- Cap commit diffs in review/commit prompts at 50KB to prevent context window overflow on follow-up sessions - Skip skills catalog (noSkills) in commit/review follow-up sessions for leaner context - Wire Pi's SettingsManager into runAgentSession so Pi's built-in retry (exponential backoff, provider retry) applies to ralpi sessions — removes ralpi's duplicate manual retry loop - Remove maxRetries/retryDelayMs from ralpi config; rely on Pi's retry.* settings (with manual override support) - Remove retries field from progress.json and incrementRetry() from ProgressTracker - Add model failover to follow-up sessions (commit/review cycle through the model pool on connection errors) - Namespace reflection files by PRD key under .ralpi/reflections/<prdKey>/ so task sets don't overwrite each other - Skip loop-startup prompts for config fields explicitly set in YAML - Remove (default) annotations from loop options prompts - Default commitTimeoutMs/reviewTimeoutMs to 0 (inherit Pi defaults)
166 lines
5.5 KiB
Markdown
166 lines
5.5 KiB
Markdown
# Ralpi
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Execute tasks from task files until done using DAG-based dependency resolution with persistent progress tracking.
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```bash
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pi install npm:@mikefreno/ralpi
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```
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## Features
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- **Parallel batching**: Independent tasks in each batch can run concurrently
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- **Persistent progress**: Execution state saved to `.ralpi/progress.json`
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- **Reflection system**: Each task produces a reflection for downstream tasks
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- **Retry with backoff**: Failed tasks retry with exponential backoff
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- **Multiple formats**: Supports simple checkboxes, and YAML
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- **Tool usage tracking**: Detects and reports tool usage (read, write, edit, bash) from task execution
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- **Configurable timeouts**: Task-level timeouts via meta blocks, with global fallback
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- **Session saving**: Saves full task output for expandable session review
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- **Resume auto-discovery**: Automatically finds and resumes interrupted execution
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## Usage
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```
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/ralpi [task-file] # Execute all tasks
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/ralpi plan # Alias to /task-manager to plan new tasks
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/ralpi resume # Resume paused execution
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/ralpi reset # Reset progress and .ralpi directory - does not modify PRD
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```
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### Highly recommended to use the task-manager prompt for prd construction, it's output pairs perfectly - /task-manager or /ralpi plan
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## Tasks
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### Simple Checkbox Format
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```markdown
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- [ ] 01: Setup project structure
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- [ ] 02: Implement auth
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- [ ] 03: Build API
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```
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### YAML Format
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```yaml
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objective: Build a web application
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tasks:
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- id: "01"
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title: Setup project structure
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file: tasks/01-setup.md
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dependencies: []
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- id: "02"
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title: Implement auth
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file: tasks/02-auth.md
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depends_on: ["01"]
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```
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## Task IDs
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Task IDs are zero-padded 2-digit strings (`01`, `02`, ...) with an optional
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single lowercase letter suffix for sub-tasks inserted between two numbered
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steps (e.g. `02b`, `02c`). The parser normalizes `2b` → `02b`.
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```
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- [ ] 01 — Setup
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- [ ] 02 — Fix bugs
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- [ ] 02b — Sub-step of 02 (inserted after the fact)
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- [ ] 02c — Another sub-step of 02
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- [ ] 03 — Continue
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```
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Use lettered sub-tasks when you discover mid-stream that a step needs to be
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split. They let you preserve sibling numbering (`01`, `02`, `03`, ...) while
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adding granularity between two existing steps.
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## Dependencies
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### Arrow Notation (recommended)
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1 -> 2,3,4
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5 -> 6
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This means: "Task 1 must complete before tasks 2, 3, and 4 can start."
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### Natural Language
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13 depends on 17, 18, 19, 20
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14 depends on 13, 15, 16
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This means: "Task 13 depends on tasks 17, 18, 19, and 20."
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### Parallel Groups (informational only)
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1, 2, 3, 4 can be done in parallel
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5, 6, 7, 8 can be done in parallel
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Note: These lines are ignored by the parser. Use explicit dependencies to control execution order.
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## Configuration
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### Task-Level Timeout
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You can set a timeout for individual tasks using a meta block in the task file:
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```markdown
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- [ ] 01: Setup project structure
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timeout: 10m
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```
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Supported formats: `10m` (minutes), `600s` (seconds), `3600000` (milliseconds)
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### Config files
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| Scope | Path |
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|-------|------|
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| **Global** | `~/.pi/ralpi/config.yaml` |
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| **Project** | `./.ralpi/config.yaml` |
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```yaml
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execution:
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maxParallel: 3 # ralpi-level concurrency only
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models: # round-robin in <provider>/<model> format
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- google/gemini-3.5-flash # 1st and 3rd task in parallel
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- openai/gpt-5.5 # 2nd task in parallel
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autoCommit: true # spawn a commit agent after each task completes
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autoReview: false # spawn a review agent to review each commit
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implModel: "" # model for task impl (sequential mode, empty = inherit parent)
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commitModel: "" # model for commit sessions (empty = inherit task model)
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reviewModel: "" # model for review sessions (empty = inherit task model)
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timeoutMs: 0 # per-task timeout in ms (0 = inherit Pi's defaults)
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commitTimeoutMs: 60000 # timeout for auto-commit agent sessions
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reviewTimeoutMs: 120000 # timeout for auto-review agent sessions
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loopTimeoutMs: 0 # max total loop duration in ms (0 = no limit)
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prompts:
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projectContext: "Additional context for all tasks"
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```
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> `execution.models` uses slot-aware round-robin: with 3 models and 2 concurrent
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> tasks, only the first two models are used. The third model is only touched when
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> a third concurrent task starts. Freed model slots are reused before new ones
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> are allocated.
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> **Automatic failover**: if a provider/API is unreachable (rate limit, 503, etc.),
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> the task automatically cycles to the next model in the list without counting it
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> as a task failure. Each model is tried once before the task is marked as failed.
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> **NOTE**: this is only used in parallel execution, in sequential mode the
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> parent pi session's model is used
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#### Auto-commit and Auto-review
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When `autoCommit` is enabled (default), a follow-up agent session is spawned
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after each task to stage and commit uncommitted changes. When `autoReview` is
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enabled, a second follow-up session reviews the latest commit against the task
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description. Both options can be overridden at loop startup via a selection
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prompt.
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`commitModel` and `reviewModel` accept `<provider>/<model>` strings (e.g.
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`anthropic/claude-sonnet-4`) resolved via the model registry. When empty, the
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task's model is inherited. `implModel` sets the model for task implementation
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in sequential mode (overridden by `execution.models` round-robin in parallel
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mode).
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## State Files
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- `.ralpi/progress.json` - Execution progress
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- `.ralpi/reflections/` - Per-task reflections
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- `.ralpi/prompts/` - Generated prompts
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- `.ralpi/sessions/` - Full task output for review
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