mcpbeat Sign in

Agentflow Skill for Claude

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 crash-proof pipeline execution.

2k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
223
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/lingxling/awesome-skills-cn --skill agentflow

The instruction itself

34 sections, as written by the author

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, 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"

4. Start the Orchestrator

# Add to crontab (runs every 15 minutes)
crontab -e
# Add: */15 * * * * ~/.claude/sdlc/agentflow-cron.sh >> /tmp/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: 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
  • Spec drift detection: SHA-256 hash comparison catches requirement changes mid-sprint

Installation

# Clone the repo
git clone https://github.com/UrRhb/agentflow.git

# Copy skills and prompts to your Claude Code config
cp -r agentflow/skills/* ~/.claude/skills/
cp -r agentflow/prompts/* ~/.claude/sdlc/prompts/
cp agentflow/conventions.md ~/.claude/sdlc/conventions.md

Or install as a Claude Code plugin:

/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 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.

  • @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

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.

Other skills for the same job

different authors, same section of the catalogue
MCP Builder
by anthropics
vendor ×13

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

30k tokens scripts
Changelog Generator
by frostant
×9

Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.

774 tokens
Finishing A Development Branch
by ZhanlinCui
×7

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

1k tokens
MCP Builder
by JayZeeDesign
×7

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

37k tokens scripts
Vercel React Native Skills
by vercel-labs
vendor ×6

React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.

39k tokens
Vercel React Best Practices
by ratacat
×5

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

34k tokens
Next Best Practices
by vercel-labs
vendor ×4

Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling

20k tokens
Using Git Worktrees
by ZhanlinCui
×4

Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification

1k tokens

How to use it

Copy the folder

Take lingxling/agentflow from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.