--- name: agentflow description: "Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and recoverable pipeline design." risk: critical source: community date_added: "2026-04-02" --- # AgentFlow ## 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, recoverable task state (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 orchestration designed to recover after 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 detectable errors before the more expensive review; coverage and cost must be measured. AI review comes after, as a second layer. ### Adversarial Review An independent review should report only substantiated findings and incomplete coverage. Do not require an arbitrary number of flaws or fabricate issues to pass a gate. ### Transitive Priority Dispatch Tasks that unblock the most downstream work get built first, automatically computing the critical path. ## Prerequisites and authorization This AAS tree contains the guide only. Slash commands, cron script, worker runtime, board integration and templates named below belong to the separately reviewed upstream installation; do not claim they exist locally. Verify a fixed upstream revision, license, schemas and setup first. Creating board tasks/comments, spawning workers, configuring schedules, paid model calls, merging and publishing each require the user's applicable authorization. Preserve existing host files and use the current repository maintainer gates. For concurrent workers, require atomic task claims or leases, disjoint write ownership, bounded concurrency and verified artifact SHAs. A stale heartbeat does not prove a worker stopped; prevent duplicate paid jobs or writes before reassignment. ## 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 ` 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: ```bash # 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" ``` ### 4. Start the Orchestrator ```bash # Add to crontab (runs every 15 minutes) crontab -e # Add: */15 * * * * ~/.claude/sdlc/agentflow-cron.sh >> /path/to/private/agentflow-orchestrate.log 2>&1 ``` ### 5. Monitor and Intervene 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**: Evidence-based review resolves blocking findings and records coverage - **Test to Integrate**: 80% coverage threshold on new files - **Integrate to Done**: Required protected merge checks plus post-merge verification; scoped rollback follows the repository workflow ## Cost Tracking The following contributed numbers are historical illustrations, not current prices or implemented guarantees. Determine provider/model/tool charges, reserve the agreed currency budget before dispatch, track retries and parallel costs, then reconcile actual billing. 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 require a verified scoped rollback; a revert may not undo database changes or external effects - **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 - **Spec drift detection**: SHA-256 hash comparison catches requirement changes mid-sprint ## Installation ```bash # Clone the repo git clone https://github.com/UrRhb/agentflow.git # Copy skills and prompts to your Claude Code config # Inspect the fixed checkout, license and host-supported setup. # Copy only explicitly selected files to the authorized host location, preserving existing files. ``` Or install as a Claude Code plugin: ```bash /plugin marketplace add UrRhb/agentflow /plugin install agentflow ``` ## Best Practices - 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 protected scoped rollback for recovery - 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:** A verified revert may restore source behavior, but does not by itself restore data or guarantee 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 ## Additional Resources - [AgentFlow Repository](https://github.com/UrRhb/agentflow) - [Architecture Documentation](https://github.com/UrRhb/agentflow/blob/main/docs/architecture.md) - [Gap Registry (45 failure modes)](https://github.com/UrRhb/agentflow/blob/main/docs/gap-registry.md) - [Getting Started Guide](https://github.com/UrRhb/agentflow/blob/main/docs/getting-started.md) ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.