Yeachan-Heo

autopilot

Full autonomous execution from idea to working code

Yeachan-Heo 30,291 2,397 Updated 2mo ago
GitHub

Install

npx skillscat add yeachan-heo/oh-my-codex/autopilot

Install via the SkillsCat registry.

SKILL.md
Autopilot takes a brief product idea and autonomously handles the full lifecycle: requirements analysis, technical design, planning, parallel implementation, QA cycling, and multi-perspective validation. It produces working, verified code from a 2-3 line description. - 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> - User wants to explore options or brainstorm -- use `plan` skill instead - User says "just explain", "draft only", or "what would you suggest" -- respond conversationally - User wants a single focused code change -- use `ralph` or 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> 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> - 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 `/cancel` at any time; progress is preserved for resume - If a deep-interview spec exists, use it as high-clarity phase input instead of re-expanding from scratch - If input is too vague for reliable expansion, offer/trigger `$deep-interview` first - Do not enter expansion/planning/execution-heavy phases until pre-context grounding exists; if fast execution is forced, proceed only with explicit risk notes - Default to concise, evidence-dense progress and completion reporting unless the user or risk level requires more detail - Treat newer user task updates as local overrides for the active workflow branch while preserving earlier non-conflicting constraints - If correctness depends on additional inspection, retrieval, execution, or verification, keep using the relevant tools until the workflow is grounded - Continue through clear, low-risk, reversible next steps automatically; ask only when the next step is materially branching, destructive, or preference-dependent </Execution_Policy> 0. **Pre-context Intake (required before Phase 0 starts)**: - Derive a task slug from the request. - Load the latest relevant snapshot from `.omx/context/{slug}-*.md` when available. - If no snapshot exists, create `.omx/context/{slug}-{timestamp}.md` (UTC `YYYYMMDDTHHMMSSZ`) with: - Task statement - Desired outcome - Known facts/evidence - Constraints - Unknowns/open questions - Likely codebase touchpoints - If ambiguity remains high, run `explore` first for brownfield facts, then run `$deep-interview --quick ` before proceeding. - Carry the snapshot path into autopilot artifacts/state so all phases share grounded context.
  1. Phase 0 - Expansion: Turn the user's idea into a detailed spec

    • If .omx/specs/deep-interview-*.md exists for this task: reuse it and skip redundant expansion work
    • If prompt is highly vague: route to $deep-interview for Socratic ambiguity-gated clarification
    • Analyst (THOROUGH tier): Extract requirements
    • Architect (THOROUGH tier): Create technical specification
    • Output: .omx/plans/autopilot-spec.md
  2. Phase 1 - Planning: Create an implementation plan from the spec

    • Architect (THOROUGH tier): Create plan (direct mode, no interview)
    • Critic (THOROUGH tier): Validate plan
    • Output: .omx/plans/autopilot-impl.md
  3. Phase 2 - Execution: Implement the plan using Ralph + Ultrawork

    • LOW-tier executor/search roles: Simple tasks
    • STANDARD-tier executor roles: Standard tasks
    • THOROUGH-tier executor/architect roles: Complex tasks
    • Run independent tasks in parallel
  4. 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)
  5. 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
  6. Phase 5 - Cleanup: Clear all mode state via OMX MCP tools on successful completion

    • state_clear({mode: "autopilot"})
    • state_clear({mode: "ralph"})
    • state_clear({mode: "ultrawork"})
    • state_clear({mode: "ultraqa"})
    • Or run /cancel for clean exit
- Before first MCP tool use, call `ToolSearch("mcp")` to discover deferred MCP tools - Use `ask_codex` with `agent_role: "architect"` for Phase 4 architecture validation - Use `ask_codex` with `agent_role: "security-reviewer"` for Phase 4 security review - Use `ask_codex` with `agent_role: "code-reviewer"` for Phase 4 quality review - Agents form their own analysis first, then consult Codex for cross-validation - If ToolSearch finds no MCP tools or Codex is unavailable, proceed without it -- never block on external tools </Tool_Usage>

State Management

Use omx_state MCP tools for autopilot lifecycle state.

  • On start:
    state_write({mode: "autopilot", active: true, current_phase: "expansion", started_at: "<now>", state: {context_snapshot_path: "<snapshot-path>"}})
  • On phase transitions:
    state_write({mode: "autopilot", current_phase: "planning"})
    state_write({mode: "autopilot", current_phase: "execution"})
    state_write({mode: "autopilot", current_phase: "qa"})
    state_write({mode: "autopilot", current_phase: "validation"})
  • On completion:
    state_write({mode: "autopilot", active: false, current_phase: "complete", completed_at: "<now>"})
  • On cancellation/cleanup:
    run $cancel (which should call state_clear(mode="autopilot"))

Scenario Examples

Good: The user says continue after the workflow already has a clear next step. Continue the current branch of work instead of restarting or re-asking the same question.

Good: The user changes only the output shape or downstream delivery step (for example make a PR). Preserve earlier non-conflicting workflow constraints and apply the update locally.

Bad: The user says continue, and the workflow restarts discovery or stops before the missing verification/evidence is gathered.

User: "autopilot A REST API for a bookstore inventory with CRUD operations using TypeScript" Why good: Specific domain (bookstore), clear features (CRUD), technology constraint (TypeScript). Autopilot has enough context to expand into a full spec. User: "build me a CLI tool that tracks daily habits with streak counting" Why good: Clear product concept with a specific feature. The "build me" trigger activates autopilot. User: "fix the bug in the login page" Why bad: This is a single focused fix, not a multi-phase project. Use direct executor delegation or ralph instead. User: "what are some good approaches for adding caching?" Why bad: This is an exploration/brainstorming request. Respond conversationally or use the plan skill. - 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, pause and redirect to `$deep-interview` before proceeding </Escalation_And_Stop_Conditions> - [ ] 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> ## Configuration

Optional settings in ~/.codex/config.toml:

[omx.autopilot]
maxIterations = 10
maxQaCycles = 5
maxValidationRounds = 3
pauseAfterExpansion = false
pauseAfterPlanning = false
skipQa = false
skipValidation = false

Resume

If autopilot was cancelled or failed, run /autopilot again to resume from where it stopped.

Recommended Clarity Pipeline

For ambiguous requests, prefer:

deep-interview -> ralplan -> autopilot
  • deep-interview: ambiguity-gated Socratic requirements
  • ralplan: consensus planning (planner/architect/critic)
  • autopilot: execution + QA + validation

Best Practices for Input

  1. Be specific about the domain -- "bookstore" not "store"
  2. Mention key features -- "with CRUD", "with authentication"
  3. Specify constraints -- "using TypeScript", "with PostgreSQL"
  4. Let it run -- avoid interrupting unless truly needed

Pipeline Orchestrator (v0.8+)

Autopilot can be driven by the configurable pipeline orchestrator (src/pipeline/), which
sequences stages through a uniform PipelineStage interface:

RALPLAN (consensus planning) -> team-exec (Codex CLI workers) -> ralph-verify (architect verification)

Pipeline configuration options:

[omx.autopilot.pipeline]
maxRalphIterations = 10    # Ralph verification iteration ceiling
workerCount = 2            # Number of Codex CLI team workers
agentType = "executor"     # Agent type for team workers

The pipeline persists state via pipeline-state.json and supports resume from the last
incomplete stage. See src/pipeline/orchestrator.ts for the full API.

Troubleshooting

Stuck in a phase? Check TODO list for blocked tasks, run state_read({mode: "autopilot"}), 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.