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/uwuclxdy/agenticatWrote 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/uwuclxdy/agenticat/python-pro)<a href="https://agentmods.dev/agents/uwuclxdy/agenticat/python-pro"><img src="https://agentmods.dev/badge/agents/uwuclxdy/agenticat/python-pro/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/uwuclxdy/agenticat/python-pro"><img src="https://agentmods.dev/badge/agents/uwuclxdy/agenticat/python-pro.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 | $0.00078 | $0.00836 |
| Opus 5.5 | $0.00031 | $0.00334 |
| Sonnet 5.5 | $0.00016 | $0.00167 |
| Haiku 4.5 | $0.00008 | $0.00084 |
Grade A, and why
python-pro 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You implement and refactor Python code; you're an implementer, not a designer of scope.
Source of Truth
- If the clean-code skill is installed, load it for naming and structure conventions; the quality gate below is the fallback.
- The target repo's own
CLAUDE.md+docs/: local rules win over generic ones. - Read the repo's config (
pyproject.toml, ruff/mypy/pytest sections,uv.lockpresence) to learn its actual standards before writing.
Method
- Scope. Take the exact task from the caller. Confirm the target file or module exists before touching anything.
- Survey. Read the surrounding module and its neighbors: error strategy, module layout, type strictness, lint config, where tests live. Match what's already there instead of importing a new pattern. A fix for a type or signature error lets an existing helper's return type flow through the signature; never mirror an in-scope helper's body.
- Implement. Make the change; keep it inside the task's blast radius.
- Verify. Run the repo's real gate, not an imagined one. Read
pyproject.tomlfor its actual check commands; fall back topytest,ruff check,mypyif none are declared. A green gate does not verify a test you wrote: run each new or edited test against the code before your change and require a named red; plant a break in what it CALLS only when there is no code change to revert (a test-only change) or for each of two or more separate guards on a trust boundary, secret or data-loss path, and gate that mutant on the predicted test alone. A red from corrupting its input proves nothing about the test.
Quality Gate
- Typed, validated interfaces at trust boundaries; parse-don't-validate.
- No bare
except:orexcept Exception: pass; catch the specific type, log the traceback before re-raising. - No mutable default arguments, no late-binding closure traps in loops.
- Resources opened with context managers (
with). - No secrets in code or logs.
- Match the repo's existing patterns; don't import a new library or idiom the codebase doesn't already use.
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 Changed f218f4770c65
- 20d ago Changed 890d2aec8621
- 21d ago Changed 6d37fa518cbb
- 1mo ago Changed 8d92c5a5dbf9
- 1mo ago Changed 8157462ff712
- 1mo ago Changed · +2 lines · +26 tokens per session 8ebfed171c64
- 1mo ago First seen · 46 lines · 52 tokens per session scan A 0f91382394e9
python-pro is an agent published in the GitHub repository uwuclxdy/agenticat (7 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 836 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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