By akaszubski
Enforces PROJECT.md-first autonomous development with an 8-agent pipeline that auto-orchestrates research, planning, testing, implementation, review, security audit, and documentation sync. Validates every feature against project goals, detects code-doc drift, generates tests, and auto-updates docs on commit.
Critical thinking analysis - validates alignment, challenges assumptions, identifies risks
Check and fix CLAUDE.md alignment with codebase
Retrofit brownfield projects for autonomous development
Analyze and fix project alignment with PROJECT.md using GenAI
Unified alignment command (--project, --docs, --retrofit)
Critical thinking agent - validates alignment, challenges assumptions, identifies risks before decisions
Find conflicts between PROJECT.md (truth) and reality (code/docs), ask one question per conflict
Validate user requests against PROJECT.md goals, scope, and constraints
This directory contains agents that have been deprecated or replaced.
Master coordinator - validates PROJECT.md alignment and coordinates specialist agents
Detects when user requests warrant critical analysis via /advise command
Standardized output formats for research, planning, implementation, and review agents. Use when generating agent outputs or parsing agent responses.
REST API design best practices, versioning strategies, error handling, pagination, and OpenAPI documentation. Use when designing or implementing REST APIs, HTTP endpoints, or API documentation.
API integration patterns for autonomous-dev including subprocess safety, GitHub CLI integration, retry logic, authentication, rate limiting, and timeout handling. Use when integrating external APIs or CLI tools.
This skill should be used when designing system architecture, making architectural decisions, or evaluating design patterns. It provides guidance on common patterns, ADR templates, design principles, and tradeoff analysis.
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Traditional software engineering meets AI.
Claude is brilliant but drifts. It starts with a plan, then improvises. Documentation falls out of sync. Tests get "added later." Direction shifts mid-feature.
autonomous-dev provides macro alignment with micro flexibility:
research → plan → test → implement → review → security → docs → commit
Every step. Every feature. Documentation, tests, and code stay in sync automatically.
/auto-implement "issue #72"
# 1. Install
bash <(curl -sSL https://raw.githubusercontent.com/akaszubski/autonomous-dev/master/install.sh)
# 2. Restart Claude Code (required - commands are cached)
# Press Cmd+Q, then reopen
# 3. Use
/auto-implement "your feature description"
Requirements:
System tools (install separately):
xcode-select --install or brew install gitbrew install gh && gh auth login (required for GitHub automation)For contributors: Development dependencies are in plugins/autonomous-dev/requirements-dev.txt (pytest, coverage, etc.)
Claude working alone drifts. Claude working within a framework stays consistent.
| Without autonomous-dev | With autonomous-dev |
|---|---|
| Claude decides workflow per-session | Same 8-step pipeline every time |
| Plan drifts mid-implementation | Macro alignment checked, micro improvements allowed |
| Tests written "if time permits" | Tests written first (TDD enforced) |
| Documentation falls out of sync | Auto-updated every feature |
| "Best practices" from training data | Actual web search with source URLs |
| Scope creep ("while I'm here...") | Out-of-scope requests blocked |
| Manual commit/push/PR | Automated git workflow |
The insight: This isn't about limiting Claude. It's about fusing traditional software engineering discipline with AI capability. Claude brings intelligence; the framework brings consistency.
When you run /auto-implement "add user authentication":
| Step | What Happens | Time |
|---|---|---|
| 0. Alignment | Checks feature against PROJECT.md scope | <1 min |
| 1. Research | Searches codebase AND web (parallel) | 2-3 min |
| 1.1 Validation | Verifies web search actually ran (not hallucinated) | <1 min |
| 2. Planning | Designs implementation approach | 2-4 min |
| 3. TDD Tests | Writes failing tests first | 3-8 min |
| 4. Implementation | Makes tests pass | 3-8 min |
| 5-7. Validation | Review + Security + Docs (parallel) | 2-4 min |
| 8. Git | Commit, push, PR (automated) | <1 min |
Total: 15-30 minutes depending on complexity.
After completion:
Most AI coding tools answer from training data. That's fine for "how do I sort a list" but dangerous for "what's the current best practice for JWT authentication."
We force actual web search:
└─ Task (Research best practices) · 5 tool uses ✅
⎿ Web Search: JWT authentication best practices 2024...
If you see 0 tool uses, the pipeline blocks:
❌ Web research failed: 0 WebSearch calls made.
Results would be hallucinated. Retrying...
This validation was added because we caught Claude returning "best practices" that it never actually searched for.
# .claude/PROJECT.md
## GOALS
- Build REST API for user management
- Ship MVP by end of Q1
## SCOPE
IN: User CRUD, authentication, password reset
OUT: Admin dashboard, analytics, billing
## CONSTRAINTS
- Python 3.11+ with FastAPI
- PostgreSQL database
- JWT authentication (no sessions)
Request something IN scope: Claude follows your constraints.
Request something OUT of scope: Blocked immediately.
❌ BLOCKED: Feature not aligned with PROJECT.md
Feature requested: "Add analytics dashboard"
Why blocked: Explicitly OUT of scope
This prevents the "while I'm here, let me also refactor..." drift.
npx claudepluginhub akaszubski/autonomous-dev --plugin autonomous-devAccess thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
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