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/ondrasek/cc-plugins/python-auditnpx skills add ondrasek/cc-plugins --skill python-auditgit clone --depth 1 https://github.com/ondrasek/cc-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 | $0.00054 | $0.00373 |
| Opus 5 | $0.00027 | $0.00187 |
| Sonnet 5 | $0.00011 | $0.00075 |
| Haiku 4.5 | $0.00005 | $0.00037 |
Grade A, and why
python-audit 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 yesterday.
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
Python Audit
Read-only — does not modify any files.
Context Files
Read these files before starting:
skills/shared/references/audit-workflow.md— the 5-step workflow structureskills/python-setup/references/methodology.md— the 9 quality dimensions (roles) to audit againstskills/python-setup/references/analysis-checklist.md— what to check in the target codebase
Workflow
Follow audit-workflow.md. Python-specific details:
1. Analyze Current State
Detect package manager, Python version, project structure, frameworks. Inventory existing tool configurations in pyproject.toml, standalone config files. Check hooks, CI.
2. Compare Against Methodology
Check each of the 9 dimensions — see methodology.md for Python-specific tools and thresholds.
3. Check Hook Coverage
Expected hooks: SessionStart (deptry), PostToolUse/Edit|Write (ruff + format), Stop (quality gate), PostToolUse/Bash (semver check).
4. Check CI Coverage
Expected jobs: test, lint, typecheck, security, deadcode, version.
5. Report
Present dimension/hook/CI coverage tables with recommendations. Suggest running /blueprint:python-setup to configure missing dimensions.
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.
- yesterday First seen · 44 lines · 54 tokens per session scan A 25957afe676a
python-audit is a skill published in the GitHub repository ondrasek/cc-plugins (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 54 tokens to every session and 373 once invoked, about $0.0003 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.
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