ccw

Auto Mode

When -y or --yes: Skip clarification and confirmation prompts. Pass -y through to each step's skill invocation.

CCW

Usage

$ccw "implement user authentication with JWT"
$ccw -y "refactor the payment module"
$ccw --continue
$ccw --dry-run "add rate limiting to API endpoints"
$ccw --chain feature "add dark mode toggle"

Flags:

• -y, --yes — Auto mode: skip all prompts; propagate -y to each skill
• --continue — Resume latest paused session from last incomplete wave
• --dry-run — Display planned chain without executing
• --chain <name> — Force a specific chain (skips intent classification)

Session state: .workflow/.ccw-coordinate/{session-id}/ Core Output: tasks.csv (master) + wave-{N}-results.csv (per wave) + context.md (report)

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Overview

Wave-based pipeline coordinator. The coordinator loop builds one wave CSV at a time, calls spawn_agents_on_csv, then performs coordinator-side artifact analysis before assembling the next wave. Barrier skills produce artifacts (plan.json, analysis results, etc.) that the coordinator reads to dynamically resolve args for subsequent steps.

Intent → Structured Extract → Resolve Chain → [Wave Loop]:
          (action×object×style)  (chainMap)
  ┌─────────────────────────────────────────────────┐
  │ 1. Identify next wave (1 or N parallel steps)   │
  │ 2. Build wave-{N}.csv with skill_call per row   │
  │ 3. spawn_agents_on_csv(wave-{N}.csv)            │
  │ 4. Read wave-{N}-results.csv                    │
  │ 5. If barrier skill: analyze artifacts,         │
  │    update context for subsequent steps           │
  │ 6. Merge into master tasks.csv                  │
  └─────────────────────────────────────────────────┘
  → Report

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Barrier Skills

Skills that produce artifacts requiring coordinator-side analysis before the next wave can be assembled. After a barrier skill completes, the coordinator reads its output and updates the execution context.