skills/autopilot/SKILL.md
Full autonomous execution from idea to working code — expand, plan, implement, QA, validate
npx skillsauth add sartoris-digital/pi-superpowers autopilotInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Autopilot takes a product idea and autonomously handles the full lifecycle: requirements analysis, technical design, planning, parallel implementation, QA cycling, and multi-perspective validation.
brainstorming skill insteadTurn the user's idea into a detailed spec.
Skip Phase 0 if a deep-interview spec exists at docs/superpowers/specs/deep-interview-*.md — use the pre-validated spec directly.
If input is vague (no file paths, function names, or concrete anchors), offer redirect to deep-interview for Socratic clarification before expanding.
Otherwise:
subagent({
agent: "analyst",
tier: "reasoning",
task: "Extract requirements, acceptance criteria, and gaps from this idea: {idea}"
})
subagent({
agent: "architect",
tier: "reasoning",
task: "MODE: plan-review\nCreate technical specification from this analyst output: {analyst_output}"
})
Save spec to docs/superpowers/autopilot/spec.md.
Create an implementation plan from the spec.
Skip Phase 1 if a ralplan consensus plan exists at docs/superpowers/plans/ralplan-*.md.
subagent({
chain: [
{ agent: "scout", tier: "fast", task: "Map relevant codebase areas for: {spec}" },
{ agent: "planner", tier: "standard", task: "Create implementation plan from spec: {spec}\nContext: {previous}" }
]
})
Then validate with critic:
subagent({
agent: "critic",
tier: "reasoning",
task: "Review this implementation plan: {plan}"
})
Save plan to docs/superpowers/plans/autopilot-impl.md.
Implement the plan using parallel subagent dispatch.
subagent({
tasks: [
{ agent: "worker", tier: "standard", task: "Implement task 1 from plan: {plan}" },
{ agent: "worker", tier: "standard", task: "Implement task 2 from plan: {plan}" }
]
})
Route complex tasks to reasoning tier, simple tasks to fast tier.
Cycle until all tests pass (max 5 cycles):
If the same error persists across 3 cycles, stop and report — indicates a fundamental issue requiring human input.
Multi-perspective review in parallel:
subagent({
tasks: [
{ agent: "architect", tier: "reasoning", task: "MODE: verification\nVerify functional completeness: {changes}" },
{ agent: "security-reviewer", tier: "reasoning", task: "Review for vulnerabilities: {changes}" },
{ agent: "code-reviewer", tier: "reasoning", task: "Review code quality: {changes}" }
]
})
All must approve. Fix and re-validate on rejection (max 3 rounds).
Remove state files and report completion to user with a summary of what was built.
The recommended full pipeline chains three quality gates:
/deep-interview "vague idea"
→ Socratic Q&A → spec (ambiguity ≤ 20%)
→ /ralplan → consensus plan (planner/architect/critic approved)
→ /autopilot → skips Phase 0+1, starts at Phase 2 (Execution)
testing
Use when creating new skills, editing existing skills, or verifying skills work before deployment
development
Use when you have a spec or requirements for a multi-step task, before touching code
data-ai
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
tools
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions