ALWAYS use this when the request matches Agentflow: Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear).
ALWAYS use this when the request matches Agentflow: Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear).
AgentFlow
Selective Reading Rule
Start with:
references/senior-master-standard.md
references/usage-routing.md
references/quality-checklist.md
Then load only the inherited docs, scripts, assets, or examples that match the user's actual task.
Overview
AgentFlow turns your existing Kanban board into a fully autonomous AI development pipeline. Instead of building custom orchestration infrastructure, it treats your project management tool (Asana, GitHub Projects, Linear) as a distributed state machine — tasks move through stages, AI agents read and write state via comments, and humans intervene through the same UI they already use.
The result is complete pipeline observability from your phone, free crash recovery (state lives in your PM tool, not in memory), and human override at any point by dragging a card.
When to Use This Skill
Use when you need to orchestrate multiple Claude Code workers across a full development lifecycle (build, review, test, integrate)
Use when you want deterministic quality gates (tsc/eslint/tests) before AI review on AI-generated code
Use when you want full pipeline visibility from your Kanban board or phone
Use when running a solo or team project that needs autonomous task dispatch with cost tracking
Use when you need crash-proof orchestration that survives session restarts
Core Concepts
7-Stage Kanban Pipeline
Tasks flow through: Backlog, Research, Build, Review, Test, Integrate, Done. Each stage has specific gates. The Kanban board IS the orchestration layer — no separate database, no message queue, no custom infrastructure.
Stateless Orchestrator
A crontab-driven one-shot sweep runs every 15 minutes. No daemon, no session dependency. If it crashes, the next sweep picks up where it left off because all state lives in your PM tool.
Deterministic Before Probabilistic
Hard gates (tsc + eslint + tests) run before any AI review, catching roughly 60% of issues at near-zero cost. AI review comes after, as a second layer.
Adversarial Review
A different AI agent reviews code and must list 3 things wrong before deciding to pass. This prevents rubber-stamp approvals.
Transitive Priority Dispatch
Tasks that unblock the most downstream work get built first, automatically computing the critical path.
Skills / Commands
/spec-to-board
Decomposes a SPEC.md into atomic tasks on your Kanban board with dependencies mapped.
/sdlc-orchestrate
Dispatches tasks to workers based on transitive priority and conflict detection. Runs as a crontab sweep.
/sdlc-worker --slot <N>
Runs a worker in a terminal slot that picks up tasks, builds code, and creates PRs. Run 3-4 workers in parallel.
/sdlc-health
Real-time pipeline status dashboard showing current stage, assigned agent, retry count, and accumulated cost for every task.
/sdlc-stop
Graceful shutdown: active workers finish their current task, unstarted tasks return to Backlog.
Step-by-Step Guide
1. Write Your Spec
Create a SPEC.md for your project describing what you want to build.
2. Decompose Into Tasks
claude -p "/spec-to-board"
This reads your SPEC.md, decomposes it into atomic tasks, maps dependencies, and creates them on your Kanban board.
3. Start Workers
Open 3-4 terminal windows, each as a worker slot:
# Terminal 2 — Builder
claude -p "/sdlc-worker --slot T2"# Terminal 3 — Builder
claude -p "/sdlc-worker --slot T3"# Terminal 4 — Reviewer
claude -p "/sdlc-worker --slot T4"# Terminal 5 — Tester
claude -p "/sdlc-worker --slot T5"
Open your Kanban board on your phone. Watch tasks flow through the pipeline. Drag any card to "Needs Human" to intervene. Run /sdlc-health for a terminal dashboard.
6. Stop the Pipeline
claude -p "/sdlc-stop"
Quality Gates
Each stage enforces specific gates before promotion:
Build to Review: tsc + eslint + npm test must all pass (deterministic)
Review to Test: Adversarial reviewer must list 3 issues before passing
Test to Integrate: 80% coverage threshold on new files
Integrate to Done: Full test suite on main after merge; auto-reverts on failure
Cost Tracking
Per-task cost tracking with stage ceilings (Sonnet defaults):
Research: ~$0.10
Build: ~$0.40
Review: ~$0.10
Test: ~$0.05
Integrate: ~$0.03
Automatic guardrails: warning at $3/$8, hard stop at $10/$20 (Sonnet/Opus) with human escalation.
Safety and Recovery
Auto-revert: Integration failures trigger git revert (new commit, never force-push)
Blocked tasks: After 2 failed attempts, tasks escalate to human review
Dead agent detection: Heartbeat every 5 min, reassign after 10 min timeout
Graceful shutdown: /sdlc-stop drains workers, returns unstarted tasks to backlog
Scope creep detection: PR diff files compared against predicted files list
Do: Write a clear SPEC.md before running /spec-to-board
Do: Start with 3-4 workers for a typical project
Do: Monitor from your Kanban board and drag cards to "Needs Human" when needed
Do: Review LEARNINGS.md periodically — it captures common failure patterns
Don't: Skip the deterministic quality gates — they catch most issues cheaply
Don't: Force-push to main — AgentFlow uses git revert for safety
Don't: Run more workers than your project's parallelism supports
Troubleshooting
Problem: Worker appears stuck or dead
Symptoms: Task card hasn't moved in 15+ minutes, no new comments
Solution: The orchestrator detects dead agents via heartbeat and reassigns after 10 minutes. If the issue persists, run /sdlc-health to check status and manually drag the card back to Backlog.
Problem: Cost guardrail triggered
Symptoms: Task moved to "Needs Human" with COST:CRITICAL tag
Solution: Review the task's comment thread for accumulated context. Decide whether to increase the budget, simplify the task, or split it into smaller pieces.
Problem: Integration test failure after merge
Symptoms: Task auto-reverted from main
Solution: The auto-revert preserves main stability. Check the task's retry context in comments, which carries what was tried and what failed. The next worker assigned will use this context.
Related Skills
@brainstorming - Use before AgentFlow to design your SPEC.md
@writing-plans - Complements spec writing for task decomposition
@test-driven-development - Works well with AgentFlow's quality gates
@subagent-driven-development - Alternative approach to multi-agent coordination