Borrowing it
Nothing to install: this file belongs to junghwaYang/oh-my-codex. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/junghwaYang/oh-my-codex/main/.codex/skills/autopilot/SKILL.mdgit clone --depth 1 https://github.com/junghwaYang/oh-my-codexWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/junghwayang/oh-my-codex/autopilot)<a href="https://agentmods.dev/skills/junghwayang/oh-my-codex/autopilot"><img src="https://agentmods.dev/badge/skills/junghwayang/oh-my-codex/autopilot/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/junghwayang/oh-my-codex/autopilot"><img src="https://agentmods.dev/badge/skills/junghwayang/oh-my-codex/autopilot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00445 |
| Opus 5.5 | $0.00000 | $0.00178 |
| Sonnet 5.5 | $0.00000 | $0.00089 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
autopilot scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Autopilot Skill
Autonomous execution mode for building features end-to-end.
When to Use
- Building new features from scratch
- Implementing complete user stories
- Complex refactoring across multiple files
- Any task that benefits from systematic planning
When NOT to Use
- Simple one-line fixes
- Quick typo corrections
- Tasks where user wants step-by-step control
- Debugging sessions (use direct interaction)
Workflow
1. UNDERSTAND
- Parse the request completely
- Identify acceptance criteria
- List unknowns and assumptions
2. PLAN
- Break into atomic tasks
- Identify file dependencies
- Estimate complexity per task
- Save plan to .codex/plans/{task-id}.md
3. EXECUTE
- Work through tasks sequentially
- Commit after each logical unit
- Log progress to .codex/sessions/
4. VERIFY
- Run tests if available
- Check against acceptance criteria
- Self-review for obvious issues
5. ITERATE
- If verification fails, fix and re-verify
- Max 3 self-fix attempts before asking user
Plan Template
# Task: {title}
## Acceptance Criteria
- [ ] {criterion 1}
- [ ] {criterion 2}
## Tasks
1. {task 1} - {file(s)} - {complexity: S/M/L}
2. {task 2} - {file(s)} - {complexity: S/M/L}
## Dependencies
- {task 2} depends on {task 1}
## Risks
- {potential issue}
Commit Message Format
{type}({scope}): {description}
- {detail 1}
- {detail 2}
[autopilot]
Types: feat, fix, refactor, docs, test, chore
Examples
Good trigger:
"autopilot: build a user authentication system with JWT"
Bad trigger (use direct instead):
"fix the typo in README"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 86 lines · 0 tokens per session scan A d6a9e3ad0ee3
autopilot is a skill published in the GitHub repository junghwaYang/oh-my-codex (5 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 445 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
autopilot compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| autopilotjunghwaYang/oh-my-codex | Skill | 5 | 8mo ago | MIT | A | 0 | Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |