autopilot▌
yeachan-heo/oh-my-claudecode · updated Apr 8, 2026
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<Use_When>
<Use_When>
- User wants end-to-end autonomous execution from an idea to working code
- User says "autopilot", "auto pilot", "autonomous", "build me", "create me", "make me", "full auto", "handle it all", or "I want a/an..."
- Task requires multiple phases: planning, coding, testing, and validation
- User wants hands-off execution and is willing to let the system run to completion </Use_When>
<Do_Not_Use_When>
- User wants to explore options or brainstorm -- use
planskill instead - User says "just explain", "draft only", or "what would you suggest" -- respond conversationally
- User wants a single focused code change -- use
ralphor delegate to an executor agent - User wants to review or critique an existing plan -- use
plan --review - Task is a quick fix or small bug -- use direct executor delegation </Do_Not_Use_When>
<Why_This_Exists> Most non-trivial software tasks require coordinated phases: understanding requirements, designing a solution, implementing in parallel, testing, and validating quality. Autopilot orchestrates all of these phases automatically so the user can describe what they want and receive working code without managing each step. </Why_This_Exists>
<Execution_Policy>
- Each phase must complete before the next begins
- Parallel execution is used within phases where possible (Phase 2 and Phase 4)
- QA cycles repeat up to 5 times; if the same error persists 3 times, stop and report the fundamental issue
- Validation requires approval from all reviewers; rejected items get fixed and re-validated
- Cancel with
/oh-my-claudecode:cancelat any time; progress is preserved for resume </Execution_Policy>
-
Phase 1 - Planning: Create an implementation plan from the spec
- If ralplan consensus plan exists: Skip — already done in the 3-stage pipeline
- Architect (Opus): Create plan (direct mode, no interview)
- Critic (Opus): Validate plan
- Output:
.omc/plans/autopilot-impl.md
-
Phase 2 - Execution: Implement the plan using Ralph + Ultrawork
- Executor (Haiku): Simple tasks
- Executor (Sonnet): Standard tasks
- Executor (Opus): Complex tasks
- Run independent tasks in parallel
-
Phase 3 - QA: Cycle until all tests pass (UltraQA mode)
- Build, lint, test, fix failures
- Repeat up to 5 cycles
- Stop early if the same error repeats 3 times (indicates a fundamental issue)
-
Phase 4 - Validation: Multi-perspective review in parallel
- Architect: Functional completeness
- Security-reviewer: Vulnerability check
- Code-reviewer: Quality review
- All must approve; fix and re-validate on rejection
-
Phase 5 - Cleanup: Delete all state files on successful completion
- Remove
.omc/state/autopilot-state.json,ralph-state.json,ultrawork-state.json,ultraqa-state.json - Run
/oh-my-claudecode:cancelfor clean exit
- Remove
<Tool_Usage>
- Use
Task(subagent_type="oh-my-claudecode:architect", ...)for Phase 4 architecture validation - Use
Task(subagent_type="oh-my-claudecode:security-reviewer", ...)for Phase 4 security review - Use
Task(subagent_type="oh-my-claudecode:code-reviewer", ...)for Phase 4 quality review - Agents form their own analysis first, then spawn Claude Task agents for cross-validation
- Never block on external tools; proceed with available agents if delegation fails </Tool_Usage>
<Escalation_And_Stop_Conditions>
- Stop and report when the same QA error persists across 3 cycles (fundamental issue requiring human input)
- Stop and report when validation keeps failing after 3 re-validation rounds
- Stop when the user says "stop", "cancel", or "abort"
- If requirements were too vague and expansion produces an unclear spec, offer redirect to
/deep-interviewfor Socratic clarification, or pause and ask the user for clarification before proceeding </Escalation_And_Stop_Conditions>
<Final_Checklist>
- All 5 phases completed (Expansion, Planning, Execution, QA, Validation)
- All validators approved in Phase 4
- Tests pass (verified with fresh test run output)
- Build succeeds (verified with fresh build output)
- State files cleaned up
- User informed of completion with summary of what was built </Final_Checklist>
Optional settings in .claude/settings.json:
{
"omc": {
"autopilot": {
"maxIterations": 10,
"maxQaCycles": 5,
"maxValidationRounds": 3,
"pauseAfterExpansion": false,
"pauseAfterPlanning": false,
"skipQa": false,
"skipValidation": false
}
}
}
Resume
If autopilot was cancelled or failed, run /oh-my-claudecode:autopilot again to resume from where it stopped.
Best Practices for Input
- Be specific about the domain -- "bookstore" not "store"
- Mention key features -- "with CRUD", "with authentication"
- Specify constraints -- "using TypeScript", "with PostgreSQL"
- Let it run -- avoid interrupting unless truly needed
Troubleshooting
Stuck in a phase? Check TODO list for blocked tasks, review .omc/autopilot-state.json, or cancel and resume.
QA cycles exhausted? The same error 3 times indicates a fundamental issue. Review the error pattern; manual intervention may be needed.
Validation keeps failing? Review the specific issues. Requirements may have been too vague -- cancel and provide more detail.
Deep Interview Integration
When autopilot is invoked with a vague input, Phase 0 can redirect to /deep-interview for Socratic clarification:
User: "autopilot build me something cool"
Autopilot: "Your request is open-ended. Would you like to run a deep interview first?"
[Yes, interview first (Recommended)] [No, expand directly]
If a deep-interview spec already exists at .omc/specs/deep-interview-*.md, autopilot uses it directly as Phase 0 output (the spec has already been mathematically validated for clarity).
3-Stage Pipeline: deep-interview → ralplan → autopilot
The recommended full pipeline chains three quality gates:
/deep-interview "vague idea"
→ Socratic Q&A → spec (ambiguity ≤ 20%)
→ /ralplan --direct → consensus plan (Planner/Architect/Critic approved)
→ /autopilot → skips Phase 0+1, starts at Phase 2 (Execution)
When autopilot detects a ralplan consensus plan (.omc/plans/ralplan-*.md or .omc/plans/consensus-*.md), it skips both Phase 0 (Expansion) and Phase 1 (Planning) because the plan has already been:
- Requirements-validated (deep-interview ambiguity gate)
- Architecture-reviewed (ralplan Architect agent)
- Quality-checked (ralplan Critic agent)
Autopilot starts directly at Phase 2 (Execution via Ralph + Ultrawork).
How to use autopilot on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add autopilot
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches autopilot from GitHub repository yeachan-heo/oh-my-claudecode and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate autopilot. Access the skill through slash commands (e.g., /autopilot) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★57 reviews- ★★★★★Aisha Chawla· Dec 28, 2024
Keeps context tight: autopilot is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Pratham Ware· Dec 16, 2024
Useful defaults in autopilot — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Diego Robinson· Dec 16, 2024
I recommend autopilot for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Mateo Sanchez· Dec 8, 2024
autopilot has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Liam Harris· Dec 4, 2024
autopilot is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Mateo Nasser· Nov 27, 2024
autopilot fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Alexander Malhotra· Nov 23, 2024
Useful defaults in autopilot — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Zaid Mensah· Nov 19, 2024
I recommend autopilot for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yash Thakker· Nov 7, 2024
autopilot is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Daniel White· Nov 7, 2024
Keeps context tight: autopilot is the kind of skill you can hand to a new teammate without a long onboarding doc.
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