+
+Prompts for depth (1-3 rounds) and breadth (1-5 queries) interactively, then runs the research and sends the final report as a user message.
+
+### Recommended usage
+
+- Use `deep_research` for complex, multi-faceted questions that benefit from multiple search angles and iterative refinement.
+- The tool handles query generation, web search, result analysis, and report synthesis automatically.
+- For simple fact-finding questions, use `firecrawl_search` directly instead.
+
+## Architecture
+
+```
+Research Flow:
+
+  Question
+     ↓
+  ┌─ Round 1 ───────────────────────────┐
+  │  LLM → generate queries (N angles)   │
+  │  Firecrawl → search each query       │
+  │  LLM → analyze results → findings    │
+  └──────────────┬───────────────────────┘
+                 ↓ (follow-up queries)
+  ┌─ Round 2 ───────────────────────────┐
+  │  LLM → identify knowledge gaps       │
+  │  Firecrawl → search follow-ups       │
+  │  LLM → analyze → new findings        │
+  └──────────────┬───────────────────────┘
+                 ↓ (iterate depth times)
+  ┌─ Synthesis ─────────────────────────┐
+  │  LLM → synthesize all findings       │
+  │  → comprehensive research report     │
+  └─────────────────────────────────────┘
+```
+
+## Configuration
+
+Deep Research reads Firecrawl configuration from omp's config.yml files, with the following resolution order (later wins):
+
+1. Environment variables (`FIRECRAWL_BASE_URL`, `FIRECRAWL_API_KEY`)
+2. Global config (`$agentDir/config.yml`) → `firecrawl.*`
+3. Project config (`.omp/config.yml`) → `firecrawl.*`
+4. Default `http://localhost:3002` (if nothing else sets baseUrl)
+
+The agent directory (`$agentDir`) defaults to `~/.omp/agent`.
+
+**Global config** (`~/.omp/agent/config.yml`):
+
+```yaml
+firecrawl:
+  baseUrl: http://localhost:3002
+```
+
+**Project config** (`.omp/config.yml` — overrides global):
+
+```yaml
+firecrawl:
+  baseUrl: https://firecrawl.team.internal
+  apiKey: your-api-key
+```
+
+### Session startup check
+
+On `session_start`, the extension checks whether the Firecrawl endpoint is reachable. If not, it shows a warning notification so you know searches will fail before you try to use it.
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+  }
+}
--- a/index.ts
+++ b/index.ts
@@ -0,0 +1,590 @@
+/**
+ * deep-research — Multi-round deep web research powered by Firecrawl
+ *
+ * Registers:
+ *   - `deep_research` tool — callable by the LLM to conduct deep research
+ *   - `/deepi-research` command — interactive session invocation
+ *
+ * Architecture:
+ *   Each research round generates queries, searches in parallel via
+ *   Firecrawl, analyzes results with agent sessions, then generates
+ *   follow-up queries. A final synthesis step produces the report.
+ *
+ * Patterns borrowed from:
+ *   - firecrawl.ts extension (direct Firecrawl HTTP calls)
+ *   - ralpi executor (agent sessions, widget updates, progress UX)
+ *   - subagent extension (structured tool rendering)
+ */
+import type {
+	ExtensionAPI,
+	ExtensionCommandContext,
+	ExtensionContext,
+} from "@oh-my-pi/pi-coding-agent";
+import type { TSchema } from "@oh-my-pi/pi-ai";
+import { Type } from "typebox";
+import {
+	Box,
+	Text,
+	truncateToWidth,
+	visibleWidth,
+} from "@oh-my-pi/pi-tui";
+import { runDeepResearch, type ResearchProgress } from "./src/research";
+import { isFirecrawlReachable } from "./src/firecrawl";
+import type { ResearchConfig, ResearchReport, Audience } from "./src/types";
+
+/* ── Constants ────────────────────────────────────────────────────── */
+
+const SPINNER_FRAMES = ["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"];
+const PHASE_ICONS: Record<string, string> = {
+	decomposing: "🧩",
+	generating_queries: "🔍",
+	searching: "🌐",
+	analyzing: "📊",
+	synthesizing: "📝",
+	complete: "✅",
+};
+
+type ResearchPhase = Parameters<ResearchProgress>[0]["phase"];
+
+/* ── Helpers ──────────────────────────────────────────────────────── */
+
+function formatDuration(ms: number): string {
+	const seconds = Math.floor(ms / 1000);
+	const minutes = Math.floor(seconds / 60);
+	if (minutes > 0) return `${minutes}m ${seconds % 60}s`;
+	return `${seconds}s`;
+}
+
+function truncate(s: string, max: number): string {
+	if (s.length <= max) return s;
+	return s.slice(0, max - 3) + "...";
+}
+
+/* ── Tool Definition ──────────────────────────────────────────────── */
+
+const DeepResearchParams = Type.Object({
+	question: Type.String({
+		description: "The research question to investigate",
+	}),
+	depth: Type.Optional(
+		Type.Integer({
+			description:
+				"Number of research rounds (1-3). Each round builds on findings from the previous for deeper analysis. Default: 2",
+			minimum: 1,
+			maximum: 3,
+			default: 2,
+		}),
+	),
+	breadth: Type.Optional(
+		Type.Integer({
+			description:
+				"Number of search queries per round (1-5). More queries = broader coverage but slower. Default: 3",
+			minimum: 1,
+			maximum: 5,
+			default: 3,
+		}),
+	),
+	format: Type.Optional(
+		Type.Union([Type.Literal("markdown"), Type.Literal("structured")], {
+			description:
+				'Output format for the research report. "markdown" for prose with headings, "structured" for detailed hierarchical sections. Default: "markdown"',
+			default: "markdown",
+		}),
+	),
+	audience: Type.Optional(
+		Type.Union(
+			[
+				Type.Literal("general"),
+				Type.Literal("expert"),
+				Type.Literal("executive"),
+			],
+			{
+				description:
+					"Target audience for the report. 'general' (accessible), 'expert' (technical depth), 'executive' (concise, action-oriented). Default: 'general'",
+				default: "general",
+			},
+		),
+	),
+	details: Type.Optional(
+		Type.Object({
+			showRoundDetails: Type.Optional(
+				Type.Boolean({
+					description:
+						"Include per-round search methodology in the output. Default: false",
+				}),
+			),
+		}),
+	),
+});
+
+interface ResearchDetails {
+	rounds: Array<{
+		round: number;
+		queries: string[];
+		findingsCount: number;
+		resultsCount: number;
+		failedSearches: number;
+	}>;
+	totalSearches: number;
+	totalPagesScraped: number;
+	durationMs: number;
+}
+
+/* ── Widget Helper ────────────────────────────────────────────────── */
+
+/**
+ * Create a widget state that drives a spinner-based progress widget.
+ * Returns the state object, the timer, and cleanup function.
+ */
+function createProgressWidget(
+	ctx: any,
+	initialPhase: ResearchPhase = "generating_queries",
+) {
+	const state: {
+		phase: ResearchPhase;
+		message: string;
+		detail: string | undefined;
+		fraction: number;
+		round: number | undefined;
+		totalRounds: number | undefined;
+	} = {
+		phase: initialPhase,
+		message: "Starting...",
+		detail: undefined,
+		fraction: 0,
+		round: undefined,
+		totalRounds: undefined,
+	};
+
+	let widgetTui: { requestRender(): void } | null = null;
+	let spinnerIdx = 0;
+
+	ctx.ui.setWidget(
+		"deep-research",
+		(tui: { requestRender(): void }, _theme: any) => {
+			widgetTui = tui;
+			return {
+				render: (width: number) => {
+					const spinner = SPINNER_FRAMES[spinnerIdx];
+					const icon = PHASE_ICONS[state.phase] ?? "";
+					const roundInfo =
+						state.round && state.totalRounds
+							? ` Round ${state.round}/${state.totalRounds}`
+							: "";
+					const firstLine = `${spinner} ${icon} ${state.message}${roundInfo}`;
+					const lines: string[] = [truncateToWidth(firstLine, width)];
+					if (state.detail) {
+						lines.push(truncateToWidth(`  ${state.detail}`, width));
+					}
+					if (state.fraction > 0) {
+						const barLen = Math.min(15, Math.max(3, width - 4));
+						const filled = Math.round(barLen * state.fraction);
+						const bar = "█".repeat(filled) + "░".repeat(barLen - filled);
+						lines.push(`  ${bar}`);
+					}
+					return lines;
+				},
+				invalidate: () => {},
+			};
+		},
+	);
+
+	const spinnerTimer = setInterval(() => {
+		spinnerIdx = (spinnerIdx + 1) % SPINNER_FRAMES.length;
+		widgetTui?.requestRender();
+	}, 100);
+
+	const onProgress: ResearchProgress = (update) => {
+		state.phase = update.phase;
+		state.message = update.message;
+		state.detail = update.detail;
+		state.fraction = update.fraction ?? 0;
+		state.round = update.round;
+		state.totalRounds = update.totalRounds;
+	};
+
+	const cleanup = () => {
+		clearInterval(spinnerTimer);
+		ctx.ui.setWidget("deep-research", undefined);
+	};
+
+	return { state, onProgress, cleanup, spinnerTimer };
+}
+
+/* ── Extension Entry ───────────────────────────────────────────────── */
+
+export default function (pi: ExtensionAPI) {
+	pi.registerTool({
+		name: "deep_research",
+		label: "Deep Research",
+		description: [
+			"Conduct multi-round deep web research on any topic using Firecrawl.",
+			"Generates diverse search queries, searches the web in parallel, analyzes results,",
+			"and produces a comprehensive report with numbered citations and a bibliography.",
+			"Supports iterative refinement and sub-question decomposition for deeper analysis.",
+			"Parameters: question (required), depth, breadth, format, audience, details.",
+			"Use for complex, multi-faceted questions that benefit from multiple search angles;",
+			"for simple fact-finding questions use firecrawl_search directly instead.",
+			"Set audience to 'executive' for concise, action-oriented reports; 'expert' for technical depth;",
+			"'general' (default) for accessible reports.",
+		].join(" "),
+		parameters: DeepResearchParams as unknown as TSchema,
+
+		async execute(
+			_toolCallId: string,
+			params: {
+				question: string;
+				depth?: number;
+				breadth?: number;
+				format?: "markdown" | "structured";
+				audience?: Audience;
+				details?: { showRoundDetails?: boolean };
+			},
+			signal: AbortSignal | undefined,
+			onUpdate: ((partial: any) => void) | undefined,
+			ctx: any,
+		) {
+			const config: ResearchConfig = {
+				question: params.question,
+				depth: params.depth ?? 2,
+				breadth: params.breadth ?? 3,
+				format: params.format ?? "markdown",
+				audience: params.audience ?? "general",
+			};
+
+			const abortSignal = signal;
+			// eslint-disable-next-line @typescript-eslint/no-unused-vars
+			const { state: _state, onProgress, cleanup } = createProgressWidget(ctx);
+
+			let researchResult: ResearchReport | null = null;
+			let lastError: string | null = null;
+
+			try {
+				ctx.ui.setStatus(
+					"deep-research",
+					`🌐 Researching: ${truncate(config.question, 40)}`,
+				);
+
+				onProgress({
+					phase: "generating_queries",
+					message: "Starting deep research...",
+					fraction: 0,
+				});
+
+				researchResult = await runDeepResearch(
+					config,
+					ctx,
+					onProgress,
+					abortSignal,
+				);
+
+				// ── Build the tool result ──────────────────────────────────
+
+				const details: ResearchDetails = {
+					rounds: researchResult.rounds.map((r) => ({
+						round: r.round,
+						queries: r.queries.map((q) => q.query),
+						findingsCount: r.findings.length,
+						resultsCount: r.results.length,
+						failedSearches: r.failedSearches,
+					})),
+					totalSearches: researchResult.totalSearches,
+					totalPagesScraped: researchResult.totalPagesScraped,
+					durationMs: researchResult.durationMs,
+				};
+
+				// Stream final content via onUpdate before returning
+				if (onUpdate) {
+					onUpdate({
+						content: [{ type: "text", text: researchResult.finalReport }],
+						details: {
+							phase: "complete",
+							duration: researchResult.durationMs,
+							rounds: researchResult.rounds.length,
+							findings: researchResult.rounds.reduce(
+								(s, r) => s + r.findings.length,
+								0,
+							),
+							references: researchResult.references.length,
+						},
+					});
+				}
+
+				cleanup();
+				ctx.ui.setStatus("deep-research", undefined);
+
+				let output = researchResult.finalReport;
+
+				// Append methodology section if requested
+				if (params.details?.showRoundDetails) {
+					output += `\n\n---\n\n## Research Methodology\n\n`;
+					for (const round of researchResult.rounds) {
+						output += `### Round ${round.round}\n\n`;
+						output += `**Queries:**\n`;
+						for (const q of round.queries) {
+							output += `- "${q.query}" (${q.angle}) — ${q.rationale}\n`;
+						}
+						output += `\n**Results scraped:** ${round.results.length}\n`;
+						output += `**Findings extracted:** ${round.findings.length}\n`;
+						if (round.failedSearches > 0) {
+							output += `**Failed searches:** ${round.failedSearches}\n`;
+						}
+						output += `\n`;
+					}
+					output += `**Total searches:** ${researchResult.totalSearches}\n`;
+					output += `**Total pages scraped:** ${researchResult.totalPagesScraped}\n`;
+					output += `**Sources in bibliography:** ${researchResult.references.length}\n`;
+					output += `**Duration:** ${formatDuration(researchResult.durationMs)}\n`;
+				}
+
+				return {
+					content: [{ type: "text", text: output }],
+					details,
+				};
+			} catch (error) {
+				cleanup();
+				ctx.ui.setStatus("deep-research", undefined);
+
+				lastError = error instanceof Error ? error.message : String(error);
+
+				return {
+					content: [
+						{
+							type: "text",
+							text: `Research failed: ${lastError}`,
+						},
+					],
+					details: {
+						rounds: [],
+						totalSearches: 0,
+						totalPagesScraped: 0,
+						durationMs: 0,
+						error: lastError,
+					} as ResearchDetails & { error: string },
+					isError: true,
+				};
+			}
+		},
+
+		// ── TUI: Render the tool call (collapsed view) ──────────────────
+
+		renderCall(
+			args: any,
+			_options: any,
+			theme: any,
+		) {
+			const question = truncate(args.question ?? "?", 70);
+			const depth = args.depth ?? 2;
+			const breadth = args.breadth ?? 3;
+			const format = args.format ?? "markdown";
+			const audience = args.audience ?? "general";
+
+			const text =
+				theme.fg("toolTitle", theme.bold("deep_research ")) +
+				theme.fg("accent", `"${question}"`) +
+				theme.fg(
+					"muted",
+					` [depth:${depth} breadth:${breadth} ${format} ${audience}]`,
+				);
+			return new Text(text, 0, 0);
+		},
+
+		// ── TUI: Render the tool result (expanded/collapsed) ─────────────
+
+		renderResult(
+			result: any,
+			{ expanded }: { expanded: boolean },
+			theme: any,
+			_context: any,
+		) {
+			const details = result.details as ResearchDetails | undefined;
+
+			if (!details) {
+				const text = result.content?.[0]?.text ?? "(no output)";
+				return new Text(text, 0, 0);
+			}
+
+			const container = new Box();
+
+			// ── Collapsed view ────────────────────────────────────────────
+
+			if (!expanded) {
+				const totalRounds = details.rounds.length;
+				const totalFindings = details.rounds.reduce(
+					(s, r) => s + r.findingsCount,
+					0,
+				);
+				const duration = formatDuration(details.durationMs);
+
+				let text = "";
+				text +=
+					theme.fg("success", "✓ ") +
+					theme.fg("toolTitle", theme.bold("deep research"));
+				text += theme.fg(
+					"muted",
+					` — ${totalRounds} rounds, ${totalFindings} findings`,
+				);
+				text += theme.fg("dim", ` (${duration})`);
+				text += "\n";
+
+				for (const round of details.rounds) {
+					const icon =
+						round.findingsCount > 0
+							? theme.fg("success", "✓")
+							: theme.fg("muted", "·");
+					text += `  ${icon} ${theme.fg("accent", `Round ${round.round}:`)} `;
+					text += theme.fg(
+						"dim",
+						`${round.queries.length} queries, ${round.resultsCount} pages, ${round.findingsCount} findings`,
+					);
+					text += "\n";
+				}
+
+				text += theme.fg("muted", "(Ctrl+O to expand)");
+				container.addChild(new Text(text, 0, 0));
+				return container;
+			}
+
+			// ── Expanded view ─────────────────────────────────────────────
+
+			const headerText =
+				theme.fg("toolTitle", theme.bold("Deep Research Results")) +
+				"\n" +
+				theme.fg("dim", `Duration: ${formatDuration(details.durationMs)} | `) +
+				theme.fg("dim", `Searches: ${details.totalSearches} | `) +
+				theme.fg("dim", `Pages scraped: ${details.totalPagesScraped}`);
+			container.addChild(new Text(headerText, 0, 0));
+
+			for (const round of details.rounds) {
+				container.addChild(new Text("", 0, 0)); // Spacer
+				const roundHeader = `Round ${round.round}`;
+				container.addChild(
+					new Text(theme.fg("toolTitle", theme.bold(roundHeader)), 0, 0),
+				);
+				container.addChild(
+					new Text(
+						theme.fg(
+							"dim",
+							`${round.queries.length} queries → ${round.resultsCount} pages → ${round.findingsCount} findings`,
+						),
+						0,
+						0,
+					),
+				);
+				for (const q of round.queries) {
+					container.addChild(
+						new Text(
+							theme.fg("muted", "  · ") + theme.fg("accent", truncate(q, 70)),
+							0,
+							0,
+						),
+					);
+				}
+			}
+
+			return container;
+		},
+	});
+
+	// ── Command ───────────────────────────────────────────────────────
+
+	pi.registerCommand("deepi-research", {
+		description:
+			"Conduct multi-round deep web research on any topic via Firecrawl. Usage: /deepi-research <question>",
+		handler: async (args: string, ctx: ExtensionCommandContext) => {
+			if (!args || args.trim().length === 0) {
+				ctx.ui.notify(
+					"Usage: /deepi-research <your research question>",
+					"error",
+				);
+				return;
+			}
+
+			// Ask about depth
+			const depthStr = await ctx.ui.select("Research depth?", [
+				"1 round (quick survey)",
+				"2 rounds (standard)",
+				"3 rounds (deep dive)",
+			]);
+			const depth = depthStr?.startsWith("1")
+				? 1
+				: depthStr?.startsWith("3")
+					? 3
+					: 2;
+
+			// Ask about breadth
+			const breadthStr = await ctx.ui.select("Research breadth?", [
+				"1 query/round (narrow)",
+				"3 queries/round (balanced)",
+				"5 queries/round (broad)",
+			]);
+			const breadth = breadthStr?.startsWith("1")
+				? 1
+				: breadthStr?.startsWith("5")
+					? 5
+					: 3;
+
+			// Ask about audience
+			const audienceStr = await ctx.ui.select("Report audience?", [
+				"General (accessible, explains terms)",
+				"Expert (technical depth, assumes domain knowledge)",
+				"Executive (concise, action-oriented)",
+			]);
+			const audience: Audience = audienceStr?.startsWith("Expert")
+				? "expert"
+				: audienceStr?.startsWith("Executive")
+					? "executive"
+					: "general";
+
+			ctx.ui.setStatus(
+				"deep-research",
+				`🌐 Researching: ${truncate(args, 40)}`,
+			);
+
+			const config: ResearchConfig = {
+				question: args,
+				depth,
+				breadth,
+				format: "markdown",
+				audience,
+			};
+
+			const { onProgress, cleanup } = createProgressWidget(ctx);
+
+			try {
+				const report = await runDeepResearch(config, ctx, onProgress);
+
+				cleanup();
+				ctx.ui.setStatus("deep-research", undefined);
+
+				// Show notification
+				ctx.ui.notify(
+					`Research complete: ${report.rounds.length} rounds, ${report.totalSearches} searches, ${report.totalPagesScraped} pages, ${report.references.length} sources in ${formatDuration(report.durationMs)}`,
+					"info",
+				);
+
+				// Send the report as a user message
+				pi.sendUserMessage(
+					`## Deep Research: ${args}\n\n${report.finalReport}\n\n---\n*${report.rounds.length} rounds · ${report.totalSearches} searches · ${report.totalPagesScraped} pages · ${report.references.length} sources · ${formatDuration(report.durationMs)}*`,
+				);
+			} catch (error) {
+				cleanup();
+				ctx.ui.setStatus("deep-research", undefined);
+				const msg = error instanceof Error ? error.message : String(error);
+				ctx.ui.notify(`Research failed: ${msg}`, "error");
+			}
+		},
+	});
+
+	// ── Startup check ─────────────────────────────────────────────────
+
+	pi.on("session_start", async (_event: unknown, ctx: ExtensionContext) => {
+		const reachable = await isFirecrawlReachable();
+		if (!reachable) {
+			ctx.ui.notify(
+				"Deep Research: Firecrawl endpoint unreachable — searches will fail. Set firecrawl.baseUrl in config.yml (global ~/.omp/agent or project .omp) or the FIRECRAWL_BASE_URL env var.",
+				"warning",
+			);
+		}
+	});
+}
--- a/package.json
+++ b/package.json
@@ -0,0 +1,43 @@
+{
+  "name": "@mikefreno/omp-deepi-research",
+  "version": "0.2.0",
+  "description": "Deep research extension for pi — parallel web research via Firecrawl with iterative query refinement",
+  "keywords": [
+    "pi-package",
+    "pi-extension",
+    "research",
+    "firecrawl",
+    "deep-research",
+    "web-search",
+    "ai"
+  ],
+  "license": "MIT",
+  "files": [
+    "index.ts",
+    "src/",
+    "README.md",
+    "LICENSE"
+  ],
+  "scripts": {
+    "typecheck": "tsc --noEmit",
+    "prepublishOnly": "tsc --noEmit"
+  },
+  "engines": {
+    "bun": ">=1.3.14"
+  },
+  "dependencies": {
+    "yaml": "^2.4.0"
+  },
+  "omp": {
+    "extensions": [
+      "./index.ts"
+    ]
+  },
+  "devDependencies": {
+    "@oh-my-pi/pi-coding-agent": "17.2.12",
+    "@oh-my-pi/pi-tui": "17.2.12",
+    "@types/node": "^20.0.0",
+    "typebox": "^1.1.0",
+    "typescript": "^5.3.0"
+  }
+}
--- a/scripts/run-harness.ts
+++ b/scripts/run-harness.ts
@@ -0,0 +1,115 @@
+/**
+ * Deep Research — standalone end-to-end test harness
+ *
+ * Imports the extension's REAL source (fresh, uncached) and runs the full
+ * research pipeline with real Firecrawl + real pi agent sessions.
+ *
+ * WHY: pi caches extension modules per session (keyed by path + cwd +
+ * generation) and only invalidates on /reload or cwd change. Tool calls in
+ * a live session therefore run the version loaded at session start. This
+ * harness bypasses that cache so you can iterate on src/ without reloading
+ * pi, and it prints verification stats (round stats, angle provenance,
+ * corroboration distribution, citation integrity, authority stats).
+ *
+ * Usage (from repo root):
+ *   NODE_PATH=/opt/homebrew/lib/node_modules bun scripts/run-harness.ts \
+ *     "<question>" [depth] [breadth] [audience]
+ *
+ * Requires the pi SDK to be resolvable (NODE_PATH above points at the
+ * global pi install) and Firecrawl reachable (settings.json firecrawl.baseUrl).
+ * Report is written to /tmp/deepi-harness/report.md.
+ */
+import { runDeepResearch } from "../src/research.ts";
+import type { ResearchReport } from "../src/types.ts";
+import { mkdirSync, writeFileSync } from "node:fs";
+
+const question =
+	process.argv[2] ?? "Compare Rust and Go for backend services in 2025";
+const depth = Number(process.argv[3] ?? 2);
+const breadth = Number(process.argv[4] ?? 3);
+const audience = (process.argv[5] ?? "expert") as
+	| "expert"
+	| "general"
+	| "executive";
+
+const started = Date.now();
+
+const report: ResearchReport = await runDeepResearch(
+	{
+		question,
+		depth,
+		breadth,
+		format: "markdown",
+		audience,
+	},
+	{ cwd: process.cwd() } as any,
+	(update) => {
+		const round = update.round
+			? ` [r${update.round}/${update.totalRounds}]`
+			: "";
+		console.log(`  [${update.phase}${round}] ${update.message}`);
+	},
+);
+
+console.log("\n" + "=".repeat(80));
+console.log(`DURATION: ${((Date.now() - started) / 1000).toFixed(1)}s`);
+console.log(`TOTAL SEARCHES: ${report.totalSearches}`);
+console.log(`TOTAL PAGES: ${report.totalPagesScraped}`);
+console.log(`REFERENCES: ${report.references.length}`);
+console.log(`ROUNDS: ${report.rounds.length}`);
+
+for (const round of report.rounds) {
+	console.log(
+		`  Round ${round.round}: ${round.queries.length} queries (${round.successfulSearches} ok, ${round.failedSearches} failed) → ${round.results.length} unique pages → ${round.findings.length} findings`,
+	);
+	const angles = new Map<string, number>();
+	for (const f of round.findings) {
+		const a = f.angle ?? "none";
+		angles.set(a, (angles.get(a) ?? 0) + 1);
+	}
+	console.log(
+		`    finding angles: ${Array.from(angles.entries())
+			.map(([a, n]) => `${a}(${n})`)
+			.join(", ")}`,
+	);
+	const corr = round.findings.map((f) => f.corroborationScore ?? 0);
+	const strong = corr.filter((c) => c >= 0.5).length;
+	const partial = corr.filter((c) => c > 0 && c < 0.5).length;
+	const none = corr.filter((c) => c === 0).length;
+	console.log(
+		`    corroboration: ${strong} strong(>=0.5), ${partial} partial, ${none} none`,
+	);
+}
+
+// Citation integrity: citations used in the report BODY vs reference list.
+// (Reference titles may legitimately contain "[2026]" etc. — those live in
+// the ## References section which was rebuilt authoritatively.)
+const refIds = new Set(report.references.map((r) => r.id));
+const body = report.finalReport.replace(/^## References[\s\S]*$/m, "");
+const cited = new Set(
+	[...body.matchAll(/\[(\d+)\]/g)].map((m) => Number(m[1])),
+);
+const dangling = [...cited].filter((id) => !refIds.has(id));
+console.log(
+	`CITATIONS (body only): ${cited.size} unique numbers used, ${dangling.length} dangling (${dangling.join(",")})`,
+);
+console.log(
+	`REFERENCES SECTION PRESENT: ${/^## References/m.test(report.finalReport)}`,
+);
+const iconCount = (report.finalReport.match(/[⭐✓○]/g) ?? []).length;
+console.log(`AUTHORITY ICONS IN REFERENCES: ${iconCount}`);
+
+const authorities = report.references.map((r) => r.authorityScore);
+const avgAuth =
+	authorities.reduce((a, b) => a + b, 0) / Math.max(1, authorities.length);
+console.log(
+	`AVG SOURCE AUTHORITY: ${(avgAuth * 100).toFixed(0)}% (max ${(Math.max(...authorities) * 100).toFixed(0)}%, min ${(Math.min(...authorities) * 100).toFixed(0)}%)`,
+);
+console.log(
+	"DOMAINS:",
+	[...new Set(report.references.map((r) => r.domain))].join(", "),
+);
+
+mkdirSync("/tmp/deepi-harness", { recursive: true });
+writeFileSync("/tmp/deepi-harness/report.md", report.finalReport);
+console.log("\nReport saved to /tmp/deepi-harness/report.md");
--- a/src/agent.ts
+++ b/src/agent.ts
@@ -0,0 +1,150 @@
+/**
+ * Deep Research — Agent Session helper
+ *
+ * Uses omp's in-process `createAgentSession` for LLM subtasks
+ * (query generation, result analysis, report synthesis).
+ * Pattern borrowed from ralpi's runAgentSession().
+ */
+import {
+	createAgentSession,
+	AgentRegistry,
+	SessionManager,
+} from "@oh-my-pi/pi-coding-agent";
+import type { AgentSessionEvent } from "@oh-my-pi/pi-coding-agent";
+
+/** Aggregate tool usage stats */
+export interface ToolUsage {
+	read: number;
+	write: number;
+	edit: number;
+	bash: number;
+	other: number;
+}
+
+export interface AgentResult {
+	success: boolean;
+	text: string;
+	error?: string;
+	toolUsage: ToolUsage;
+}
+
+/**
+ * Run a prompt through an in-process omp agent session.
+ * Non-blocking — the event loop stays responsive.
+ */
+export async function runAnalysisAgent(
+	systemPrompt: string,
+	taskPrompt: string,
+	cwd: string,
+	timeoutMs: number = 120_000,
+	onEvent?: (event: AgentSessionEvent) => void,
+	signal?: AbortSignal,
+): Promise<AgentResult> {
+	const toolUsage: ToolUsage = {
+		read: 0,
+		write: 0,
+		edit: 0,
+		bash: 0,
+		other: 0,
+	};
+
+	let timeoutHandle: ReturnType<typeof setTimeout> | null = null;
+	if (timeoutMs > 0) {
+		timeoutHandle = setTimeout(() => {
+			sessionRef.session?.agent.abort();
+		}, timeoutMs);
+	}
+
+	const sessionRef: {
+		session?: Awaited<ReturnType<typeof createAgentSession>>["session"];
+	} = {};
+
+	try {
+		const result = await createAgentSession({
+			cwd,
+			sessionManager: SessionManager.inMemory(cwd),
+			toolNames: ["read", "grep", "glob"],
+			restrictToolNames: true,
+			disableExtensionDiscovery: true,
+			skills: [],
+			promptTemplates: [],
+			rules: [],
+			contextFiles: [],
+			enableMCP: false,
+			enableLsp: false,
+			agentRegistry: new AgentRegistry(),
+		});
+		sessionRef.session = result.session;
+
+		const abortHandler = () => result.session.agent.abort();
+		signal?.addEventListener("abort", abortHandler, { once: true });
+
+		let finalText = "";
+		let errorMessage: string | undefined;
+
+		const unsubscribe = result.session.subscribe((event: AgentSessionEvent) => {
+			onEvent?.(event);
+
+			if (event.type === "message_end") {
+				const message = event.message as {
+					role?: string;
+					content?: unknown;
+					errorMessage?: string;
+				};
+				if (message.role !== "assistant") return;
+				if (message.errorMessage) errorMessage = message.errorMessage;
+				const text = extractAssistantText(message.content);
+				if (text) finalText = text;
+			}
+
+			if (event.type === "tool_execution_start") {
+				const name = event.toolName;
+				if (name in toolUsage) {
+					(toolUsage as unknown as Record<string, number>)[name]++;
+				} else {
+					toolUsage.other++;
+				}
+			}
+		});
+
+		if (signal?.aborted) throw new Error("Aborted");
+
+		await result.session.prompt(`${systemPrompt}\n\n${taskPrompt}`);
+		await result.session.agent.waitForIdle();
+
+		unsubscribe();
+		result.session.dispose();
+		signal?.removeEventListener("abort", abortHandler);
+		if (timeoutHandle) clearTimeout(timeoutHandle);
+
+		if (errorMessage && !finalText) {
+			return { success: false, text: "", error: errorMessage, toolUsage };
+		}
+
+		return { success: true, text: finalText.trim(), toolUsage };
+	} catch (error) {
+		if (timeoutHandle) clearTimeout(timeoutHandle);
+		return {
+			success: false,
+			text: "",
+			error: error instanceof Error ? error.message : String(error),
+			toolUsage,
+		};
+	} finally {
+		sessionRef.session?.dispose();
+	}
+}
+
+function extractAssistantText(content: unknown): string {
+	if (typeof content === "string") return content;
+	if (!Array.isArray(content)) return "";
+	return content
+		.filter(
+			(c): c is { type: string; text?: string } =>
+				!!c &&
+				typeof c === "object" &&
+				(c as { type?: string }).type === "text",
+		)
+		.map((c) => (c as { text?: string }).text ?? "")
+		.join("");
+}
--- a/src/firecrawl.ts
+++ b/src/firecrawl.ts
@@ -0,0 +1,525 @@
+/**
+ * Deep Research — direct Firecrawl HTTP client
+ *
+ * Calls the self-hosted Firecrawl API directly (same approach as the
+ * firecrawl.ts extension)
+ */
+import * as fs from "node:fs";
+import * as path from "node:path";
+import { parse as parseYaml } from "yaml";
+import type { SearchResult, EnrichedSearchResult, ContentType } from "./types";
+import { getAgentDir } from "@oh-my-pi/pi-coding-agent";
+
+/* ── Config ──────────────────────────────────────────────────────── */
+
+/**
+ * Read and merge Firecrawl settings from omp's config.yml files.
+ *
+ * Resolution order (later wins):
+ *   1. env vars FIRECRAWL_BASE_URL / FIRECRAWL_API_KEY
+ *   2. global ~/.omp/agent/config.yml → firecrawl.*
+ *   3. project .omp/config.yml → firecrawl.*
+ *   4. default http://localhost:3002 (if no baseUrl configured)
+ */
+function loadFirecrawlConfig() {
+	// Start with env var defaults
+	let baseUrl = process.env.FIRECRAWL_BASE_URL ?? "http://localhost:3002";
+	let apiKey = process.env.FIRECRAWL_API_KEY;
+
+	const agentDir = getAgentDir();
+
+	// Helper: read a config.yml and merge its firecrawl.* keys
+	const tryReadConfig = (configPath: string): void => {
+		try {
+			const raw = parseYaml(fs.readFileSync(configPath, "utf-8")) as Record<
+				string,
+				unknown
+			>;
+			const fc = (raw?.firecrawl ?? {}) as Record<string, unknown>;
+			if (typeof fc.baseUrl === "string" && fc.baseUrl.length > 0) {
+				baseUrl = fc.baseUrl;
+			}
+			if (typeof fc.apiKey === "string" && fc.apiKey.length > 0) {
+				apiKey = fc.apiKey;
+			}
+		} catch {
+			// File missing or unparseable — skip
+		}
+	};
+
+	// 1. Global config
+	tryReadConfig(path.join(agentDir, "config.yml"));
+
+	// 2. Project config (override global)
+	tryReadConfig(path.join(process.cwd(), ".omp", "config.yml"));
+
+	return {
+		baseUrl: baseUrl.replace(/\/+$/, ""),
+		apiKey,
+	};
+}
+
+const { baseUrl: BASE_URL, apiKey: API_KEY } = loadFirecrawlConfig();
+
+/* ── Domain Authority Heuristics ─────────────────────────────────── */
+
+/**
+ * Known high-authority domains and their authority scores (0.0 – 1.0).
+ * Academic, official, and established technical sources score highest.
+ */
+const AUTHORITY_DOMAINS: Record<string, number> = {
+	// Academic & scholarly
+	"arxiv.org": 0.95,
+	"scholar.google.com": 0.95,
+	"pubmed.ncbi.nlm.nih.gov": 0.95,
+	"semanticscholar.org": 0.9,
+	"ieee.org": 0.95,
+	"acm.org": 0.95,
+	"springer.com": 0.9,
+	"sciencedirect.com": 0.9,
+	"wiley.com": 0.85,
+	"nature.com": 0.95,
+	"science.org": 0.95,
+	"plos.org": 0.85,
+	// Official documentation
+	"docs.python.org": 0.9,
+	"developer.mozilla.org": 0.9,
+	"learn.microsoft.com": 0.85,
+	"developer.apple.com": 0.85,
+	"kubernetes.io": 0.85,
+	"react.dev": 0.85,
+	"nextjs.org": 0.8,
+	// Official language/platform docs
+	"go.dev": 0.9,
+	"golang.org": 0.9,
+	"rust-lang.org": 0.9,
+	"nodejs.org": 0.85,
+	"python.org": 0.85,
+	"typescriptlang.org": 0.85,
+	"openai.com": 0.8,
+	"anthropic.com": 0.8,
+	"cloud.google.com": 0.8,
+	"aws.amazon.com": 0.8,
+	"azure.microsoft.com": 0.8,
+	"postgresql.org": 0.85,
+	"sqlite.org": 0.85,
+	"redis.io": 0.85,
+	"docker.com": 0.75,
+	"elastic.co": 0.75,
+	"grafana.com": 0.75,
+	"datadoghq.com": 0.75,
+	"cloudflare.com": 0.8,
+	"blog.cloudflare.com": 0.8,
+	"techempower.com": 0.8,
+	"goframe.org": 0.75,
+	"corrode.dev": 0.6,
+	"evrone.com": 0.4,
+	"rustify.rs": 0.4,
+	"core.cz": 0.4,
+	// Medical / clinical
+	"mayoclinic.org": 0.9,
+	"heart.org": 0.85,
+	"researchgate.net": 0.6,
+	"healthline.com": 0.5,
+	"medicalnewstoday.com": 0.5,
+	"webmd.com": 0.45,
+	"verywellhealth.com": 0.5,
+	// Databases & dev tools
+	"mysql.com": 0.85,
+	"mariadb.org": 0.85,
+	"cockroachlabs.com": 0.7,
+	"timescale.com": 0.7,
+	"mongodb.com": 0.8,
+	"liquibase.com": 0.6,
+	"sqlpipe.com": 0.5,
+	"data-tune.com": 0.4,
+	"binaryigor.com": 0.4,
+	// Government & non-profits
+	".gov": 0.9,
+	".edu": 0.85,
+	"who.int": 0.9,
+	"worldbank.org": 0.85,
+	"oecd.org": 0.85,
+	// Established tech & news
+	"github.com": 0.8,
+	"stackoverflow.com": 0.7,
+	"medium.com": 0.4,
+	"dev.to": 0.5,
+	"wikipedia.org": 0.7,
+	"reuters.com": 0.8,
+	"apnews.com": 0.8,
+	"bbc.com": 0.75,
+	"nytimes.com": 0.75,
+	"theguardian.com": 0.7,
+	"techcrunch.com": 0.6,
+	"arstechnica.com": 0.65,
+	"wired.com": 0.65,
+	"infoworld.com": 0.55,
+	// Practitioner/aggregator content with measurable quality
+	"github.io": 0.6,
+	"crates.io": 0.7,
+	"docs.rs": 0.75,
+	"digitalocean.com": 0.6,
+	"freecodecamp.org": 0.6,
+	"geeksforgeeks.org": 0.35,
+	"stackexchange.com": 0.65,
+	"huggingface.co": 0.65,
+	"nasa.gov": 0.9,
+	"mit.edu": 0.9,
+	"stanford.edu": 0.9,
+	"harvard.edu": 0.9,
+	"ox.ac.uk": 0.9,
+	"cam.ac.uk": 0.9,
+	// Low-authority: personal social / SEO content
+	"linkedin.com": 0.25,
+	"reddit.com": 0.25,
+	"x.com": 0.3,
+	"twitter.com": 0.3,
+	"youtube.com": 0.3,
+	"blogspot.com": 0.25,
+	"substack.com": 0.3,
+	"hashnode.dev": 0.35,
+	"quora.com": 0.3,
+	"netguru.com": 0.3,
+	"relisoftware.com": 0.3,
+	"dasroot.net": 0.3,
+	"devgenius.io": 0.3,
+	"devnewsletter.com": 0.3,
+};
+
+/**
+ * Known low-quality SEO/comparison-spam domains. Content is often
+ * auto-generated, republished from other sites, or thin on substance.
+ * These get a hard authority floor so they never rank above real content.
+ */
+const LOW_AUTHORITY_DOMAINS: Record<string, number> = {
+	"markaicode.com": 0.15,
+	"bytegoblin.io": 0.2,
+	"towardsdev.com": 0.2,
+	"rustvsgo.com": 0.3,
+	"seekingalpha.com": 0.3,
+	"investopedia.com": 0.55,
+	"devops-daily.com": 0.3,
+};
+
+/** Content-type hints based on domain patterns */
+const CONTENT_TYPE_HINTS: [RegExp, ContentType][] = [
+	[
+		/arxiv\.org|semanticscholar|ieee\.org|acm\.org|springer|sciencedirect|pubmed\.ncbi/,
+		"paper",
+	],
+	[
+		/docs\.|learn\.|developer\.|kubernetes\.io|react\.dev|nextjs\.org/,
+		"documentation",
+	],
+	[/wikipedia\.org|stackoverflow\.com|medium\.com|dev\.to/, "forum"],
+	[
+		/reuters\.com|apnews\.com|bbc\.com|nytimes\.com|techcrunch|arstechnica|wired/,
+		"news",
+	],
+	[/\.gov|\.edu|who\.int|worldbank|oecd\.org/, "official"],
+	[/github\.com/, "documentation"],
+];
+
+/* ── Source enrichment helpers ───────────────────────────────────── */
+
+/**
+ * Extract the registered domain from a URL (e.g., "blog.example.com" → "example.com").
+ * Uses a simple 2-part TLD heuristic. For common cases like .co.uk this is approximate.
+ */
+function extractDomain(url: string): string {
+	try {
+		const hostname = new URL(url).hostname.toLowerCase();
+		// Special-case common multi-part TLDs
+		const multiPartTlds =
+			/\.(co\.uk|org\.uk|ac\.uk|gov\.uk|com\.au|co\.jp|co\.kr|com\.br)$/;
+		const parts = hostname.split(".");
+		if (multiPartTlds.test(hostname) && parts.length >= 3) {
+			return parts.slice(-3).join(".");
+		}
+		return parts.slice(-2).join(".");
+	} catch {
+		return url.replace(/^https?:\/\//, "").split("/")[0] ?? url;
+	}
+}
+
+function computeAuthorityScore(domain: string): number {
+	// Hard floor for known low-authority domains first
+	if (LOW_AUTHORITY_DOMAINS[domain] !== undefined)
+		return LOW_AUTHORITY_DOMAINS[domain];
+
+	// Direct match first
+	if (AUTHORITY_DOMAINS[domain]) return AUTHORITY_DOMAINS[domain];
+
+	// Suffix matches (.gov, .edu, etc.)
+	for (const [key, score] of Object.entries(AUTHORITY_DOMAINS)) {
+		if (key.startsWith(".") && domain.endsWith(key)) return score;
+	}
+
+	// Subdomain matches (e.g., blog.example.com matches example.com)
+	const parent = domain.split(".").slice(-2).join(".");
+	if (parent !== domain && AUTHORITY_DOMAINS[parent]) {
+		return AUTHORITY_DOMAINS[parent] * 0.9;
+	}
+
+	// github.io personal sites: treat as practitioner content (medium)
+	if (domain.endsWith(".github.io")) return 0.55;
+
+	return 0.3; // Unknown / low-authority default
+}
+
+function detectContentType(url: string, description: string): ContentType {
+	const lowerUrl = url.toLowerCase();
+	const lowerDesc = description.toLowerCase();
+
+	for (const [pattern, type] of CONTENT_TYPE_HINTS) {
+		if (pattern.test(lowerUrl)) return type;
+	}
+
+	// Heuristics from description text
+	if (/paper|research|study|experiment|analysis\b/.test(lowerDesc))
+		return "paper";
+	if (/documentation|guide|tutorial|api|reference/.test(lowerDesc))
+		return "documentation";
+	if (/blog|post|article|opinion/.test(lowerDesc)) return "blog";
+	if (/news|report|announce|release/.test(lowerDesc)) return "news";
+	if (/forum|discussion|question|answer|thread/.test(lowerDesc)) return "forum";
+
+	return "other";
+}
+
+function tryParseDate(dateStr: string | undefined | null): Date | null {
+	if (!dateStr) return null;
+	const d = new Date(dateStr);
+	return isNaN(d.getTime()) ? null : d;
+}
+
+/**
+ * Normalize a title for near-duplicate detection: lowercase, strip
+ * punctuation, collapse whitespace, drop common filler words.
+ * Two syndicated copies of the same article normalize identically.
+ */
+export function normalizeTitle(title: string): string {
+	return title
+		.toLowerCase()
+		.replace(/[^a-z0-9\s]/g, " ")
+		.replace(
+			/\b(?:the|a|an|of|for|and|or|in|on|with|vs|versus|to|how|what|why|2024|2025|2026)\b/g,
+			" ",
+		)
+		.replace(/\s+/g, " ")
+		.trim();
+}
+
+/**
+ * Near-duplicate check between two titles: normalized forms must share
+ * a substantial token overlap (same core words in the same order).
+ */
+export function isNearDuplicateTitle(a: string, b: string): boolean {
+	const normA = normalizeTitle(a);
+	const normB = normalizeTitle(b);
+	if (!normA || !normB) return false;
+	if (normA === normB) return true;
+
+	const tokensA = normA.split(" ");
+	const tokensB = normB.split(" ");
+	if (tokensA.length < 3 || tokensB.length < 3) return normA === normB;
+
+	// Check if one title is a substring of the other (after normalization)
+	if (normA.includes(normB) || normB.includes(normA)) return true;
+
+	// Jaccard-ish overlap on the shorter token set
+	const [short, long] =
+		tokensA.length <= tokensB.length ? [tokensA, tokensB] : [tokensB, tokensA];
+	const overlap = short.filter((t) => long.includes(t)).length;
+	return overlap / short.length >= 0.75;
+}
+
+/**
+ * Enrich a raw search result with source authority metadata.
+ * Accepts extra fields (e.g. date) from the Firecrawl API response.
+ */
+export function enrichResult(
+	result: SearchResult & Record<string, unknown>,
+): EnrichedSearchResult {
+	const domain = extractDomain(result.url);
+	return {
+		...result,
+		domain,
+		authorityScore: computeAuthorityScore(domain),
+		publishedDate: tryParseDate(result.date as string | undefined),
+		contentType: detectContentType(result.url, result.description),
+	};
+}
+
+/* ── Helpers ──────────────────────────────────────────────────────── */
+
+async function firecrawlRequest(
+	endpoint: string,
+	body: Record<string, unknown>,
+	signal?: AbortSignal,
+): Promise<unknown> {
+	const headers: Record<string, string> = {
+		"Content-Type": "application/json",
+	};
+	if (API_KEY) {
+		headers["Authorization"] = `Bearer ${API_KEY}`;
+	}
+
+	const res = await fetch(`${BASE_URL}/v1/${endpoint}`, {
+		method: "POST",
+		headers,
+		body: JSON.stringify(body),
+		signal,
+	});
+
+	if (!res.ok) {
+		const text = await res.text();
+		throw new Error(
+			`Firecrawl ${endpoint} failed (${res.status}): ${text.slice(0, 500)}`,
+		);
+	}
+
+	return res.json();
+}
+
+/**
+ * firecrawlRequest with retry-with-backoff for transient failures
+ * (429 rate limits, 5xx server errors, network blips). Does NOT retry
+ * 4xx client errors (invalid requests) or aborts.
+ */
+async function firecrawlRequestWithRetry(
+	endpoint: string,
+	body: Record<string, unknown>,
+	signal?: AbortSignal,
+	retries: number = 2,
+): Promise<unknown> {
+	let lastError: unknown;
+	for (let attempt = 0; attempt <= retries; attempt++) {
+		if (signal?.aborted) throw new Error("Aborted");
+		try {
+			return await firecrawlRequest(endpoint, body, signal);
+		} catch (error) {
+			lastError = error;
+			const status =
+				error instanceof Error
+					? Number(/failed \((\d+)\)/.exec(error.message)?.[1] ?? 0)
+					: 0;
+			// Don't retry aborts or 4xx client errors (other than 429)
+			if (
+				signal?.aborted ||
+				(status >= 400 && status < 500 && status !== 429)
+			) {
+				throw error;
+			}
+			if (attempt < retries) {
+				const delayMs = 400 * 2 ** attempt + Math.random() * 200;
+				await new Promise((r) => setTimeout(r, delayMs));
+			}
+		}
+	}
+	throw lastError;
+}
+
+export async function isFirecrawlReachable(): Promise<boolean> {
+	try {
+		const res = await fetch(`${BASE_URL}/v1/scrape`, {
+			method: "POST",
+			headers: {
+				"Content-Type": "application/json",
+				...(API_KEY ? { Authorization: `Bearer ${API_KEY}` } : {}),
+			},
+			body: JSON.stringify({ url: "https://example.com", formats: ["links"] }),
+			signal: AbortSignal.timeout(10_000),
+		});
+		return res.ok;
+	} catch {
+		return false;
+	}
+}
+
+/* ── Search ───────────────────────────────────────────────────────── */
+
+/**
+ * Search the web and return structured, enriched results.
+ * Uses Firecrawl's search endpoint with scrape to get full page content.
+ */
+export async function searchWeb(
+	query: string,
+	limit: number = 5,
+	signal?: AbortSignal,
+): Promise<EnrichedSearchResult[]> {
+	const body: Record<string, unknown> = {
+		query,
+		limit: Math.min(limit, 10),
+		scrapeOptions: {
+			formats: ["markdown"],
+			onlyMainContent: true,
+		},
+	};
+
+	const result = await firecrawlRequestWithRetry("search", body, signal);
+
+	if (!result || typeof result !== "object") return [];
+
+	const res = result as {
+		success?: boolean;
+		data?: Record<string, unknown>[];
+		error?: string;
+	};
+
+	if (!res.success || !res.data) return [];
+
+	const rawResults: (SearchResult & Record<string, unknown>)[] = res.data
+		.map((doc) => ({
+			title: (doc.title as string) ?? "",
+			url: (doc.url as string) ?? "",
+			description: (doc.description as string) ?? "",
+			markdown: (doc.markdown as string) ?? "",
+			// Preserve extra fields for date extraction
+			...doc,
+		}))
+		.filter((r) => {
+			// Keep results with a meaningful body OR a substantive description.
+			// Filters out stub pages / pure navigation results that would
+			// waste analysis tokens.
+			const hasBody = (r.markdown ?? "").trim().length >= 150;
+			const hasSubstantiveDesc = (r.description ?? "").trim().length >= 40;
+			return hasBody || hasSubstantiveDesc;
+		});
+
+	// Enrich each result with source metadata
+	return rawResults.map(enrichResult);
+}
+
+/* ── Scrape ───────────────────────────────────────────────────────── */
+
+/**
+ * Scrape a single URL and return its markdown content.
+ */
+export async function scrapeUrl(
+	url: string,
+	signal?: AbortSignal,
+): Promise<{ title: string; markdown: string; links: string[] } | null> {
+	const result = await firecrawlRequestWithRetry(
+		"scrape",
+		{ url, formats: ["markdown"] },
+		signal,
+	);
+
+	if (!result || typeof result !== "object") return null;
+
+	const res = result as {
+		success?: boolean;
+		data?: Record<string, unknown>;
+		error?: string;
+	};
+
+	if (!res.success || !res.data) return null;
+
+	return {
+		title: (res.data.title as string) ?? "",
+		markdown: (res.data.markdown as string) ?? "",
+		links: (res.data.links as string[]) ?? [],
+	};
+}
--- a/src/queries.ts
+++ b/src/queries.ts
@@ -0,0 +1,625 @@
+/**
+ * Deep Research — Search query generation & refinement
+ *
+ * Uses an LLM agent to generate search queries from different research
+ * angles, then analyzes results to produce follow-up queries.
+ */
+import type {
+	SearchQuery,
+	Finding,
+	ResearchRound,
+	EnrichedSearchResult,
+} from "./types";
+import { runAnalysisAgent } from "./agent";
+
+/* ── System Prompts ──────────────────────────────────────────────── */
+
+const DECOMPOSE_SYSTEM = `You are a research methodology expert. Given a broad research question, your job is to break it down into 4-7 focused sub-questions that, when answered, collectively provide a complete answer to the original question.
+
+Guidelines:
+- Each sub-question should tackle ONE specific facet of the research question
+- Cover different dimensions: what, how, why, who, comparison, evidence, implications
+- Sub-questions should be independently researchable via web search
+- Avoid overlap between sub-questions
+- Prioritize questions that will surface concrete evidence over speculative ones
+
+Output ONLY a JSON array of sub-question strings.
+
+Example:
+Input: "What are the benefits and risks of artificial intelligence in healthcare?"
+Output: ["What specific AI technologies are currently deployed in clinical healthcare settings?", "What peer-reviewed evidence exists for AI improving diagnostic accuracy?", "What are the documented risks and failure cases of AI in healthcare?", "How do regulatory frameworks (FDA, EMA) address AI-based medical devices?", "What do healthcare practitioners report as barriers to AI adoption?"]
+`;
+
+const GENERATE_QUERIES_SYSTEM = `You are a research methodology expert. Your role is to generate effective web search queries that will yield high-quality, diverse information about a research topic.
+
+Guidelines:
+- Create queries from DIFFERENT angles (technical, practical, comparative, critical, forward-looking, authoritative)
+- Each query should target a specific facet of the question
+- Queries should use keywords that search engines rank well (avoid overly long questions)
+- Cover contrasting viewpoints and alternative approaches
+- Include queries for finding authoritative sources (docs, papers, official sites)
+- Prioritize recent information where relevant
+
+Output ONLY a JSON array of objects with fields:
+- "query": the search query string
+- "rationale": why this query will help answer the research question
+- "angle": one of "technical" | "practical" | "comparative" | "critical" | "forward-looking" | "authoritative" | "historical" | "case-study" | "data-statistics" | "ethical"
+
+Example:
+[
+  {"query": "Rust async/await performance benchmarks 2024", "rationale": "Understanding current performance characteristics", "angle": "technical"},
+  {"query": "Rust vs Go concurrency patterns comparison", "rationale": "Comparative analysis helps contextualize trade-offs", "angle": "comparative"}
+]
+`;
+
+const FOLLOWUP_SYSTEM = `You are a research analyst. Given the research question, sub-questions, and findings so far, your job is to identify what's still unknown and generate follow-up search queries to fill those gaps.
+
+Look for:
+- Claims made without sufficient evidence
+- Conflicting information that needs resolution
+- Angles that haven't been explored yet
+- Missing authoritative sources (papers, official docs, primary data)
+- Practical implications that need more detail
+- Recent developments that might have updated findings
+
+Guidelines:
+- Do NOT repeat or paraphrase queries already explored — aim for genuinely new angles
+- Prefer querying for authoritative/primary sources over more blog posts when evidence is weak
+- When findings conflict, craft a query designed to resolve the contradiction
+- Keep queries concise and keyword-rich
+
+Output ONLY a JSON array of objects with fields:
+- "query": the search query string
+- "rationale": what gap this query fills or what angle it explores
+- "angle": one of "technical" | "practical" | "comparative" | "critical" | "forward-looking" | "authoritative" | "historical" | "case-study" | "data-statistics" | "ethical"
+`;
+
+/* ── JSON parsing helpers ────────────────────────────────────────── */
+
+/**
+ * Robustly parse a JSON array from LLM output.
+ *
+ * LLMs frequently wrap JSON in ```json fences, prepend prose like
+ * "Here are the queries:", or emit trailing punctuation. This strips
+ * fences and extracts the first bracketed array before parsing.
+ *
+ * Returns null when no array can be extracted.
+ */
+function parseJsonArray(text: string): unknown[] | null {
+	if (!text) return null;
+
+	// Strip markdown code fences
+	const withoutFences = text
+		.replace(/```(?:json|javascript)?\s*/gi, "")
+		.replace(/```/g, "");
+
+	// Find the first '[' ... ']' block (arrays are our target shape)
+	const start = withoutFences.indexOf("[");
+	const end = withoutFences.lastIndexOf("]");
+	if (start === -1 || end === -1 || end <= start) return null;
+
+	const candidate = withoutFences.slice(start, end + 1);
+	try {
+		const parsed = JSON.parse(candidate);
+		return Array.isArray(parsed) ? parsed : null;
+	} catch {
+		// Try to salvage: strip trailing commas (common LLM artifact)
+		try {
+			const fixed = candidate.replace(/,\s*([}\]])/g, "$1");
+			const parsed = JSON.parse(fixed);
+			return Array.isArray(parsed) ? parsed : null;
+		} catch {
+			return null;
+		}
+	}
+}
+
+/** Map a parsed array entry to a SearchQuery, tolerating missing fields. */
+function toSearchQuery(q: Record<string, unknown>): SearchQuery | null {
+	const query = String(q.query ?? "").trim();
+	if (!query) return null;
+	return {
+		query,
+		rationale: String(q.rationale ?? "").trim(),
+		angle: String(q.angle ?? "technical").trim() || "technical",
+	};
+}
+
+/* ── Sub-Question Decomposition ───────────────────────────────────── */
+
+/**
+ * Decompose a broad research question into focused, independently
+ * researchable sub-questions. Returns the sub-questions or an empty
+ * array if the LLM call fails.
+ */
+export async function decomposeQuestion(
+	question: string,
+	cwd: string,
+	signal?: AbortSignal,
+): Promise<string[]> {
+	const taskPrompt = `Break down this research question into 4-7 focused sub-questions:\n\n${question}`;
+
+	const result = await runAnalysisAgent(
+		DECOMPOSE_SYSTEM,
+		taskPrompt,
+		cwd,
+		60_000,
+		undefined,
+		signal,
+	);
+
+	if (!result.success || !result.text) return [];
+
+	const parsed = parseJsonArray(result.text);
+	if (parsed) {
+		const subQuestions = parsed
+			.map(String)
+			.map((s: string) => s.trim())
+			.filter((s: string) => s.length > 10);
+		if (subQuestions.length > 0) return subQuestions;
+	}
+
+	return [];
+}
+
+/* ── Query Generation ────────────────────────────────────────────── */
+
+/**
+ * Generate initial search queries for a research question.
+ * When sub-questions are available, generates queries per sub-question
+ * for better depth and diversity.
+ */
+export async function generateQueries(
+	question: string,
+	count: number,
+	cwd: string,
+	signal?: AbortSignal,
+	subQuestions?: string[],
+): Promise<SearchQuery[]> {
+	// If we have sub-questions, generate queries distributed across them
+	if (subQuestions && subQuestions.length > 0) {
+		const queriesPerSub = Math.max(1, Math.ceil(count / subQuestions.length));
+		const allQueries: SearchQuery[] = [];
+
+		for (const subQ of subQuestions) {
+			if (allQueries.length >= count) break;
+
+			const taskPrompt = `Research question: ${question}\nSub-question: ${subQ}\n\nGenerate ${queriesPerSub} search query(ies) to answer this sub-question specifically.`;
+
+			const result = await runAnalysisAgent(
+				GENERATE_QUERIES_SYSTEM,
+				taskPrompt,
+				cwd,
+				60_000,
+				undefined,
+				signal,
+			);
+
+			if (!result.success || !result.text) continue;
+
+			const parsed = parseJsonArray(result.text);
+			if (parsed) {
+				const queries = parsed
+					.slice(0, queriesPerSub)
+					.map((q) => toSearchQuery(q as Record<string, unknown>))
+					.filter((q): q is SearchQuery => q !== null);
+				allQueries.push(...queries);
+			}
+		}
+
+		if (allQueries.length > 0) {
+			return allQueries.slice(0, count);
+		}
+	}
+
+	// Fall through to standard query generation
+	const taskPrompt = `Research question: ${question}
+
+Generate ${count} diverse search queries to research this topic effectively. Cover different angles.`;
+
+	const result = await runAnalysisAgent(
+		GENERATE_QUERIES_SYSTEM,
+		taskPrompt,
+		cwd,
+		60_000,
+		undefined,
+		signal,
+	);
+
+	if (!result.success || !result.text) {
+		return generateFallbackQueries(question, count);
+	}
+
+	try {
+		const parsed = parseJsonArray(result.text);
+		if (parsed && parsed.length > 0) {
+			return parsed
+				.slice(0, count)
+				.map((q) => toSearchQuery(q as Record<string, unknown>))
+				.filter((q): q is SearchQuery => q !== null);
+		}
+	} catch {
+		// JSON parse failed, fall back
+	}
+
+	return generateFallbackQueries(question, count);
+}
+
+/* ── Follow-up Query Generation ──────────────────────────────────── */
+
+/**
+ * Generate follow-up queries based on findings from previous rounds.
+ */
+export async function generateFollowUpQueries(
+	question: string,
+	rounds: ResearchRound[],
+	count: number,
+	cwd: string,
+	signal?: AbortSignal,
+): Promise<SearchQuery[]> {
+	// Build a summary of findings so far
+	const allFindings = rounds.flatMap((r) => r.findings);
+	const findingsSummary = allFindings
+		.map((f) => {
+			const corr =
+				f.corroborationScore !== undefined
+					? ` [corroboration: ${(f.corroborationScore * 100).toFixed(0)}%]`
+					: "";
+			return `- ${f.title}: ${f.summary} (confidence: ${f.confidence}${corr})`;
+		})
+		.join("\n");
+
+	const exploredAngles = rounds
+		.flatMap((r) => r.queries)
+		.map((q) => `[${q.angle}] ${q.query} — ${q.rationale}`)
+		.join("\n");
+
+	// Find low-corroboration or low-confidence topics
+	const gaps = allFindings
+		.filter((f) => f.confidence === "low" || (f.corroborationScore ?? 1) < 0.5)
+		.map((f) => `Gap: ${f.title} — ${f.summary}`)
+		.join("\n");
+
+	const taskPrompt = `Research question: ${question}
+
+Queries already explored:
+${exploredAngles}
+
+Findings so far:
+${findingsSummary}
+
+${gaps ? `Remaining knowledge gaps:\n${gaps}` : ""}
+
+Generate ${count} follow-up search queries to fill remaining gaps and deepen the research. Do not repeat or paraphrase the queries already explored.`;
+
+	const result = await runAnalysisAgent(
+		FOLLOWUP_SYSTEM,
+		taskPrompt,
+		cwd,
+		60_000,
+		undefined,
+		signal,
+	);
+
+	if (!result.success || !result.text) {
+		return [];
+	}
+
+	const exploredNormalized = new Set(
+		rounds.flatMap((r) => r.queries).map((q) => normalizeQueryText(q.query)),
+	);
+
+	const parsed = parseJsonArray(result.text);
+	if (parsed && parsed.length > 0) {
+		const fresh: SearchQuery[] = [];
+		for (const q of parsed.slice(0, count)) {
+			const sq = toSearchQuery(q as Record<string, unknown>);
+			if (!sq) continue;
+			const normalized = normalizeQueryText(sq.query);
+			// Skip queries that are near-duplicates of already-explored ones
+			if (exploredNormalized.has(normalized)) continue;
+			if (fresh.some((fq) => normalizeQueryText(fq.query) === normalized))
+				continue;
+			exploredNormalized.add(normalized);
+			fresh.push(sq);
+		}
+		return fresh;
+	}
+
+	return [];
+}
+
+/**
+ * Lightweight query-text normalization for duplicate detection.
+ */
+function normalizeQueryText(query: string): string {
+	return query
+		.toLowerCase()
+		.replace(/[^a-z0-9\s]/g, " ")
+		.replace(/\s+/g, " ")
+		.trim();
+}
+
+/* ── Fallback Query Generation ────────────────────────────────────── */
+
+/**
+ * Fallback query generation when the LLM call fails.
+ */
+function generateFallbackQueries(
+	question: string,
+	count: number,
+): SearchQuery[] {
+	const queries: SearchQuery[] = [];
+	const angles = [
+		{ angle: "technical", desc: "technical details and specifications" },
+		{
+			angle: "practical",
+			desc: "practical examples, tutorials, and best practices",
+		},
+		{ angle: "comparative", desc: "comparisons with alternatives" },
+		{ angle: "critical", desc: "limitations, challenges, and criticisms" },
+		{ angle: "forward-looking", desc: "future trends and developments" },
+	];
+
+	for (let i = 0; i < Math.min(count, angles.length); i++) {
+		queries.push({
+			query: `${question} ${angles[i].desc}`,
+			rationale: `Exploring ${angles[i].desc} related to the research question`,
+			angle: angles[i].angle as SearchQuery["angle"],
+		});
+	}
+
+	return queries;
+}
+
+/* ── Analysis ────────────────────────────────────────────────────── */
+
+const ANALYZE_SYSTEM = `You are a research analyst. Given search results for a specific query, extract key findings.
+
+For each finding:
+- Give it a concise, specific title (a claim, not a topic)
+- Summarize what was found in 1-3 sentences, focused on evidence
+- List which source URLs support this finding
+- Include 1-2 key quotes from the sources
+- Rate your confidence (high/medium/low) based on source authority and consistency
+
+Guidelines:
+- Extract 3-6 findings maximum, prioritizing the most decision-relevant
+- Prefer findings with concrete evidence over generic observations
+- Ignore boilerplate, navigation text, and irrelevant tangents in the content
+- Do NOT invent quotes — only use text that appears in the provided content
+- When sources conflict, note the conflict in the summary
+
+Output ONLY a JSON array of objects with fields:
+- "title": concise finding title
+- "summary": 1-3 sentence summary
+- "sources": array of source URLs
+- "keyQuotes": array of 1-2 key quotes
+- "confidence": "high" | "medium" | "low"`;
+
+/**
+ * Analyze search results for a specific query and extract findings.
+ */
+export async function analyzeResults(
+	query: string,
+	results: EnrichedSearchResult[],
+	cwd: string,
+	signal?: AbortSignal,
+	angle?: string,
+): Promise<Finding[]> {
+	// Include authority metadata in the prompt so the LLM can consider source quality.
+	// Token budget: give high-authority sources generous space, truncate
+	// low-authority/SEO content aggressively so junk doesn't dominate the prompt.
+	const MAX_CHARS_HIGH_AUTH = 3500;
+	const MAX_CHARS_LOW_AUTH = 1200;
+
+	const resultsText = results
+		.map((r, i) => {
+			const maxChars =
+				r.authorityScore >= 0.6 ? MAX_CHARS_HIGH_AUTH : MAX_CHARS_LOW_AUTH;
+			const content = r.markdown.slice(0, maxChars).trim();
+			const body =
+				content.length > 0
+					? content
+					: `(no body content; description only)\n${r.description}`;
+			return `--- Result ${i + 1} ---\nTitle: ${r.title}\nURL: ${r.url}\nDomain: ${r.domain}\nAuthority Score: ${(r.authorityScore * 100).toFixed(0)}%\nContent Type: ${r.contentType}\nDescription: ${r.description}\nContent:\n${body}`;
+		})
+		.join("\n\n");
+
+	const taskPrompt = `Search query: "${query}"${angle ? ` (angle: ${angle})` : ""}
+
+Search results:
+${resultsText}
+
+Extract key findings from these results. Consider source authority when rating confidence.`;
+
+	const result = await runAnalysisAgent(
+		ANALYZE_SYSTEM,
+		taskPrompt,
+		cwd,
+		90_000,
+		undefined,
+		signal,
+	);
+
+	if (!result.success || !result.text) return [];
+
+	const parsed = parseJsonArray(result.text);
+	if (parsed) {
+		return parsed
+			.map((f) => {
+				const entry = f as Record<string, unknown>;
+				return {
+					title: String(entry.title ?? "").trim(),
+					summary: String(entry.summary ?? "").trim(),
+					sources: Array.isArray(entry.sources)
+						? entry.sources.map(String)
+						: [],
+					keyQuotes: Array.isArray(entry.keyQuotes)
+						? entry.keyQuotes.map(String)
+						: [],
+					confidence: (["high", "medium", "low"].includes(
+						String(entry.confidence),
+					)
+						? String(entry.confidence)
+						: "medium") as Finding["confidence"],
+					// Provenance: which query and angle produced this finding
+					query,
+					angle,
+				};
+			})
+			.filter((f) => f.title && f.summary);
+	}
+
+	return [];
+}
+
+/* ── Corroboration Tracking ──────────────────────────────────────── */
+
+/**
+ * Cross-reference all findings to compute corroboration scores.
+ *
+ * For each finding, we check:
+ * 1. How many other findings reference the same or similar source URLs
+ * 2. The authority scores of the supporting sources
+ * 3. Whether independent domains support the same claim
+ *
+ * Returns the findings with added corroborationScore, bestSourceAuthority,
+ * and avgSourceAuthority.
+ */
+export function computeCorroboration(
+	findings: Finding[],
+	urlQueryCounts?: Map<string, number>,
+): Finding[] {
+	if (findings.length === 0) return [];
+
+	// Collect all unique source URLs and their authority scores
+	// In a real implementation, we'd map URLs to EnrichedSearchResult authority scores
+	// For now, extract domain-level patterns
+
+	// Build a map of domain -> authority scores from source URLs
+	const domainAuthority = new Map<string, number>();
+	for (const finding of findings) {
+		for (const url of finding.sources) {
+			try {
+				const domain = extractDomainSimple(url);
+				if (!domainAuthority.has(domain)) {
+					domainAuthority.set(domain, heuristicDomainScore(domain));
+				}
+			} catch {
+				// skip invalid URLs
+			}
+		}
+	}
+
+	return findings.map((finding) => {
+		if (finding.sources.length === 0) {
+			return {
+				...finding,
+				corroborationScore: 0,
+				bestSourceAuthority: 0,
+				avgSourceAuthority: 0,
+			};
+		}
+
+		// Compute source authority stats
+		const authorities: number[] = finding.sources.map((url) => {
+			try {
+				const domain = extractDomainSimple(url);
+				return domainAuthority.get(domain) ?? 0.3;
+			} catch {
+				return 0.3;
+			}
+		});
+
+		const bestAuthority = Math.max(...authorities);
+		const avgAuthority =
+			authorities.reduce((a, b) => a + b, 0) / authorities.length;
+
+		// Compute corroboration.
+		//
+		// PRIMARY signal (when urlQueryCounts is provided): what fraction of
+		// this finding's sources were independently surfaced by multiple
+		// DIFFERENT search queries? A source found by several independent
+		// searches is genuinely corroborated; same-query duplicates do not
+		// count (findings from one query analyzed the same result set).
+		//
+		// FALLBACK signal (no map): domain-level agreement across findings
+		// from different queries.
+		let corroborationScore: number;
+
+		if (urlQueryCounts && urlQueryCounts.size > 0) {
+			const multiQuerySources = finding.sources.filter(
+				(url) => (urlQueryCounts.get(url) ?? 1) > 1,
+			).length;
+			corroborationScore =
+				finding.sources.length > 0
+					? multiQuerySources / finding.sources.length
+					: 0;
+		} else {
+			// Fallback: cross-query agreement by shared domain
+			const myDomains = new Set(
+				finding.sources.map((u) => extractDomainSimple(u)),
+			);
+			let corroboratingFindings = 0;
+			let independentOthers = 0;
+
+			for (const other of findings) {
+				if (other === finding) continue;
+				// Same query provenance = same analyzed result set = not independent
+				if (other.query && finding.query && other.query === finding.query) {
+					continue;
+				}
+				independentOthers++;
+				const otherDomains = new Set(
+					other.sources.map((u) => extractDomainSimple(u)),
+				);
+				const shared = [...myDomains].some((d) => otherDomains.has(d));
+				if (shared) corroboratingFindings++;
+			}
+
+			corroborationScore =
+				independentOthers > 0
+					? Math.min(1, corroboratingFindings / independentOthers)
+					: 0;
+		}
+
+		return {
+			...finding,
+			corroborationScore: Math.round(corroborationScore * 100) / 100,
+			bestSourceAuthority: Math.round(bestAuthority * 100) / 100,
+			avgSourceAuthority: Math.round(avgAuthority * 100) / 100,
+		};
+	});
+}
+
+/**
+ * Simple domain extraction (avoids URL constructor for compatibility).
+ */
+function extractDomainSimple(url: string): string {
+	const match = url.match(/https?:\/\/([^/]+)/);
+	if (!match) return url;
+	const hostname = match[1].toLowerCase();
+	const parts = hostname.split(".");
+	const multiPartTlds =
+		/\.(co\.uk|org\.uk|ac\.uk|gov\.uk|com\.au|co\.jp|co\.kr|com\.br)$/;
+	if (multiPartTlds.test(hostname) && parts.length >= 3) {
+		return parts.slice(-3).join(".");
+	}
+	return parts.slice(-2).join(".");
+}
+
+/**
+ * Very basic domain score heuristic without the full domain list.
+ */
+function heuristicDomainScore(domain: string): number {
+	if (/\.gov$|\.edu$/.test(domain)) return 0.85;
+	if (/arxiv|scholar|pubmed|ieee|acm|springer|nature|science/.test(domain))
+		return 0.9;
+	if (/github|gitlab|bitbucket/.test(domain)) return 0.75;
+	if (/wikipedia|stackoverflow|medium|dev\.to/.test(domain)) return 0.55;
+	if (/docs\.|learn\.|developer\./.test(domain)) return 0.8;
+	if (/reuters|apnews|bbc|nytimes|bloomberg/.test(domain)) return 0.75;
+	if (/blog|forum|reddit/.test(domain)) return 0.3;
+	return 0.4;
+}
--- a/src/report.ts
+++ b/src/report.ts
@@ -0,0 +1,530 @@
+/**
+ * Deep Research — Report synthesis
+ *
+ * Takes all research rounds and synthesizes a comprehensive report
+ * using an LLM agent. Produces:
+ *  - Numbered inline citations with a bibliography
+ *  - Layered report: TL;DR → Executive Summary → Key Findings
+ *    → Detailed Analysis → Limitations/Gaps → References
+ *  - Audience-aware tone adjustment
+ */
+import type {
+	ResearchRound,
+	ResearchConfig,
+	Reference,
+	Finding,
+} from "./types";
+import { runAnalysisAgent } from "./agent";
+import { isNearDuplicateTitle } from "./firecrawl";
+
+/** Return shape from synthesizeReport */
+export interface SynthesisResult {
+	report: string;
+	references: Reference[];
+}
+
+/**
+ * Maximum findings included in the synthesis prompt.
+ * Keeps token usage bounded and forces the synthesizer to focus on
+ * the highest-quality evidence.
+ */
+const MAX_SYNTHESIS_FINDINGS = 30;
+
+/**
+ * Rank a finding for inclusion in synthesis: authority-weighted,
+ * confidence-weighted, with a corroboration bonus.
+ */
+function findingQualityScore(f: Finding): number {
+	const authority =
+		(f.bestSourceAuthority ?? f.avgSourceAuthority ?? 0.5) || 0.5;
+	const confidenceWeight =
+		f.confidence === "high" ? 1.0 : f.confidence === "medium" ? 0.7 : 0.45;
+	const corroborationBonus = (f.corroborationScore ?? 0) * 0.3;
+	return authority * confidenceWeight + corroborationBonus;
+}
+
+/* ── System Prompts ──────────────────────────────────────────────── */
+
+function buildSynthesisSystem(audience: string): string {
+	const audienceGuidance: Record<string, string> = {
+		expert:
+			"Assume expert-level domain knowledge. Use precise technical terminology, reference specific methodologies and standards, and prioritize depth over hand-holding. The reader understands the field.",
+		general:
+			"Write for an informed general audience. Define technical terms on first use, explain context, and keep the tone accessible but not simplistic. Avoid jargon without explanation.",
+		executive:
+			"Write for a busy executive or decision-maker. Lead with actionable conclusions and recommendations. Be concise — use bold for key takeaways. Minimize technical detail; focus on implications, trade-offs, and decisions. Target 2-3 pages.",
+	};
+
+	const guidance = audienceGuidance[audience] ?? audienceGuidance.general;
+
+	return `You are a senior research analyst synthesizing findings from multiple web searches into a comprehensive, well-structured report.
+
+Audience: ${guidance}
+
+Report structure (use ## headings):
+1. **TL;DR** — One paragraph (2-3 sentences) giving the single most important answer
+2. **Executive Summary** — 2-3 paragraphs covering what was found, how confident we are, and key implications
+3. **Key Findings** — Tiered by importance/confidence. Bullet points with inline citations
+4. **Detailed Analysis** — Organized by theme. Each section covers one aspect with evidence
+5. **Limitations & Knowledge Gaps** — What evidence is weak, missing, or contradictory
+6. **Conclusion** — Wrap up with actionable takeaways
+
+Citation rules:
+- Use numbered references like [1], [2] etc. throughout the text
+- At the end, include a ## References section listing each citation
+- Format references as: [1] Title — Domain (URL)
+- Cite specific evidence, not vague associations
+- When multiple sources support a claim, cite all of them: [1][3][5]
+
+Style guidelines:
+- Write in an objective, authoritative tone
+- Use bullet points for listing evidence
+- Note the confidence level for key claims
+- Be thorough but concise — every paragraph should add value
+- Use > for notable direct quotes with citations`;
+}
+
+/* ── Evidence Builder ────────────────────────────────────────────── */
+
+function buildEvidenceText(
+	question: string,
+	rounds: ResearchRound[],
+): { evidenceText: string; referenceMap: Map<string, Reference> } {
+	const allFindings = rounds.flatMap((r) => r.findings);
+	const totalSearches = rounds.reduce((sum, r) => sum + r.queries.length, 0);
+	const totalPages = rounds.reduce((sum, r) => sum + r.results.length, 0);
+
+	// Build a bibliography map (url -> Reference)
+	const seenUrls = new Map<string, Reference>();
+	let refId = 0;
+
+	for (const round of rounds) {
+		for (const result of round.results) {
+			if (!seenUrls.has(result.url)) {
+				refId++;
+				seenUrls.set(result.url, {
+					id: refId,
+					url: result.url,
+					title: result.title,
+					domain: result.domain,
+					authorityScore: result.authorityScore,
+					accessedAt: new Date().toISOString().split("T")[0],
+				});
+			}
+		}
+	}
+
+	// ── Deduplicate findings across rounds ────────────────────────────
+	// The same claim often surfaces in multiple rounds under slightly
+	// different titles. Merge them (union of sources/quotes, keep the
+	// highest-quality version) so the synthesizer isn't double-counting.
+	const deduped: Finding[] = [];
+	for (const finding of allFindings) {
+		const dupIndex = deduped.findIndex(
+			(f) =>
+				f.title !== finding.title &&
+				isNearDuplicateTitle(f.title, finding.title),
+		);
+		if (dupIndex === -1) {
+			deduped.push({ ...finding });
+		} else {
+			const existing = deduped[dupIndex];
+			deduped[dupIndex] = {
+				title: existing.title,
+				summary: existing.summary,
+				sources: Array.from(new Set([...existing.sources, ...finding.sources])),
+				keyQuotes: Array.from(
+					new Set([...existing.keyQuotes, ...finding.keyQuotes]),
+				).slice(0, 3),
+				confidence:
+					existing.confidence === "high" || finding.confidence === "high"
+						? "high"
+						: existing.confidence === "medium" ||
+								finding.confidence === "medium"
+							? "medium"
+							: "low",
+				query: existing.query ?? finding.query,
+				angle: existing.angle ?? finding.angle,
+			};
+		}
+	}
+
+	// ── Rank and cap findings for synthesis ───────────────────────────
+	const ranked = deduped
+		.map((f) => ({ f, score: findingQualityScore(f) }))
+		.sort((a, b) => b.score - a.score)
+		.slice(0, MAX_SYNTHESIS_FINDINGS)
+		.map(({ f }) => f);
+
+	// Organize findings by their own angle (provenance-aware)
+	const evidenceByAngle = new Map<string, Finding[]>();
+	for (const finding of ranked) {
+		const angle = finding.angle ?? "general";
+		if (!evidenceByAngle.has(angle)) evidenceByAngle.set(angle, []);
+		evidenceByAngle.get(angle)!.push(finding);
+	}
+
+	let evidenceText = `## Research Question\n${question}\n\n`;
+	evidenceText += `## Overview\n- Rounds of research: ${rounds.length}\n`;
+	evidenceText += `- Total searches executed: ${totalSearches}\n`;
+	evidenceText += `- Total pages analyzed: ${totalPages}\n`;
+	evidenceText += `- Key findings extracted: ${allFindings.length} (${ranked.length} passed dedup/quality filter)\n\n`;
+
+	// Build evidence grouped by angle with reference IDs
+	for (const [angle, findings] of Array.from(evidenceByAngle)) {
+		if (findings.length === 0) continue;
+		evidenceText += `## Angle: ${angle}\n\n`;
+		for (const finding of findings) {
+			// Get reference IDs for this finding's sources
+			const refs = finding.sources
+				.map((url) => seenUrls.get(url))
+				.filter((r): r is Reference => !!r)
+				.map((r) => `[${r.id}]`);
+
+			const avgAuth =
+				finding.avgSourceAuthority !== undefined
+					? ` | Avg Authority: ${(finding.avgSourceAuthority * 100).toFixed(0)}%`
+					: "";
+			const corr =
+				finding.corroborationScore !== undefined
+					? ` | Corroboration: ${(finding.corroborationScore * 100).toFixed(0)}%`
+					: "";
+			const bestAuthStr =
+				finding.bestSourceAuthority !== undefined
+					? ` | Best Source: ${(finding.bestSourceAuthority * 100).toFixed(0)}%`
+					: "";
+
+			evidenceText += `### ${finding.title}\n`;
+			evidenceText += `**Confidence:** ${finding.confidence}${avgAuth}${corr}${bestAuthStr}\n`;
+			if (refs.length > 0) {
+				evidenceText += `**Sources:** ${refs.join(", ")}\n`;
+			}
+			evidenceText += `${finding.summary}\n\n`;
+			if (finding.keyQuotes.length > 0) {
+				evidenceText += `> ${finding.keyQuotes[0]}\n\n`;
+			}
+		}
+	}
+
+	// Include reference metadata for the LLM to build proper citations
+	evidenceText += `## Reference Metadata\n\n`;
+	for (const [, ref] of seenUrls) {
+		evidenceText += `[${ref.id}] ${ref.title} (${ref.domain}, authority: ${(ref.authorityScore * 100).toFixed(0)}%) — ${ref.url}\n`;
+	}
+
+	return { evidenceText, referenceMap: seenUrls };
+}
+
+/* ── Main Synthesis ──────────────────────────────────────────────── */
+
+/**
+ * Synthesize a research report from all rounds.
+ * Returns both the formatted report and the full bibliography.
+ */
+export async function synthesizeReport(
+	question: string,
+	rounds: ResearchRound[],
+	config: ResearchConfig,
+	cwd: string,
+	signal?: AbortSignal,
+): Promise<SynthesisResult> {
+	const audience = config.audience ?? "general";
+	const { evidenceText, referenceMap } = buildEvidenceText(question, rounds);
+
+	const formatInstruction =
+		config.format === "structured"
+			? "Structured report with numbered sections, clear hierarchies, and data tables where appropriate."
+			: "Well-formatted markdown report with ## headings, bullet points, and inline numbered citations like [1].";
+
+	const taskPrompt = `Synthesize the following research findings into a comprehensive, well-structured report.
+
+${evidenceText}
+
+Write a thorough report that answers the original question: "${question}"
+
+Format: ${formatInstruction}
+Audience: ${audience}
+
+Remember to use numbered citations like [1], [2] and include a ## References section at the end.`;
+
+	const result = await runAnalysisAgent(
+		buildSynthesisSystem(audience),
+		taskPrompt,
+		cwd,
+		120_000,
+		undefined,
+		signal,
+	);
+
+	if (result.success && result.text) {
+		// Build bibliography section
+		const bibSection = buildBibliography(referenceMap);
+
+		let report = result.text;
+
+		// ── Citation integrity ─────────────────────────────────────────
+		// 1. Strip any references section the LLM wrote and replace it with
+		//    the authoritative bibliography (built from real scraped sources).
+		// 2. Remove inline [n] citations that point at IDs outside the
+		//    bibliography (hallucinated numbers), so every citation resolves.
+		report = report.replace(
+			/^#+\s*references\s*$/gim,
+			"\n## END_OF_REPORT_MARKER",
+		);
+		const markerIdx = report.indexOf("## END_OF_REPORT_MARKER");
+		if (markerIdx !== -1) {
+			report = report.slice(0, markerIdx).trimEnd();
+		}
+
+		const maxRefId = Math.max(
+			0,
+			...Array.from(referenceMap.values()).map((r) => r.id),
+		);
+		report = report.replace(/\[(\d+)\]/g, (match, id: string) => {
+			const num = parseInt(id, 10);
+			return num >= 1 && num <= maxRefId ? match : "";
+		});
+
+		report = report.trimEnd() + `\n\n${bibSection}`;
+
+		return { report, references: Array.from(referenceMap.values()) };
+	}
+
+	// Fallback: generate a simple structured report
+	const fallbackReport = generateFallbackReport(
+		question,
+		rounds,
+		referenceMap,
+		audience,
+	);
+	return {
+		report: fallbackReport + `\n\n${buildBibliography(referenceMap)}`,
+		references: Array.from(referenceMap.values()),
+	};
+}
+
+/* ── Bibliography Builder ────────────────────────────────────────── */
+
+/**
+ * Build a structured ## References section from the reference map.
+ */
+function buildBibliography(referenceMap: Map<string, Reference>): string {
+	if (referenceMap.size === 0) return "## References\n\nNo sources cited.";
+
+	const refs = Array.from(referenceMap.values()).sort((a, b) => a.id - b.id);
+	const lines: string[] = ["## References\n"];
+	for (const ref of refs) {
+		const authIcon =
+			ref.authorityScore >= 0.8 ? "⭐" : ref.authorityScore >= 0.5 ? "✓" : "○";
+		lines.push(
+			`[${ref.id}] ${authIcon} **${ref.title}** — ${ref.domain} (${ref.url}) — accessed ${ref.accessedAt}`,
+		);
+	}
+
+	return lines.join("\n");
+}
+
+/* ── Fallback Report ─────────────────────────────────────────────── */
+
+/**
+ * Fallback report when the LLM synthesis fails.
+ * Produces a clean, structured report from the evidence.
+ */
+function generateFallbackReport(
+	question: string,
+	rounds: ResearchRound[],
+	referenceMap: Map<string, Reference>,
+	_audience: string,
+): string {
+	const lines: string[] = [];
+	const allFindings = rounds.flatMap((r) => r.findings);
+
+	// ── TL;DR ──
+	lines.push(`# Research Report: ${question}`);
+	lines.push("");
+
+	const highConfFindings = allFindings.filter((f) => f.confidence === "high");
+	const totalHigh = highConfFindings.length;
+	const total = allFindings.length;
+
+	lines.push("## TL;DR");
+	lines.push("");
+	if (highConfFindings.length > 0) {
+		lines.push(
+			`Based on analysis of ${total} findings across ${rounds.length} research round(s), ` +
+				`${totalHigh} high-confidence conclusions were identified. ` +
+				`${highConfFindings[0].title}: ${highConfFindings[0].summary}`,
+		);
+	} else {
+		lines.push(
+			`This report covers findings from ${rounds.length} research round(s) exploring "${question}". ` +
+				`${total} findings were extracted, with varying levels of confidence.`,
+		);
+	}
+	lines.push("");
+
+	// ── Executive Summary ──
+	lines.push("## Executive Summary");
+	lines.push("");
+	lines.push(
+		`This report synthesizes findings from ${rounds.length} research round(s), ` +
+			`${rounds.reduce((s, r) => s + r.queries.length, 0)} search queries, ` +
+			`and ${rounds.reduce((s, r) => s + r.results.length, 0)} sources.`,
+	);
+	lines.push("");
+
+	// ── Key Findings (tiered) ──
+	if (allFindings.length > 0) {
+		lines.push("## Key Findings");
+		lines.push("");
+
+		// High confidence first
+		const highConf = allFindings.filter((f) => f.confidence === "high");
+		if (highConf.length > 0) {
+			lines.push("### High Confidence");
+			for (const finding of highConf) {
+				const refs = finding.sources
+					.map((url) => referenceMap.get(url))
+					.filter((r): r is Reference => !!r)
+					.map((r) => `[${r.id}]`);
+				lines.push(
+					`- **${finding.title}** ${refs.length > 0 ? refs.join("") : ""}`,
+				);
+				lines.push(`  - ${finding.summary}`);
+			}
+			lines.push("");
+		}
+
+		// Medium confidence
+		const medConf = allFindings.filter((f) => f.confidence === "medium");
+		if (medConf.length > 0) {
+			lines.push("### Moderate Confidence");
+			for (const finding of medConf) {
+				const refs = finding.sources
+					.map((url) => referenceMap.get(url))
+					.filter((r): r is Reference => !!r)
+					.map((r) => `[${r.id}]`);
+				lines.push(
+					`- **${finding.title}** ${refs.length > 0 ? refs.join("") : ""}`,
+				);
+				lines.push(`  - ${finding.summary}`);
+			}
+			lines.push("");
+		}
+
+		// Low confidence
+		const lowConf = allFindings.filter((f) => f.confidence === "low");
+		if (lowConf.length > 0) {
+			lines.push("### Lower Confidence (Needs Further Research)");
+			for (const finding of lowConf) {
+				const refs = finding.sources
+					.map((url) => referenceMap.get(url))
+					.filter((r): r is Reference => !!r)
+					.map((r) => `[${r.id}]`);
+				lines.push(
+					`- **${finding.title}** ${refs.length > 0 ? refs.join("") : ""}`,
+				);
+				lines.push(`  - ${finding.summary}`);
+			}
+			lines.push("");
+		}
+
+		// ── Detailed Analysis ──
+		lines.push("## Detailed Analysis");
+		lines.push("");
+
+		const byAngle = new Map<string, Finding[]>();
+		for (const round of rounds) {
+			for (const f of round.findings) {
+				const angle = f.angle ?? round.queries[0]?.angle ?? "general";
+				if (!byAngle.has(angle)) byAngle.set(angle, []);
+				byAngle.get(angle)!.push(f);
+			}
+		}
+
+		for (const [angle, findings] of byAngle) {
+			lines.push(`### ${angle.charAt(0).toUpperCase() + angle.slice(1)}`);
+			lines.push("");
+			for (const f of findings) {
+				const corrStr =
+					f.corroborationScore !== undefined
+						? ` (corroboration: ${(f.corroborationScore * 100).toFixed(0)}%)`
+						: "";
+				lines.push(`**${f.title}** — *${f.confidence} confidence${corrStr}*`);
+				lines.push("");
+				lines.push(f.summary);
+				lines.push("");
+				if (f.keyQuotes.length > 0) {
+					lines.push(`> ${f.keyQuotes[0]}`);
+					lines.push("");
+				}
+			}
+		}
+
+		// ── Limitations ──
+		const lowConfCount = allFindings.filter(
+			(f) => f.confidence === "low",
+		).length;
+		const noCorr = allFindings.filter(
+			(f) => (f.corroborationScore ?? 0) < 0.3,
+		).length;
+
+		lines.push("## Limitations & Knowledge Gaps");
+		lines.push("");
+		if (lowConfCount > 0) {
+			lines.push(
+				`- **${lowConfCount} of ${allFindings.length} findings** have low confidence, indicating limited or conflicting evidence.`,
+			);
+		}
+		if (noCorr > 0) {
+			lines.push(
+				`- **${noCorr} findings** lack corroboration from multiple independent sources.`,
+			);
+		}
+		lines.push(
+			"- This research relied on web search results; some relevant sources may not be indexed or accessible.",
+		);
+		lines.push(
+			"- Findings are dependent on search engine ranking and the quality of indexed content.",
+		);
+		lines.push("");
+
+		// ── Conclusion ──
+		lines.push("## Conclusion");
+		lines.push("");
+		if (highConf.length > 0) {
+			lines.push(
+				`The research identified ${highConf.length} high-confidence finding(s) and ${medConf.length} moderately-supported finding(s). ` +
+					`The strongest evidence relates to: ${highConf.map((f) => f.title).join(", ")}.`,
+			);
+		} else {
+			lines.push(
+				"The research surfaced relevant information but with limited high-confidence evidence. Further investigation is recommended for the identified knowledge gaps.",
+			);
+		}
+		lines.push("");
+	}
+
+	// ── Methodology ──
+	lines.push(`*Report prepared for: ${_audience} audience*`);
+	lines.push("");
+
+	lines.push("## Methodology");
+	lines.push("");
+	for (const round of rounds) {
+		const failedSearches =
+			round.failedSearches ?? round.queries.length - round.successfulSearches;
+		lines.push(`### Round ${round.round}`);
+		lines.push(
+			`Queries: ${round.queries.map((q) => `"${q.query}" [${q.angle}]`).join(", ")}`,
+		);
+		lines.push(`Pages scraped: ${round.results.length}`);
+		lines.push(`Findings extracted: ${round.findings.length}`);
+		if (failedSearches > 0) {
+			lines.push(`Searches failed: ${failedSearches}`);
+		}
+		lines.push("");
+	}
+
+	return lines.join("\n");
+}
--- a/src/research.ts
+++ b/src/research.ts
@@ -0,0 +1,468 @@
+/**
+ * Deep Research — Core research orchestration
+ *
+ * Manages the multi-round deep research process:
+ * 1. Decompose the question into sub-questions (when depth > 1)
+ * 2. Generate initial search queries (per sub-question for better diversity)
+ * 3. Execute all queries in parallel via Firecrawl
+ * 4. Analyze results and extract findings
+ * 5. Compute corroboration scores
+ * 6. Generate follow-up queries for gaps
+ * 7. Iterate for depth rounds
+ * 8. Synthesize final report with numbered references
+ *
+ * Widget and progress callback patterns borrowed from ralpi's executor.
+ */
+import type { ExtensionContext } from "@oh-my-pi/pi-coding-agent";
+import type {
+	Finding,
+	ResearchConfig,
+	EnrichedSearchResult,
+	ResearchRound,
+	ResearchReport,
+} from "./types";
+import type { SynthesisResult } from "./report";
+import { searchWeb, isNearDuplicateTitle } from "./firecrawl";
+import {
+	generateQueries,
+	generateFollowUpQueries,
+	analyzeResults,
+	computeCorroboration,
+	decomposeQuestion,
+} from "./queries";
+import { synthesizeReport } from "./report";
+
+/** Progress callback for UI updates */
+export type ResearchProgress = (update: {
+	phase:
+		| "decomposing"
+		| "generating_queries"
+		| "searching"
+		| "analyzing"
+		| "synthesizing"
+		| "complete";
+	round?: number;
+	totalRounds?: number;
+	message: string;
+	detail?: string;
+	fraction?: number; // 0-1
+}) => void;
+
+// ── Round-Robin Parallel Execution ──────────────────────────────────
+
+/**
+ * Maximum concurrent Firecrawl search requests.
+ * Prevents rate limiting while still parallelizing queries.
+ */
+const MAX_SEARCH_CONCURRENT = 3;
+
+/**
+ * Maximum concurrent analysis agent sessions.
+ */
+const MAX_ANALYSIS_CONCURRENT = 2;
+
+/**
+ * Minimum findings per round before we consider early stopping.
+ * If we're getting very few new findings, saturation is near.
+ */
+const SATURATION_THRESHOLD = 0.15; // < 15% new findings = likely saturated
+
+/**
+ * Bounded-concurrency parallel execution with round-robin slot assignment.
+ *
+ * Similar to ralpi's ModelRoundRobin: with N concurrent slots, items are
+ * assigned to free slots in FIFO order. When a slot finishes, the next
+ * item in the queue is assigned to it.
+ *
+ * This ensures even load distribution and avoids bursty concurrency.
+ */
+async function boundedConcurrency<T, R>(
+	items: T[],
+	maxConcurrent: number,
+	mapper: (item: T, index: number) => Promise<R>,
+): Promise<R[]> {
+	const results: R[] = new Array(items.length);
+	let nextIndex = 0;
+
+	async function worker(): Promise<void> {
+		while (true) {
+			const currentIndex = nextIndex++;
+			if (currentIndex >= items.length) return;
+			results[currentIndex] = await mapper(items[currentIndex], currentIndex);
+		}
+	}
+
+	const numWorkers = Math.min(maxConcurrent, items.length);
+	const workers = Array.from({ length: numWorkers }, () => worker());
+	await Promise.all(workers);
+	return results;
+}
+
+/**
+ * Assess whether the research is reaching information saturation.
+ */
+function assessSaturation(
+	previousRound: ResearchRound | undefined,
+	currentRound: ResearchRound,
+): number {
+	if (!previousRound || previousRound.findings.length === 0) return 0;
+
+	const prevUrls = new Set(previousRound.results.map((r) => r.url));
+	const newUrls = currentRound.results.filter(
+		(r) => !prevUrls.has(r.url),
+	).length;
+	const totalUrls = currentRound.results.length;
+	const newRatio = totalUrls > 0 ? newUrls / totalUrls : 0;
+
+	// Also check finding novelty
+	const prevFindingTitles = new Set(
+		previousRound.findings.map((f) => f.title.toLowerCase()),
+	);
+	const newFindings = currentRound.findings.filter(
+		(f) => !prevFindingTitles.has(f.title.toLowerCase()),
+	).length;
+	const totalFindings = currentRound.findings.length;
+	const findingNovelty = totalFindings > 0 ? newFindings / totalFindings : 0;
+
+	// Weight: URL novelty (40%) + finding novelty (60%)
+	return newRatio * 0.4 + findingNovelty * 0.6;
+}
+
+/**
+ * Run a complete deep research session.
+ */
+export async function runDeepResearch(
+	config: ResearchConfig,
+	ctx: ExtensionContext,
+	onProgress: ResearchProgress,
+	signal?: AbortSignal,
+): Promise<ResearchReport> {
+	const startTime = Date.now();
+	const rounds: ResearchRound[] = [];
+	let totalSearches = 0;
+	let totalPages = 0;
+	let subQuestions: string[] = [];
+
+	// ── Phase: Decompose question into sub-questions ────────────────
+
+	if (config.depth > 1) {
+		onProgress({
+			phase: "decomposing",
+			round: 1,
+			totalRounds: config.depth,
+			message: "Decomposing research question into sub-topics...",
+			fraction: 0,
+		});
+
+		if (signal?.aborted) throw new Error("Research cancelled");
+
+		subQuestions = await decomposeQuestion(config.question, ctx.cwd, signal);
+	}
+
+	// ── Phase: Generate initial queries ─────────────────────────────
+
+	onProgress({
+		phase: "generating_queries",
+		round: 1,
+		totalRounds: config.depth,
+		message:
+			subQuestions.length > 0
+				? `Generating queries across ${subQuestions.length} sub-topics...`
+				: "Generating initial search queries...",
+		fraction: 0.05,
+	});
+
+	if (signal?.aborted) throw new Error("Research cancelled");
+
+	const queries = await generateQueries(
+		config.question,
+		config.breadth,
+		ctx.cwd,
+		signal,
+		subQuestions.length > 0 ? subQuestions : undefined,
+	);
+
+	if (queries.length === 0) {
+		throw new Error("Failed to generate any search queries");
+	}
+
+	// ── Execute rounds ───────────────────────────────────────────────
+
+	for (let round = 1; round <= config.depth; round++) {
+		if (signal?.aborted) throw new Error("Research cancelled");
+
+		const isFirstRound = round === 1;
+		const currentQueries = isFirstRound
+			? queries
+			: await generateFollowUpQueries(
+					config.question,
+					rounds,
+					config.breadth,
+					ctx.cwd,
+					signal,
+				);
+
+		if (!currentQueries || currentQueries.length === 0) {
+			// No follow-up queries to generate — stop here
+			break;
+		}
+
+		// ── Search phase (parallel with round-robin) ────────────────────
+
+		onProgress({
+			phase: "searching",
+			round,
+			totalRounds: config.depth,
+			message: `Searching ${currentQueries.length} queries in parallel...`,
+			fraction: 0.25,
+		});
+
+		if (signal?.aborted) throw new Error("Research cancelled");
+
+		// Run searches in parallel using round-robin bounded concurrency.
+		// Each mapper call runs independently; failures are caught per-query.
+		// Results keep their originating query index for later grouping.
+		const searchResultsArrays: (EnrichedSearchResult[] | null)[] =
+			await boundedConcurrency(
+				currentQueries,
+				MAX_SEARCH_CONCURRENT,
+				async (q, i) => {
+					onProgress({
+						phase: "searching",
+						round,
+						totalRounds: config.depth,
+						message: `Searching: "${q.query.slice(0, 60)}..."`,
+						detail: q.rationale,
+						fraction: 0.25 + (i / currentQueries.length) * 0.25,
+					});
+
+					try {
+						return await searchWeb(q.query, 5, signal);
+					} catch (error) {
+						const errorMsg =
+							error instanceof Error ? error.message : String(error);
+						onProgress({
+							phase: "searching",
+							round,
+							totalRounds: config.depth,
+							message: `Search failed: ${errorMsg.slice(0, 80)}`,
+							fraction: 0.25 + ((i + 1) / currentQueries.length) * 0.25,
+						});
+						return null;
+					}
+				},
+			);
+
+		const successfulSearches = searchResultsArrays.filter(
+			(r): r is EnrichedSearchResult[] => r !== null,
+		).length;
+		const failedSearches = currentQueries.length - successfulSearches;
+
+		totalSearches += currentQueries.length;
+
+		// Track which URLs were independently surfaced by MULTIPLE different
+		// queries. This is the corroboration signal: a source found by
+		// several independent searches is stronger evidence than one found
+		// by a single query.
+		const urlQueryCounts = new Map<string, number>();
+		searchResultsArrays.forEach((results, queryIndex) => {
+			if (!results) return;
+			const queryUrls = new Set(results.map((r) => r.url));
+			for (const url of queryUrls) {
+				urlQueryCounts.set(url, (urlQueryCounts.get(url) ?? 0) + 1);
+			}
+			// (queryIndex is unused beyond the closure; kept for clarity)
+			void queryIndex;
+		});
+
+		// ── Per-query result collection ──────────────────────────────────
+		// Deduplicate within each query's results by URL (prefer higher
+		// authority) AND by near-identical title (catches syndicated copies
+		// of the same article under different URLs).
+		const resultsByQuery: EnrichedSearchResult[][] = currentQueries.map(
+			() => [],
+		);
+
+		searchResultsArrays.forEach((results, queryIndex) => {
+			if (!results) return;
+			const seenUrls = new Set<string>();
+			const seenTitles: string[] = [];
+			for (const r of results) {
+				if (seenUrls.has(r.url)) continue;
+				seenUrls.add(r.url);
+
+				// Skip syndicated duplicates (same article, different URL)
+				if (
+					r.title &&
+					seenTitles.some((t) => isNearDuplicateTitle(t, r.title))
+				) {
+					continue;
+				}
+				if (r.title) seenTitles.push(r.title);
+				resultsByQuery[queryIndex].push(r);
+			}
+		});
+
+		// Global URL dedup across queries: a URL found by multiple queries
+		// stays attached to the FIRST query that surfaced it (most likely
+		// the most relevant one).
+		const globalSeen = new Set<string>();
+		for (const list of resultsByQuery) {
+			for (let i = list.length - 1; i >= 0; i--) {
+				if (globalSeen.has(list[i].url)) {
+					list.splice(i, 1);
+				} else {
+					globalSeen.add(list[i].url);
+				}
+			}
+		}
+
+		const uniqueResults = resultsByQuery.flat();
+		totalPages += uniqueResults.length;
+
+		// ── Analyze phase (parallel with round-robin) ──────────────────
+
+		onProgress({
+			phase: "analyzing",
+			round,
+			totalRounds: config.depth,
+			message: `Analyzing ${uniqueResults.length} search results in parallel...`,
+			fraction: 0.6,
+		});
+
+		if (signal?.aborted) throw new Error("Research cancelled");
+
+		// Build query-result pairs for parallel analysis.
+		// Each query is analyzed with the results IT actually produced,
+		// so findings stay coherent with the query's intent and angle.
+		const analysisTasks: Array<{
+			query: (typeof currentQueries)[number];
+			results: EnrichedSearchResult[];
+			index: number;
+		}> = [];
+
+		for (let i = 0; i < currentQueries.length; i++) {
+			const queryResults = resultsByQuery[i];
+			if (!queryResults || queryResults.length === 0) continue;
+
+			analysisTasks.push({
+				query: currentQueries[i],
+				results: queryResults,
+				index: i,
+			});
+		}
+
+		// Run analyses in parallel using round-robin bounded concurrency
+		const findingsArrays: Finding[][] = await boundedConcurrency(
+			analysisTasks,
+			MAX_ANALYSIS_CONCURRENT,
+			async (task) => {
+				onProgress({
+					phase: "analyzing",
+					round,
+					totalRounds: config.depth,
+					message: `Analyzing: "${task.query.query.slice(0, 40)}..."`,
+					fraction:
+						0.6 + (task.index / Math.max(analysisTasks.length, 1)) * 0.2,
+				});
+
+				try {
+					return await analyzeResults(
+						task.query.query,
+						task.results,
+						ctx.cwd,
+						signal,
+						task.query.angle,
+					);
+				} catch {
+					// Analysis failure shouldn't crash the round
+					return [];
+				}
+			},
+		);
+
+		// Flatten all findings
+		const allFindings: ResearchRound["findings"] = findingsArrays.flat();
+
+		// ── Corroboration pass ────────────────────────────────────────
+		// Cross-reference findings to compute corroboration scores.
+		// Corroboration = fraction of a finding's sources that were
+		// independently surfaced by multiple different search queries.
+		const corroboratedFindings = computeCorroboration(
+			allFindings,
+			urlQueryCounts,
+		);
+
+		// Record this round
+		const followUpTopics = corroboratedFindings
+			.filter(
+				(f: Finding) =>
+					f.confidence === "low" && (f.corroborationScore ?? 0) < 0.5,
+			)
+			.map((f: Finding) => f.title);
+
+		rounds.push({
+			round,
+			queries: currentQueries,
+			results: uniqueResults,
+			findings: corroboratedFindings,
+			followUpTopics,
+			successfulSearches,
+			failedSearches,
+		});
+
+		// ── Adaptive depth: check for saturation ──────────────────────
+		if (round > 1 && round < config.depth) {
+			const saturation = assessSaturation(
+				rounds[rounds.length - 2],
+				rounds[rounds.length - 1],
+			);
+			if (saturation < SATURATION_THRESHOLD) {
+				onProgress({
+					phase: "synthesizing",
+					message: `Information saturation reached (${(saturation * 100).toFixed(0)}% novelty) — synthesizing early`,
+					fraction: 0.85,
+				});
+				break;
+			}
+		}
+	}
+
+	// ── Synthesis phase ───────────────────────────────────────────────
+
+	onProgress({
+		phase: "synthesizing",
+		message: "Synthesizing research into final report...",
+		fraction: 0.9,
+	});
+
+	if (signal?.aborted) throw new Error("Research cancelled");
+
+	const synthesisResult: SynthesisResult = await synthesizeReport(
+		config.question,
+		rounds,
+		config,
+		ctx.cwd,
+		signal,
+	);
+	const finalReport = synthesisResult.report;
+	const references = synthesisResult.references;
+
+	const durationMs = Date.now() - startTime;
+
+	onProgress({
+		phase: "complete",
+		message: "Research complete!",
+		fraction: 1.0,
+	});
+
+	return {
+		question: config.question,
+		rounds,
+		finalReport,
+		totalSearches,
+		totalPagesScraped: totalPages,
+		durationMs,
+		references,
+	};
+}
--- a/src/types.ts
+++ b/src/types.ts
@@ -0,0 +1,106 @@
+/**
+ * Deep Research — type definitions
+ */
+
+/** Content type classification for a source */
+export type ContentType =
+	| "documentation"
+	| "paper"
+	| "news"
+	| "blog"
+	| "forum"
+	| "official"
+	| "other";
+
+/** A single search result from Firecrawl */
+export interface SearchResult {
+	title: string;
+	url: string;
+	description: string;
+	markdown: string;
+}
+
+/** Enriched search result with source authority metadata */
+export interface EnrichedSearchResult extends SearchResult {
+	domain: string;
+	authorityScore: number; // 0.0 – 1.0
+	publishedDate: Date | null;
+	contentType: ContentType;
+}
+
+/** A finding extracted from search results by an analysis agent */
+export interface Finding {
+	title: string;
+	summary: string;
+	sources: string[];
+	keyQuotes: string[];
+	confidence: "high" | "medium" | "low";
+	/** The search query this finding was extracted under (provenance) */
+	query?: string;
+	/** The research angle of the originating query (provenance) */
+	angle?: string;
+	/** 0.0 – 1.0: how many independent sources support this finding */
+	corroborationScore?: number;
+	/** Authority score of the best source supporting this finding */
+	bestSourceAuthority?: number;
+	/** Average authority score across all sources */
+	avgSourceAuthority?: number;
+}
+
+/** A numbered reference with full metadata */
+export interface Reference {
+	id: number;
+	url: string;
+	title: string;
+	domain: string;
+	authorityScore: number;
+	accessedAt: string; // ISO date string
+}
+
+/** A generated search query with its intent/rationale */
+export interface SearchQuery {
+	query: string;
+	rationale: string;
+	angle: string;
+}
+
+/** Output from one research round */
+export interface ResearchRound {
+	round: number;
+	queries: SearchQuery[];
+	results: EnrichedSearchResult[];
+	findings: Finding[];
+	/** Any follow-up questions/angles the analysis suggests */
+	followUpTopics: string[];
+	/** Number of search queries that actually returned data (non-empty) */
+	successfulSearches: number;
+	/** Number of search queries that failed entirely */
+	failedSearches: number;
+}
+
+/** Target audience expertise level */
+export type Audience = "expert" | "general" | "executive";
+
+/** Configuration for a research session */
+export interface ResearchConfig {
+	question: string;
+	depth: number; // 1-3 rounds
+	breadth: number; // queries per round (1-5)
+	format: "markdown" | "structured";
+	audience?: Audience;
+	/** Focus on specific research angles only (empty = all angles) */
+	focus?: string[];
+	/** Show the research methodology section in the report */
+	showMethodology?: boolean;
+}
+
+/** Final research report */
+export interface ResearchReport {
+	question: string;
+	rounds: ResearchRound[];
+	finalReport: string;
+	totalSearches: number;
+	totalPagesScraped: number;
+	durationMs: number;
+	references: Reference[];
+}
--- a/tsconfig.json
+++ b/tsconfig.json
@@ -0,0 +1,16 @@
+{
+  "compilerOptions": {
+    "target": "ES2022",
+    "module": "ES2022",
+    "moduleResolution": "node",
+    "lib": ["ES2022"],
+    "noEmit": true,
+    "strict": true,
+    "esModuleInterop": true,
+    "skipLibCheck": true,
+    "forceConsistentCasingInFileNames": true,
+    "resolveJsonModule": true
+  },
+  "include": ["index.ts", "src/**/*"],
+  "exclude": ["node_modules", "dist"]
+}