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/jeffh/claude-plugins/computernpx skills add jeffh/claude-plugins --skill computergit clone --depth 1 https://github.com/jeffh/claude-pluginsWhat 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 | $0.00168 | $0.01608 |
| Opus 5 | $0.00084 | $0.00804 |
| Sonnet 5 | $0.00034 | $0.00322 |
| Haiku 4.5 | $0.00017 | $0.00161 |
Grade A, and why
computer 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 2d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Computer Use
Delegate a desktop UI task to a Codex subagent running GPT 5.6 Sol (or another GPT model the user names) with Codex's Computer Use feature. The subagent will take screenshots and drive the Mac by clicking, typing, and scrolling.
Choosing the model
The -m flag selects the model. Default to gpt-5.6-sol, but honor any specific model the user asks for:
- Use
gpt-5.6-solunless the user names a different model. - If the user specifies a model — e.g. "drive it with gpt-5.6-terra", "use the
<name>model" — pass that exact string to-minstead. Don't validate or second-guess the name; Codex will error if it's unknown. Note the model must support Computer Use; if it doesn't, the run will fail and you should report that back. - If they typed
/codex:computer --model <name> <task>(or-m <name>), strip that flag from the prompt and use<name>as the model.
Choosing the effort
Reasoning effort is set with -c model_reasoning_effort="<level>". Default to low for Computer Use — each action is a screenshot + reasoning cycle, and low effort keeps the loop fast. Honor any level the user asks for:
- Use
lowunless the user names a different level. - If the user asks in prose — e.g. "high effort" — substitute that level.
- If they typed
/codex:computer --effort <level> <task>, strip that flag from the prompt and use<level>as the effort.
The command below shows -m gpt-5.6-sol and low effort; substitute the chosen model and effort.
Before invoking — confirm intent
Computer Use has real-world side effects (sending messages, making purchases, changing settings). Before spawning the subagent:
- Confirm the task is genuinely a GUI task, not something better done via CLI or code.
- If the task could touch sensitive scopes — sending messages, transmitting personal data, deleting cloud data, submitting forms, entering passwords, installing software, changing system settings — surface that risk to the user and get explicit approval before invoking. Because the run bypasses approvals and the sandbox (see below), Codex will not stop to confirm risky steps mid-run — Claude's up-front confirmation is the only gate, so build any "don't do X without confirming" constraint into the prompt itself.
- The Codex Computer Use app must be present at
~/.codex/computer-use/Codex Computer Use.app. If it's missing, tell the user to install it via the Codex desktop app (codex app).
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.
- 2d ago First seen · 76 lines · 168 tokens per session scan A d03be2e308e9
computer is a skill published in the GitHub repository jeffh/claude-plugins (12 stars, last pushed 17d ago), licensed Apache-2.0. It adds 168 tokens to every session and 1,608 once invoked, about $0.0008 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 2026-08-30.
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