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/rishapgandhi/python-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/rules/rishapgandhi/python-skills/python-security)<a href="https://agentmods.dev/rules/rishapgandhi/python-skills/python-security"><img src="https://agentmods.dev/badge/rules/rishapgandhi/python-skills/python-security/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/rules/rishapgandhi/python-skills/python-security"><img src="https://agentmods.dev/badge/rules/rishapgandhi/python-skills/python-security.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 | $0.00149 | $0.00149 |
| Opus 5.5 | $0.00060 | $0.00060 |
| Sonnet 5.5 | $0.00030 | $0.00030 |
| Haiku 4.5 | $0.00015 | $0.00015 |
Grade A, and why
python-security 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.
What it actually says
Security Rules
- All secrets via pydantic-settings from environment — never in source
- All API endpoints authenticated unless explicitly marked public
- Input validation via Pydantic schemas on all endpoints
- SQL injection prevention: ORM only, parameterised queries if raw SQL
- Never log sensitive data (passwords, tokens, PII)
- Use
Field(repr=False)for sensitive settings fields - CORS configured explicitly — never
allow_origins=["*"]in production - Rate limiting on auth endpoints
Reference: skills/common/security.md, skills/common/api-auth.md
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 · 19 lines · 149 tokens per session scan A 80d9ecb3bc2a
python-security is a cursor rule published in the GitHub repository rishapgandhi/python-skills (4 stars, last pushed 5mo ago), licensed MIT. It adds 149 tokens to every session, about $0.0006 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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