agentsclimarketplace

Autopilot

Skill momentmaker/kaijutsu/skills/core/autopilot

Write your dev workflow once. Run it on any LLM. Open agent skills + multi-model swarm + a local findings store that learns which models you can trust.

Install
npx -y skills add momentmaker/kaijutsu --skill autopilot

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  • 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Intent-to-PR pipeline. Describe an outcome in natural language and the system runs the full development pipeline autonomously — brainstorm, spec, plan, build, ship — with multi-agent adversarial review at every artifact stage. Two gates total (post-brainstorm + PR review on GitHub). Cost-capped. Use when the user says "autopilot", "build this end to end", "take this from idea to PR", or invokes /autopilot {intent}.

SKILL.md

9.0 KB, as published. Nobody here has run it

autopilot v2 — Intent → PR pipeline

Take a natural-language intent and run the full development pipeline to a polished PR. Two gates total: brainstorm approval (Gate 1) + PR review on GitHub (Gate 2 — the existing PR semantics). Multi-agent adversarial review replaces the single-reviewer model from v1.

NOTE: kaijutsu-managed. Re-running jutsu install autopilot overwrites this file. The previous v1 SKILL.md (if any) is preserved at ~/.claude/skills/autopilot/.archived/SKILL.md.

Command Detection

  • /autopilot {intent}Run mode (start new pipeline)
  • /autopilot resumeResume mode (continue interrupted run)
  • /autopilot abortAbort mode (clean up + stop)
  • /autopilot statusStatus mode (show current phase)

CLI equivalents: jutsu autopilot {init,status,abort,resume,run}. Use the slash command for interactive runs; the cobra group is for scripted use + CI test mode.

Phase Map

/autopilot {intent}
  → Phase 1: BRAINSTORM (interactive — anti-sycophancy via jutsu swarm dream)
  → ★ GATE 1 (configurable: skip | review) ★
  → Phase 2: SPEC
      → write spec to docs/specs/<date>-<slug>.md
      → swarm doc-review on spec [report-only]
      → record approved-spec path in state file
  → Phase 3: PLAN
      → write plan to IMPLEMENTATION_PLAN.md
      → swarm doc-review on plan [report-only]
  → Phase 4: BUILD (stage 1..N — each followed by polish loop)
  → Phase 5: SHIP
      → final swarm pr-review (full lens)
      → reverse-drift gate (informational, tagged on PR)
      → gh pr create  (or test-mode: write planned PR JSON)
  → ★ GATE 2 = PR review on GitHub ★
  → Phase 6: LEARN (state file, findings.db, MEMORY.md)

Cost Cap

Three layers (per spec Decision #3):

  1. Soft cap — config default $20 (overridable via .kaijutsu/autopilot.yaml::cost.max_total_usd); at 50% of soft cap, autopilot pauses + asks user to confirm continue.
  2. Hard ceilingMaxAutopilotCostUSD = $100 constant in cli/internal/cli/autopilot.go. Cannot be raised by editing yaml. Per-run override via --max-cost N works only up to ceiling.
  3. Per-shell ceiling override — set KAIJUTSU_AUTOPILOT_HARD_CAP_OVERRIDE=N in your shell environment to raise the ceiling for THIS shell. Not stored in repo. Defense against malicious yaml.

Above the ceiling without env var → error. Pre-flight jutsu swarm <preset> --estimate projection runs at Gate 1 before any model dispatch.

Phases (detailed)

Phase 1: BRAINSTORM (interactive)

Interactive conversation with the user about the intent. Anti-sycophancy enabled by default: invoke jutsu swarm dream --mode full --strict --personas brainstorm-creative-claude,architecture-purist-antigravity,claim-auditor-claude against the leading direction. User sees the design ALREADY ARGUED AGAINST before approving Gate 1.

Step 1: Read project context (parallel):

  • CLAUDE.md (project rules + constraints)
  • ~/.claude/projects/*/memory/MEMORY.md matching this project
  • .claude/decisions/*.md with status: active
  • git log --oneline -20
  • Past autopilot runs from memory (entries named autopilot-run-*)

Step 2: Scan for related code — grep + skill-suggest:

  • jutsu suggest "<intent>" to see if installed skills already handle sub-problems
  • Grep the codebase for keywords from the intent

Step 3: Anti-sycophancy dream pass (when autopilot.yaml gates.brainstorm: review):

  • Run jutsu swarm dream --mode full against the leading design
  • Surface load-bearing findings + anti-skill arguments to the user

Step 4: GATE 1 — present design to user with the dream findings already attached:

## Autopilot: Direction Review

**Intent:** "{original intent}"
**Leading approach:** {1-paragraph summary}
**Why this approach:** {2-3 sentences}
**Dream's adversarial findings:** {top 3 load-bearing concerns}
**Estimated cost (pre-flight):** ${X}

Approve, revise, or reject?

Wait for user response. Approve → Phase 2. Revise → re-explore. Reject → abort.

Phase 2: SPEC

Step 1: Write spec to docs/specs/<date>-<slug>.md following the brainstorming spec format.

Step 2: Run jutsu swarm doc-review --personas architecture-purist-antigravity,paranoid-security-claude,claim-auditor-claude <spec-path>.

Step 3: Findings printed to stderr inline + appended to <workspace>/findings.md. Findings are report-only (per spec Decision #2). Autopilot does NOT mutate the spec automatically. User can apply specific findings via re-run after editing.

Step 4: Record approved spec path in .kaijutsu/autopilot-state.md (approved_spec_path key) for the reverse-drift gate to consume.

Phase 3: PLAN

Step 1: Write IMPLEMENTATION_PLAN.md following the writing-plans skill format — bite-sized stages with exact file paths + test commands.

Step 2: Run jutsu swarm doc-review --personas perf-purist-codex,claim-auditor-claude,cross-file-antigravity <plan-path>.

Step 3: Findings report-only (same as spec).

Phase 4: BUILD

For each stage in the plan:

  1. Implement the stage — fresh subagent dispatched per task per the subagent-driven-development protocol.
  2. Polish loop — invoke /polish skill against the stage's diff. Up to 4 review-fix passes per stage. If findings remain after 4, escalate to user.
  3. Run tests — project's test command must pass before moving to next stage.
  4. Commit — descriptive message linking to the spec + plan.

Track cost across all stages. Pause at 50% of soft cap; abort at hard ceiling without override.

Phase 5: SHIP

Step 1: Final swarm pr-review (full lens) — jutsu swarm pr-review --diff-from-branch main --strict --personas paranoid-security-claude,architecture-purist-antigravity,perf-purist-codex,claim-auditor-claude --mode full. Apply load-bearing findings; defensible-skip the rest.

Step 2: Reverse-drift gatejutsu swarm reverse --spec <state.approved_spec_path> --diff origin/main...HEAD. Drift findings appended to PR description as <details> block. PR labeled autopilot-drift if drift surfaced.

Step 3: Open PRgh pr create with synthesized body. In test mode (KAIJUTSU_AUTOPILOT_TEST_MODE=1), writes planned PR to .kaijutsu/autopilot-pr.json instead.

Phase 6: LEARN

After PR open (or abort):

  1. Write run summary to ~/.claude/projects/<project>/memory/autopilot-run-<date>-<slug>.md.
  2. Findings recorded into ~/.kaijutsu/findings.db (existing v0.7 schema). Each autopilot run adds rows so per-agent confidence weights tune the next run.
  3. Update MEMORY.md if a lesson is broadly applicable.

State File

Path: .kaijutsu/autopilot-state.md. YAML frontmatter, no body.

---
intent: "<original intent>"
phase: brainstorm | spec | plan | build | ship | learn | done
slug: <feature-slug>
approved_spec_path: docs/specs/<date>-<slug>.md
plan_path: IMPLEMENTATION_PLAN.md
branch: feat/<slug>
pr: <url-or-empty>
started_at: <ISO timestamp>
gate_responses: { brainstorm: approve | revise | reject }
cost_so_far_usd: <running total>
---

State file enables resume + status + abort to work after session interruption.

Findings Application Path

Per spec Decision #2: doc-review findings are report-only. Never mutate the artifact silently.

  • Findings printed to stderr inline during the swarm run.
  • Same findings written to <workspace>/findings.md.
  • User reviews findings; if changes are wanted, user edits the spec/plan directly OR re-runs autopilot after editing.
  • Autopilot continues to next phase without applying findings unless severity is blocker (per findings.escalate_threshold config) — in which case autopilot pauses + asks user how to proceed.

This preserves the reviewer/generator boundary that dream finding #4 surfaced.

Skill References

See references/:

  • config-schema.md — full .kaijutsu/autopilot.yaml reference
  • cost-model.md — soft cap + hard ceiling + env override
  • persona-defaults.md — which personas run at which phase + how to override

See runbooks/:

  • abort-and-resume.md — state file format + resume protocol
  • drift-detection.md — reverse-drift gate behavior + interpretation

Hard Rules

  • Two gates only. Brainstorm approval + PR review on GitHub. No mid-flight gates by default.
  • Findings are report-only. Never auto-apply.
  • Cost ceiling is non-negotiable. Hard ceiling lives in skill code, not yaml.
  • Reverse-drift is informational, not blocking. Drift surfaces on the PR; user decides.
  • Replace, don't extend. v1 autopilot at ~/.claude/skills/autopilot/.archived/SKILL.md (preserved on install).

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