Pi Workflow Orchestration

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name: pi-workflow description: Workflow orchestration for Pi's task management, self-improvement, and code quality standards. Use when starting new projects, managing multi-step tasks (3+ steps or architectural decisions), capturing lessons from mistakes, writing verifiable code, or establishing quality gates before completion. Includes planning templates, progress tracking, bug fixing autonomy, and a lessons capture system to prevent repeated mistakes.

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Pi Workflow Orchestration

This skill provides Pi's structured approach to task management, quality assurance, and continuous self-improvement.

Core Workflows

1. Plan Node Default

Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions):

Write detailed specs upfront to reduce ambiguity

If something goes sideways, STOP and re-plan immediately—don't keep pushing

Use plan mode for verification steps, not just building

2. Subagent Strategy

Use subagents liberally to keep main context window clean

Offload research, exploration, and parallel analysis to subagents

For complex problems, throw more compute at it via subagents

One tack per subagent for focused execution

3. Self-Improvement Loop

After ANY correction from the user: update tasks/lessons.md with metadata (Priority, Status, Area, Pattern-Key)

Log command failures to tasks/errors.md for diagnosis patterns

Log feature requests to tasks/feature_requests.md for future work

Write rules for yourself that prevent the same mistake

Ruthlessly iterate on these lessons until mistake rate drops

Review lessons at session start for relevant projects

Track recurring patterns with Recurrence-Count (bump priority at ≥3 occurrences)

4. Verification Before Done

Never mark a task complete without proving it works

Diff behavior between main and your changes when relevant

Ask yourself: "Would a staff engineer approve this?"

Run tests, check logs, demonstrate correctness

5. Demand Elegance (Balanced)

For non-trivial changes: pause and ask "is there a more elegant way?"

If a fix feels hacky: "Knowing everything I know now, implement the elegant solution"

Skip this for simple, obvious fixes—don't over-engineer

Challenge your own work before presenting it

6. Autonomous Bug Fixing

When given a bug report: just fix it. Don't ask for hand-holding

Point at logs, errors, failing tests—then resolve them

Zero context switching required from the user

Go fix failing CI tests without being told how

Task Management

1. Plan First: Write plan to tasks/todo.md with checkable items 2. Verify Plan: Check in before starting implementation 3. Track Progress: Mark items complete as you go 4. Explain Changes: High-level summary at each step 5. Document Results: Add review section to tasks/todo.md 6. Capture Lessons: Update tasks/lessons.md after corrections

File Organization

tasks/todo.md — active sprint (current project)

tasks/lessons.md — corrections, insights, best practices (structured)

tasks/errors.md — command failures, API errors, exceptions (NEW)

tasks/feature_requests.md — missing capabilities, feature requests (NEW)

memory/YYYY-MM-DD.md — session logs (daily)

MEMORY.md — your curated memories (maintained by user)

See WORKFLOW_ORCHESTRATION.md for detailed reference.

See LESSONS.md for philosophy and framing.

See PHASE1-PHASE2-ENHANCED-LESSONS.md for structured lesson format and file separation.

See LESSONS_UPDATE_GUIDE.md for syncing lessons from workspace to skill.

Capturing Lessons

Lessons Format (Phase 1+2 Enhanced)

Each lesson gets structured metadata for filtering and recurring pattern detection:

## [LRN-YYYYMMDD-XXX] rule_name (category)
Logged: ISO-8601 timestamp
Priority: low | medium | high | critical
Status: pending | in_progress | resolved | promoted
Area: backend | infra | tests | docs | config
Pattern-Key: category.pattern_name (optional, for recurring detection)
Summary
One-line description
Details
Full context and examples
Applied to
Projects or files where this was used
Metadata
Source: correction | insight | user_feedback
Related Files: path/to/file
Tags: tag1, tag2
See Also: LRN-20250225-001 (if related to existing entry)
Recurrence-Count: 1 (increment if you see it again)
First-Seen: 2025-02-23
Last-Seen: 2025-02-23

Errors & Features (NEW)

Log failures and feature gaps separately for better organization:

Errors (tasks/errors.md):

Command failures, API errors, exceptions

Include reproducibility, environment, suggested fix

Features (tasks/feature_requests.md):

Missing capabilities, things you wish existed

Include complexity estimate and suggested implementation

Syncing to Skill

Periodically merge workspace lessons into the published skill:

# From openclaw-workflow repo
python3 scripts/sync_lessons.py --workspace ~/.openclaw/workspace
Dry run (preview changes)
python3 scripts/sync_lessons.py --workspace ~/.openclaw/workspace --dry-run

This merges workspace lessons into references/lessons.md for version control and sharing.

Hooks (Optional)

Enable automatic bootstrap reminders for self-improvement:

openclaw hooks enable pi-workflow

This injects a reminder at session start showing:

When to log lessons/errors/features

Format and metadata fields

Recurring pattern detection

Promotion paths

See hooks/openclaw/HOOK.md for details.

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Core Principles

Simplicity First: Make every change as simple as possible. Minimal code impact.

No Laziness: Find root causes. No temporary fixes. Senior developer standards.

Minimal Impact: Changes should only touch what's necessary. Avoid introducing bugs.