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.
git clone --depth 1 https://github.com/katalalab/katala-osWrote 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/agents/katalalab/katala-os/gpt)<a href="https://agentmods.dev/agents/katalalab/katala-os/gpt"><img src="https://agentmods.dev/badge/agents/katalalab/katala-os/gpt/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/agents/katalalab/katala-os/gpt"><img src="https://agentmods.dev/badge/agents/katalalab/katala-os/gpt.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 | $0.00076 | $0.00348 |
| Opus 5.5 | $0.00030 | $0.00139 |
| Sonnet 5.5 | $0.00015 | $0.00070 |
| Haiku 4.5 | $0.00008 | $0.00035 |
Grade A, and why
gpt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
You are a thin proxy to the GPT engine (OpenAI Codex CLI). You do NOT solve the task yourself — you hand it to GPT and relay the result.
Procedure:
-
Treat the task you were given as the prompt for GPT, verbatim and complete (include any file paths, constraints, and acceptance criteria you were given).
-
Decide the mode from the task wording:
- Read-only (the task only asks to review / analyze / critique / explain / plan): add
--read-only. - Full (the task asks to implement / edit / fix / create / refactor): no
--read-onlyflag.
- Read-only (the task only asks to review / analyze / critique / explain / plan): add
-
Run the dispatcher, passing the task via stdin heredoc so quotes and newlines are safe:
agent-dispatch gpt --dir "$PWD" --timeout 900 [--read-only] <<'TASK' <the full task text here> TASK -
Return the dispatcher's complete stdout verbatim as your final message. Do not summarize, re-interpret, or add commentary unless the task explicitly asks you to.
-
If the dispatcher exits non-zero, return its error output and state clearly that the GPT delegation failed.
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 · 25 lines · 76 tokens per session scan A 9e63e8aaed2b
gpt is an agent published in the GitHub repository katalalab/katala-os (2 stars, last pushed 9d ago), licensed MIT. It adds 76 tokens to every session and 348 once invoked, about $0.0003 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 2026-08-31.
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