Crank

Crank Skill

Quick Ref: Autonomous epic execution. Loops /implement on all issues until DONE. Output: closed issues + final vibe.

YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.

Autonomous execution: implement all issues until the epic is DONE.

Requires: bd CLI (beads) for issue tracking, OR in-session TaskList for task-based tracking.

Global Limits

MAX_EPIC_ITERATIONS = 50 (hard limit across entire epic)

This prevents infinite loops on circular dependencies or cascading failures.

Why 50?

• Typical epic: 5-10 issues
• With retries: ~5 iterations per issue max
• 50 = safe upper bound (10 issues × 5 retries)

MAX_PARALLEL_AGENTS = 3 (hard limit per wave)

When multiple issues are ready, execute them in parallel using subagents. Capped at 3 to prevent context explosion.

Why 3?

• Each subagent returns results that accumulate in context
• 3 parallel agents = manageable context growth
• Higher parallelism risks context overflow on complex issues

Completion Enforcement (The Sisyphus Rule)

THE SISYPHUS RULE: Not done until explicitly DONE.

After each task, output completion marker:

• <promise>DONE</promise> - Epic truly complete, all issues closed
• <promise>BLOCKED</promise> - Cannot proceed (with reason)
• <promise>PARTIAL</promise> - Incomplete (with remaining items)

Never claim completion without the marker.

Execution Steps

Given /crank [epic-id]:

Step 0: Load Knowledge Context (ao Integration)

Search for relevant learnings before starting the epic:

# If ao CLI available, inject prior knowledge about epic execution
if command -v ao &>/dev/null; then
    # Search for relevant learnings
    ao search "epic execution implementation patterns" 2>/dev/null | head -20

    # Check flywheel status
    ao flywheel status 2>/dev/null

    # Get current ratchet state
    ao ratchet status 2>/dev/null
fi

If ao not available, skip this step and proceed. The knowledge flywheel enhances but is not required.

Step 1: Identify the Epic

If epic ID provided: Use it directly. Do NOT ask for confirmation.

If no epic ID: Discover it:

bd list --type epic --status open 2>/dev/null | head -5

If bd not available, look for a plan:

ls -lt .agents/plans/ 2>/dev/null | head -3

If multiple epics found, ask user which one.

Step 1a: Initialize Iteration Counter

# Initialize crank tracking in epic notes
bd update <epic-id> --append-notes "CRANK_START: iteration=0 at $(date -Iseconds)" 2>/dev/null

Track in memory: iteration=0

Step 2: Get Epic Details

bd show <epic-id> 2>/dev/null

Or read the plan document if using file-based tracking.

Step 3: List Ready Issues (Current Wave)

Find issues that can be worked on (no blockers):

bd ready 2>/dev/null

bd ready returns the current wave - all unblocked issues. These can be executed in parallel because they have no dependencies on each other.

Or parse the plan document for Wave 1 issues.

Or use TaskList tool if using in-session task tracking.

Step 3a: Pre-flight Check - Issues Exist

Verify there are issues to work on:

If 0 ready issues found:

STOP and return error:
  "No ready issues found for this epic. Either:
   - All issues are blocked (check dependencies)
   - Epic has no child issues (run /plan first)
   - All issues already completed"

Do NOT proceed with empty issue list - this produces false "epic complete" status.

Step 4: Execute Wave (Parallel Subagents)

Ready issues are executed in parallel waves. Each wave dispatches up to MAX_PARALLEL_AGENTS (3) subagents.

BEFORE each wave:

# Increment iteration counter (count waves, not individual issues)
iteration=$((iteration + 1))
bd update <epic-id> --append-notes "CRANK_WAVE: $iteration at $(date -Iseconds)" 2>/dev/null

# CHECK GLOBAL LIMIT
if [[ $iteration -ge 50 ]]; then
    echo "<promise>BLOCKED</promise>"
    echo "Global iteration limit (50) reached. Remaining issues:"
    bd children <epic-id> --status open 2>/dev/null
    # STOP - do not continue
fi

Wave Execution Logic:

1. Get ready issues from Step 3
2. Batch into wave (max 3 issues per wave)
3. Dispatch subagents in parallel using Task tool

FOR EACH WAVE, USE THE TASK TOOL IN PARALLEL:

When you have N ready issues (where N ≤ 3), dispatch them in a SINGLE message with multiple Task tool calls:

# Example: 3 ready issues → 3 parallel Task calls in ONE message

Tool: Task (call 1)
Parameters:
  subagent_type: "general-purpose"
  description: "Implement <issue-id-1>"
  prompt: |
    Execute /implement <issue-id-1>

    Use the Skill tool to invoke the implement skill:
    - skill: "agentops:implement"
    - args: "<issue-id-1>"

    Return the completion marker when done.

Tool: Task (call 2)
Parameters:
  subagent_type: "general-purpose"
  description: "Implement <issue-id-2>"
  prompt: |
    Execute /implement <issue-id-2>

    Use the Skill tool to invoke the implement skill:
    - skill: "agentops:implement"
    - args: "<issue-id-2>"

    Return the completion marker when done.

Tool: Task (call 3)
Parameters:
  subagent_type: "general-purpose"
  description: "Implement <issue-id-3>"
  prompt: |
    Execute /implement <issue-id-3>

    Use the Skill tool to invoke the implement skill:
    - skill: "agentops:implement"
    - args: "<issue-id-3>"

    Return the completion marker when done.

CRITICAL: All Task calls for a wave MUST be in a single message to enable parallel execution.

If more than 3 ready issues: Process in batches of 3. Complete one wave before starting the next.

Check results from each subagent:

• If <promise>BLOCKED</promise> returned → record blocker, continue with others
• If <promise>PARTIAL</promise> returned → record remaining, continue with others
• If <promise>DONE</promise> returned → issue complete

Wait for all subagents in the wave to complete before proceeding to Step 5.

Step 5: Track Progress (No Per-Issue Vibe)

After implement completes:

1. Update issue status:

bd update <issue-id> --status closed 2>/dev/null

Or use TaskUpdate to mark task completed.

2. Track changed files in memory or use TaskCreate to note them.

3. Record ratchet progress (ao integration):

# If ao CLI available, record implementation progress
if command -v ao &>/dev/null; then
    ao ratchet record implement 2>/dev/null
    echo "Ratchet: recorded implementation of <issue-id>"
fi

If ao not available, skip ratchet recording.

Note: Skip per-issue vibe - validation is batched at the end to save context.

Step 6: Check for More Work

After completing an issue:

1. Check if new issues are now unblocked (use bd ready or TaskList)
2. If yes, return to Step 4
3. If no more issues after 3 retry attempts, proceed to Step 7
4. Max retries: If issues remain blocked after 3 checks, escalate: "Epic blocked - cannot unblock remaining issues"

Step 7: Final Batched Validation

When all issues complete, run ONE comprehensive vibe on recent changes:

# Get list of changed files from recent commits
git diff --name-only HEAD~10 2>/dev/null | sort -u

Run vibe on recent changes:

Tool: Skill
Parameters:
  skill: "agentops:vibe"
  args: "recent"

If CRITICAL issues found:

1. Fix them
2. Re-run vibe on affected files
3. Only proceed to completion when clean

Step 8: Extract Learnings (ao Integration)

Before reporting completion, extract learnings from the session:

# If ao CLI available, forge learnings from this epic execution
if command -v ao &>/dev/null; then
    # Extract learnings from recent session transcripts
    ao forge transcript ~/.claude/projects/*/conversations/*.jsonl 2>/dev/null

    # Show flywheel status post-execution
    echo "=== Flywheel Status ==="
    ao flywheel status 2>/dev/null

    # Show pending learnings for review
    ao pool list --tier=pending 2>/dev/null | head -10
fi

If ao not available, skip learning extraction. Recommend user runs /post-mortem manually.

Step 9: Report Completion

Tell the user:

1. Epic ID and title
2. Number of issues completed
3. Total iterations used (of 50 max)
4. Final vibe results
5. Flywheel status (if ao available)
6. Suggest running /post-mortem to review and promote learnings

Output completion marker:

<promise>DONE</promise>
Epic: <epic-id>
Issues completed: N
Iterations: M/50
Flywheel: <status from ao flywheel status>

If stopped early:

<promise>BLOCKED</promise>
Reason: <global limit reached | unresolvable blockers>
Issues remaining: N
Iterations: M/50

The FIRE Loop

Crank follows FIRE for each wave:

Parallel Wave Model:

Wave 1: [issue-1, issue-2, issue-3] → 3 subagents in parallel
         ↓         ↓         ↓
      DONE      DONE      BLOCKED
                            ↓
                      (retry in next wave)

Wave 2: [issue-4, issue-3-retry] → 2 subagents in parallel
         ↓         ↓
      DONE      DONE

Final vibe on all changes → Epic DONE

Loop until all issues are CLOSED.

Key Rules

• If epic ID given, USE IT - don't ask for confirmation
• Parallel waves - execute up to 3 issues per wave using subagents
• One subagent per issue - each issue gets its own isolated agent
• Max 3 subagents per wave - prevents context explosion
• Batch validation at end - ONE vibe at the end saves context
• Fix CRITICAL before completion - address findings before reporting done
• Loop until done - don't stop until all issues closed
• Autonomous execution - minimize human prompts
• Respect iteration limit - STOP at 50 iterations (hard limit)
• Output completion markers - DONE, BLOCKED, or PARTIAL (required)
• Knowledge flywheel - load learnings at start, forge at end (ao optional)

Without Beads

If bd CLI not available:

1. Use the plan document as the source of truth
2. Track completed issues by checking git commits
3. Mark issues done by noting in the plan document