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Use when deciding whether a question warrants spawning a Codex turn or you can answer locally — covers the cost/value matrix and which subagent or command is the right entry point for each kind of consultation.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use when running an active autopilot-codex session — explains the plan→implement→review→verdict cycle, state machine, and termination conditions. Required reading when status='running' and the implementer needs to act inside the loop.
Use when interpreting state mutations during plan/review/verdict transitions — explains exactly which fields the bridge writes when, so the implementer can debug 'why is current_task suddenly T3' or 'why is base_sha old'.
Use whenever you're about to run a destructive Bash command, push code, or spend Codex tokens — explains every cap and denylist this plugin enforces and how to extend them.
Use whenever the user invokes /autopilot-codex:* in this repo, OR mentions "autopilot", "Codex manager", "Codex architect", or asks Codex to plan/review for them. Establishes the role split — OpenAI Codex is manager/architect, Claude Code is implementer — and the operating contract.
| name | consulting-codex |
| description | Use when deciding whether a question warrants spawning a Codex turn or you can answer locally — covers the cost/value matrix and which subagent or command is the right entry point for each kind of consultation. |
| effort | high |
| allowed-tools | Bash(autopilot-codex:*), Read |
Every Codex turn costs tokens. Per the May 2026 rate card, a single
gpt-5.4 call on autopilot averages 25–40k input + 5–10k output =
$0.10–$0.30. Multiply by 30 iterations and a runaway loop is real money.
This skill is the cost/value matrix for deciding "do I ask Codex, or do
I just answer the user".
current_task, plan,
last_review, last_verdict are local. Use /codex-status or
/codex-next first.approve and you want to "double-check", don't. The verdict is the
contract.| Kind of question | Entry point |
|---|---|
| "Decompose this engineering goal into tasks." | codex-manager subagent → mcp__autopilot-bridge__plan |
| "Does this diff meet the current task's acceptance contract?" | codex-reviewer subagent → mcp__autopilot-bridge__review |
| "Is the goal achieved? If not, what next?" | Stop hook (automatic) → mcp__autopilot-bridge__verdict |
| "Should I use library X or Y for this?" (one-shot architectural) | codex-planner subagent (haiku, no state mutation) |
| "Re-plan from scratch — original plan exhausted but goal not met." | /codex-plan <revised goal> |
Codex's prompts (in lib/prompts.mjs) embed:
That's already enough for most calls. Don't add to the prompt unless you're sure — extra context is extra tokens, and Codex's role-specific prompts are tuned to deny shell / MCP / file I/O. Adding hints can break that framing.
gpt-5.4 (default) for plan / review / verdict. gpt-5.5 is
twice the price for marginal quality on these structured tasks.gpt-5.4-mini or haiku for codex-planner one-shot questions
— they're $0.50/$2 per 1M tokens; an architectural opinion costs
pennies.--budget USD on /autopilot to cap a session. The
budget-guard.mjs check hook flips status to stopped_budget once
spend ≥ cap. See safety-rails skill.The bridge prompts explicitly forbid Codex from:
Codex's only output is the structured JSON for plan / review / verdict.
If a Codex response includes shell commands or "I'll just run X" — that's
prompt drift; the bridge's validateXxxShape will reject the output and
the autopilot will surface a clean error to the user.
The bridge does not use codex-reply or --resume. Each call
spawns a fresh codex exec process. Continuity is achieved by embedding
state.json in the prompt — Codex sees the running plan, last_review,
last_verdict, recent commits in every prompt. This trades token cost
for reproducibility: every turn is replayable from the prompt log.