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 agentmods add skills/amirkiarafiei/subagent-cli-skills/codex-clinpx skills add amirkiarafiei/subagent-cli-skills --skill codex-cligit clone --depth 1 https://github.com/amirkiarafiei/subagent-cli-skillsWrote 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/amirkiarafiei/subagent-cli-skills/codex-cli)<a href="https://agentmods.dev/skills/amirkiarafiei/subagent-cli-skills/codex-cli"><img src="https://agentmods.dev/badge/skills/amirkiarafiei/subagent-cli-skills/codex-cli.svg" alt="Measured on agentmods" 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 | $0.00079 | $0.01825 |
| Opus 5 | $0.00039 | $0.00912 |
| Sonnet 5 | $0.00016 | $0.00365 |
| Haiku 4.5 | $0.00008 | $0.00183 |
Grade A, and why
codex-cli 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 4d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenAI Codex CLI (subagent/task delegation)
Use OpenAI Codex CLI to run a separate long-horizon pass over the repo: multi-step implementation, broad refactors, batch file writes, or deep exploration—similar to handing a task to a subagent. You stay orchestrator: smaller prompts, less context burn, often lower spend than doing the same work entirely in-session.
Codex CLI (powered by the latest GPT-5 architectures) excels at high-level reasoning, multi-turn autonomous problem solving, and native environment interaction.
When to use Codex CLI
- Large or multi-step work: several files, phases, or checkpoints (feature slice, migration, test suite, docs sweep).
- Heavy code generation or editing: Codex drives
--full-autotool use while you summarize outcomes and merge. - Reasoning-heavy tasks: Successor to the o-series; use when PhD-level logic and native "Thinking" modes are required.
- Parallel mental lane: you continue planning or reviewing while Codex runs a bounded task (optionally background—see reference.md).
- User explicitly asks for Codex or “use Codex for this.”
When not to use
- Small / single-step tasks answerable with one or two edits or a short explanation.
- Tight feedback loops where the user wants rapid back-and-forth refinement in one thread.
- Secrets or policy-sensitive flows—avoid piping credentials; redact before delegating.
- Already-loaded context where duplicating the whole plan adds no value—handle locally.
- Low ROI (Return on Investment): If the task is "needle-in-a-haystack" (requires high precision over a single line) or if the time to compose the Handoff Table exceeds the time to simply edit the file locally. Delegation should only be used when the "mental offloading" outweighs the "handoff overhead."
Delegation and context (critical)
Isolated subagent context saves tokens but splits the story: Codex does not see the main session's full thread. Poor handoffs cause misread subtasks, conflicting assumptions (stack, style, APIs), and wasted edits—see Cognition’s discussion of sharing context and implicit decisions in multi-step setups.
What ships with it
1 file 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.
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.
- 4d ago First seen · 110 lines · 79 tokens per session scan A c2cbd595027d
codex-cli is a skill published in the GitHub repository amirkiarafiei/subagent-cli-skills (5 stars, last pushed 22d ago), licensed MIT. It adds 79 tokens to every session and 1,825 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
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brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…