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Agent skill

Agentflow

by sickn33 in sickn33/agentic-awesome-skills

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear).

MITAuto-check passedTesting & QA

Install Agentflow

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill agentflow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills agentflow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/agentflow .claude/skills/agentflow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agentflow
GitHub stars
47k
Used in
2 other repos
Token cost
~2k tokens
SKILL.md length
933 words
Files
1
Skills in repo
1,354
Repo updated
First seen
Licence
MIT

At a glance

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear).

  • Works in 6 steps: Write Your Spec → Decompose Into Tasks → Start Workers → …
  • Tasks that involve LLM cost and token optimization
  • SKILL.md covers Overview, When to Use This Skill, Core Concepts and Skills / Commands, plus 7 more sections
  • Calls claude, git and npm; reaches github.com

What it does

Agentflow is an agent skill from sickn33/agentic-awesome-skills. 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.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering LLM cost and token optimization, Quality gates and Sprint planning and agile. It works with GitHub and Asana. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve LLM cost and token optimization
  • Tasks that involve Quality gates
  • Tasks that involve Sprint planning and agile

Example prompts

  • “/agentflow”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Write Your Spec
  2. Decompose Into Tasks
  3. Start Workers
  4. Start the Orchestrator
  5. Monitor and Intervene
  6. Stop the Pipeline

What it can do on your machine

Read from SKILL.md and the folder at commit ec02547. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • claude
    • git
    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agentflow loads about 2k tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 933 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit ec02547, republished under its MIT licence (© sickn33). 933 words, ~2,042 tokens.

Download SKILL.mdSave it as .claude/skills/agentflow/SKILL.md (or your agent's skills folder).
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 crash-proof pipeline execution.
risk
safe
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, 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:

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 >> /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.

Show full SKILL.md (361 more words)Show less

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

bash
# 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:

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 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.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/agentflow of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit ec02547

Used in 2 other repositories

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Agentflow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agentflow compared with similar skills
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Agentflow this skillsickn33/agentic-awesome-skills47k2 repos~2kAutomated safety check: PassMIT
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lo2cin4bt Acceptance Reviewlo2cin4/lo2cin4bt288—~1.4kAutomated safety check: PassCustom licence
Dev ReviewFHIR/fhir-codegen154—~5kAutomated safety check: PassMIT
Michel Packmind Engineer ReviewPackmindHub/packmind317—~2.7kAutomated safety check: PassApache-2.0
cmux Testing Rulesdisler/learning-cmux-with-agents115—~1.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Agentflow

What does Agentflow do?

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Agentflow is an agent skill from sickn33/agentic-awesome-skills. Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear).

When should I use Agentflow?

Agentflow fits situations like: tasks that involve LLM cost and token optimization; tasks that involve Quality gates; tasks that involve Sprint planning and agile.

How do I install Agentflow in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill agentflow -a claude-code`. Or copy the skill folder (skills/agentflow in sickn33/agentic-awesome-skills) into .claude/skills/agentflow in your project. Claude Code loads it when a task matches its description.

How do I install Agentflow in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill agentflow -a codex`. Or copy the skill folder (skills/agentflow in sickn33/agentic-awesome-skills) into .agents/skills/agentflow in your project. Codex loads it when a task matches its description.

Can I use Agentflow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill agentflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agentflow, .gemini/skills/agentflow, .github/skills/agentflow and .opencode/skills/agentflow in your project.

What does Agentflow need to run?

Going by SKILL.md and its folder, Agentflow needs the command-line tools its instructions call (claude, git and npm).

Does Agentflow access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Agentflow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agentflow use?

Agentflow is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agentflow use?

About 2k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Agentflow?

Skills that share tags, products or a category with Agentflow: Cherry Studio Regression Tests (CherryHQ/cherry-studio, 52k stars), lo2cin4bt Acceptance Review (lo2cin4/lo2cin4bt, 288 stars), Dev Review (FHIR/fhir-codegen, 154 stars) and Michel Packmind Engineer Review (PackmindHub/packmind, 317 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agentflow?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,343 GitHub stars. The repository holds 1,354 skills in this directory. The repository was last updated on October 7, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.