Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tubecreate/tubecli --skill codexgit clone --depth 1 https://github.com/tubecreate/tubecliWrote 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/tubecreate/tubecli/codex)<a href="https://agentmods.dev/skills/tubecreate/tubecli/codex"><img src="https://agentmods.dev/badge/skills/tubecreate/tubecli/codex/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/tubecreate/tubecli/codex"><img src="https://agentmods.dev/badge/skills/tubecreate/tubecli/codex.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.01590 |
| Opus 5.5 | $0.00012 | $0.00636 |
| Sonnet 5.5 | $0.00006 | $0.00318 |
| Haiku 4.5 | $0.00003 | $0.00159 |
Grade A, and why
Codex 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🎛 Codex — work control panel
Codex is where ALL work that truly needs doing lives. Any request that runs long, is resource-heavy (LLM, browser, download/upload), changes data or the outside world, or needs someone to review the result → do NOT do it inline; create a Codex task and report the task number to the user. Only answer directly when the question is a quick lookup/explanation that produces no change.
🛑 Approval rules (MANDATORY)
- Tasks created by the AI are ALWAYS in
pending_approvalstate and wait for human approval. The AI must not approve its own tasks. - After creating a task, NEVER say the work has run/finished. Only say: created
#<n>, awaiting approval, and instruct the user to typeapprove <n>. - Lifecycle:
pending_approval → queued → running → review → done(+failedcan be retried,rejected,cancelled).
⚠️ FLAT PAYLOAD rule (MANDATORY)
The action parser can only read JSON that is one level deep, all scalar values (string/number/bool). Do NOT use nested objects, do NOT use arrays in an action.
To split a large job into smaller ones → emit MULTIPLE consecutive codex_create_task actions, one goal per action. Never pack a list of subtasks into a single action.
📥 codex_create_task — create a new task
{"action": "codex_create_task", "goal": "Full description of what needs to be done", "title": "Short title", "assignee_type": "agent", "assignee": "Agent name or team name", "skill": "Skill name (optional)", "priority": 0}
goal(required) — a self-contained description; the worker reads only this string.assignee_type:"agent"or"team".assigneetakes a NAME (matching an existing agent/team name), no ID needed.priority: the higher the number, the sooner it runs (default 0).
📥 codex_list_tasks — view the list
{"action": "codex_list_tasks", "status": "active"}
status: active (default) | pending_approval | queued | running | review | done | failed | rejected | cancelled.
What ships with it
24 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- __init__.py 184 B runs code
- commands.py 4.6 KB runs code
- executor.py 15 KB runs code
- extension.py 5.1 KB runs code
- locales/en.json 30 KB
- locales/es.json 32 KB
- locales/ja.json 36 KB
- locales/ko.json 33 KB
- locales/ru.json 41 KB
- locales/tr.json 32 KB
- locales/vi.json 34 KB
- locales/zh-TW.json 30 KB
- locales/zh.json 30 KB
- manager.py 80 KB runs code
- pipelines.py 6.5 KB runs code
- routes.py 22 KB runs code
- static/codex.css 47 KB
- static/codex.html 40 KB
- static/codex.js 170 KB runs code
- static/live.css 16 KB
- static/live.html 1.3 KB
- static/live.js 39 KB runs code
- telegram.py 15 KB runs code
- worker.py 5.5 KB runs code
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.
- 1mo ago First seen · 108 lines · 29 tokens per session scan A db1f05a93bc3
Codex is a skill published in the GitHub repository tubecreate/tubecli (174 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,590 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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