mirror of
https://github.com/azaion/gps-denied-onboard.git
synced 2026-04-23 07:26:37 +00:00
Oleksandr Bezdieniezhnykh
322 lines
15 KiB
Markdown
322 lines
15 KiB
Markdown
---
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name: autopilot
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description: |
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Auto-chaining orchestrator that drives the full BUILD-SHIP workflow from problem gathering through deployment.
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Detects current project state from _docs/ folder, resumes from where it left off, and flows through
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problem → research → plan → decompose → implement → deploy without manual skill invocation.
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Maximizes work per conversation by auto-transitioning between skills.
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Trigger phrases:
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- "autopilot", "auto", "start", "continue"
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- "what's next", "where am I", "project status"
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category: meta
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tags: [orchestrator, workflow, auto-chain, state-machine, meta-skill]
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disable-model-invocation: true
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---
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# Autopilot Orchestrator
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Auto-chaining execution engine that drives the full BUILD → SHIP workflow. Detects project state from `_docs/`, resumes from where work stopped, and flows through skills automatically. The user invokes `/autopilot` once — the engine handles sequencing, transitions, and re-entry.
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## Core Principles
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- **Auto-chain**: when a skill completes, immediately start the next one — no pause between skills
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- **Only pause at decision points**: BLOCKING gates inside sub-skills are the natural pause points; do not add artificial stops between steps
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- **State from disk**: all progress is persisted to `_docs/_autopilot_state.md` and cross-checked against `_docs/` folder structure
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- **Rich re-entry**: on every invocation, read the state file for full context before continuing
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- **Delegate, don't duplicate**: read and execute each sub-skill's SKILL.md; never inline their logic here
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## State File: `_docs/_autopilot_state.md`
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The autopilot persists its state to `_docs/_autopilot_state.md`. This file is the primary source of truth for re-entry. Folder scanning is the fallback when the state file doesn't exist.
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### Format
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```markdown
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# Autopilot State
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## Current Step
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step: [0-5 or "done"]
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name: [Problem / Research / Plan / Decompose / Implement / Deploy / Done]
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status: [not_started / in_progress / completed]
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sub_step: [optional — sub-skill phase if interrupted mid-step, e.g. "Plan Step 3: Component Decomposition"]
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## Completed Steps
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| Step | Name | Completed | Key Outcome |
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|------|------|-----------|-------------|
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| 0 | Problem | [date] | [one-line summary] |
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| 1 | Research | [date] | [N drafts, final approach summary] |
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| 2 | Plan | [date] | [N components, architecture summary] |
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| 3 | Decompose | [date] | [N tasks, total complexity points] |
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| 4 | Implement | [date] | [N batches, pass/fail summary] |
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| 5 | Deploy | [date] | [artifacts produced] |
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## Key Decisions
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- [decision 1: e.g. "Tech stack: Python + Rust for perf-critical, Postgres DB"]
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- [decision 2: e.g. "6 research rounds, final draft: solution_draft06.md"]
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- [decision N]
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## Last Session
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date: [date]
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ended_at: [step name and phase]
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reason: [completed step / session boundary / user paused / context limit]
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notes: [any context for next session, e.g. "User asked to revisit risk assessment"]
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## Blockers
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- [blocker 1, if any]
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- [none]
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```
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### State File Rules
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1. **Create** the state file on the very first autopilot invocation (after state detection determines Step 0)
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2. **Update** the state file after every step completion, every session boundary, and every BLOCKING gate confirmation
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3. **Read** the state file as the first action on every invocation — before folder scanning
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4. **Cross-check**: after reading the state file, verify against actual `_docs/` folder contents. If they disagree (e.g., state file says Step 2 but `_docs/02_plans/architecture.md` already exists), trust the folder structure and update the state file to match
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5. **Never delete** the state file. It accumulates history across the entire project lifecycle
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## Execution Entry Point
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Every invocation of this skill follows the same sequence:
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```
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1. Read _docs/_autopilot_state.md (if exists)
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2. Cross-check state file against _docs/ folder structure
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3. Resolve current step (state file + folder scan)
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4. Present Status Summary (from state file context)
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5. Enter Execution Loop:
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a. Read and execute the current skill's SKILL.md
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b. When skill completes → update state file
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c. Re-detect next step
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d. If next skill is ready → auto-chain (go to 5a with next skill)
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e. If session boundary reached → update state file with session notes → suggest new conversation
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f. If all steps done → update state file → report completion
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```
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## State Detection
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Read `_docs/_autopilot_state.md` first. If it exists and is consistent with the folder structure, use the `Current Step` from the state file. If the state file doesn't exist or is inconsistent, fall back to folder scanning.
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### Folder Scan Rules (fallback)
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Scan `_docs/` to determine the current workflow position. Check rules in order — first match wins.
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### Detection Rules
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**Step 0 — Problem Gathering**
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Condition: `_docs/00_problem/` does not exist, OR any of these are missing/empty:
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- `problem.md`
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- `restrictions.md`
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- `acceptance_criteria.md`
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- `input_data/` (must contain at least one file)
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Action: Read and execute `.cursor/skills/problem/SKILL.md`
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---
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**Step 1 — Research (Initial)**
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Condition: `_docs/00_problem/` is complete AND `_docs/01_solution/` has no `solution_draft*.md` files
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Action: Read and execute `.cursor/skills/research/SKILL.md` (will auto-detect Mode A)
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---
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**Step 1b — Research Decision**
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Condition: `_docs/01_solution/` contains `solution_draft*.md` files AND `_docs/01_solution/solution.md` does not exist AND `_docs/02_plans/architecture.md` does not exist
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Action: Present the current research state to the user:
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- How many solution drafts exist
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- Whether tech_stack.md and security_analysis.md exist
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- One-line summary from the latest draft
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Then ask: **"Run another research round (Mode B assessment), or proceed to planning?"**
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- If user wants another round → Read and execute `.cursor/skills/research/SKILL.md` (will auto-detect Mode B)
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- If user wants to proceed → auto-chain to Step 2 (Plan)
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---
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**Step 2 — Plan**
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Condition: `_docs/01_solution/` has `solution_draft*.md` files AND `_docs/02_plans/architecture.md` does not exist
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Action:
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1. The plan skill's Prereq 2 will rename the latest draft to `solution.md` — this is handled by the plan skill itself
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2. Read and execute `.cursor/skills/plan/SKILL.md`
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If `_docs/02_plans/` exists but is incomplete (has some artifacts but no `FINAL_report.md`), the plan skill's built-in resumability handles it.
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---
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**Step 3 — Decompose**
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Condition: `_docs/02_plans/` contains `architecture.md` AND `_docs/02_plans/components/` has at least one component AND `_docs/02_tasks/` does not exist or has no task files (excluding `_dependencies_table.md`)
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Action: Read and execute `.cursor/skills/decompose/SKILL.md`
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If `_docs/02_tasks/` has some task files already, the decompose skill's resumability handles it.
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---
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**Step 4 — Implement**
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Condition: `_docs/02_tasks/` contains task files AND `_dependencies_table.md` exists AND `_docs/03_implementation/FINAL_implementation_report.md` does not exist
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Action: Read and execute `.cursor/skills/implement/SKILL.md`
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If `_docs/03_implementation/` has batch reports, the implement skill detects completed tasks and continues.
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---
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**Step 5 — Deploy**
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Condition: `_docs/03_implementation/FINAL_implementation_report.md` exists AND `_docs/04_deploy/` does not exist or is incomplete
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Action: Read and execute `.cursor/skills/deploy/SKILL.md`
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---
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**Done**
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Condition: `_docs/04_deploy/` contains all expected artifacts (containerization.md, ci_cd_pipeline.md, environment_strategy.md, observability.md, deployment_procedures.md)
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Action: Report project completion with summary.
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## Status Summary
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On every invocation, before executing any skill, present a status summary built from the state file (with folder scan fallback).
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Format:
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```
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═══════════════════════════════════════════════════
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AUTOPILOT STATUS
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═══════════════════════════════════════════════════
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Step 0 Problem [DONE / IN PROGRESS / NOT STARTED]
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Step 1 Research [DONE (N drafts) / IN PROGRESS / NOT STARTED]
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Step 2 Plan [DONE / IN PROGRESS / NOT STARTED]
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Step 3 Decompose [DONE (N tasks) / IN PROGRESS / NOT STARTED]
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Step 4 Implement [DONE / IN PROGRESS (batch M of ~N) / NOT STARTED]
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Step 5 Deploy [DONE / IN PROGRESS / NOT STARTED]
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═══════════════════════════════════════════════════
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Current step: [Step N — Name]
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Action: [what will happen next]
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═══════════════════════════════════════════════════
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```
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For re-entry (state file exists), also include:
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- Key decisions from the state file's `Key Decisions` section
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- Last session context from the `Last Session` section
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- Any blockers from the `Blockers` section
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## Auto-Chain Rules
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After a skill completes, apply these rules:
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| Completed Step | Next Action |
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|---------------|-------------|
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| Problem Gathering | Auto-chain → Research (Mode A) |
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| Research (any round) | Auto-chain → Research Decision (ask user: another round or proceed?) |
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| Research Decision → proceed | Auto-chain → Plan |
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| Plan | Auto-chain → Decompose |
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| Decompose | **Session boundary** — suggest new conversation before Implement |
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| Implement | Auto-chain → Deploy |
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| Deploy | Report completion |
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### Session Boundary: Decompose → Implement
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After decompose completes, **do not auto-chain to implement**. Instead:
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1. Update state file: mark Decompose as completed, set current step to 4 (Implement) with status `not_started`
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2. Write `Last Session` section: `reason: session boundary`, `notes: Decompose complete, implementation ready`
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3. Present a summary: number of tasks, estimated batches, total complexity points
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4. Suggest: "Implementation is the longest phase and benefits from a fresh conversation context. Start a new conversation and type `/autopilot` to begin implementation."
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5. If the user insists on continuing in the same conversation, proceed.
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This is the only hard session boundary. All other transitions auto-chain.
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## Skill Delegation
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For each step, the delegation pattern is:
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1. Update state file: set current step to `in_progress`, record `sub_step` if applicable
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2. Announce: "Starting [Skill Name]..."
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3. Read the skill file: `.cursor/skills/[name]/SKILL.md`
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4. Execute the skill's workflow exactly as written, including:
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- All BLOCKING gates (present to user, wait for confirmation)
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- All self-verification checklists
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- All save actions
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- All escalation rules
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5. When the skill's workflow is fully complete:
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- Update state file: mark step as `completed`, record date, write one-line key outcome
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- Add any key decisions made during this step to the `Key Decisions` section
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- Return to the auto-chain rules
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Do NOT modify, skip, or abbreviate any part of the sub-skill's workflow. The autopilot is a sequencer, not an optimizer.
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## Re-Entry Protocol
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When the user invokes `/autopilot` and work already exists:
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1. Read `_docs/_autopilot_state.md`
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2. Cross-check against `_docs/` folder structure
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3. Present Status Summary with context from state file (key decisions, last session, blockers)
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4. If the detected step has a sub-skill with built-in resumability (plan, decompose, implement, deploy all do), the sub-skill handles mid-step recovery
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5. Continue execution from detected state
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## Error Handling
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| Situation | Action |
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|-----------|--------|
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| State detection is ambiguous (artifacts suggest two different steps) | Present findings to user, ask which step to execute |
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| Sub-skill fails or hits an unrecoverable blocker | Report the error, suggest the user fix it manually, then re-invoke `/autopilot` |
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| User wants to skip a step | Warn about downstream dependencies, proceed if user confirms |
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| User wants to go back to a previous step | Warn that re-running may overwrite artifacts, proceed if user confirms |
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| User asks "where am I?" without wanting to continue | Show Status Summary only, do not start execution |
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## Trigger Conditions
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This skill activates when the user wants to:
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- Start a new project from scratch
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- Continue an in-progress project
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- Check project status
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- Let the AI guide them through the full workflow
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**Keywords**: "autopilot", "auto", "start", "continue", "what's next", "where am I", "project status"
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**Differentiation**:
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- User wants only research → use `/research` directly
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- User wants only planning → use `/plan` directly
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- User wants the full guided workflow → use `/autopilot`
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## Methodology Quick Reference
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```
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┌────────────────────────────────────────────────────────────────┐
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│ Autopilot (Auto-Chain Orchestrator) │
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├────────────────────────────────────────────────────────────────┤
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│ EVERY INVOCATION: │
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│ 1. State Detection (scan _docs/) │
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│ 2. Status Summary (show progress) │
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│ 3. Execute current skill │
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│ 4. Auto-chain to next skill (loop) │
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│ │
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│ WORKFLOW: │
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│ Step 0 Problem → .cursor/skills/problem/SKILL.md │
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│ ↓ auto-chain │
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│ Step 1 Research → .cursor/skills/research/SKILL.md │
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│ ↓ auto-chain (ask: another round?) │
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│ Step 2 Plan → .cursor/skills/plan/SKILL.md │
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│ ↓ auto-chain │
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│ Step 3 Decompose → .cursor/skills/decompose/SKILL.md │
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│ ↓ SESSION BOUNDARY (suggest new conversation) │
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│ Step 4 Implement → .cursor/skills/implement/SKILL.md │
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│ ↓ auto-chain │
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│ Step 5 Deploy → .cursor/skills/deploy/SKILL.md │
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│ ↓ │
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│ DONE │
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│ │
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│ STATE FILE: _docs/_autopilot_state.md │
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│ FALLBACK: _docs/ folder structure scan │
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│ PAUSE POINTS: sub-skill BLOCKING gates only │
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│ SESSION BREAK: after Decompose (before Implement) │
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├────────────────────────────────────────────────────────────────┤
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│ Principles: Auto-chain · State to file · Rich re-entry │
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│ Delegate don't duplicate · Pause at decisions only │
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└────────────────────────────────────────────────────────────────┘
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```
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