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/mathisk2095/jko-claude-pluginsWrote 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/commands/mathisk2095/jko-claude-plugins/py-harden)<a href="https://agentmods.dev/commands/mathisk2095/jko-claude-plugins/py-harden"><img src="https://agentmods.dev/badge/commands/mathisk2095/jko-claude-plugins/py-harden/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/commands/mathisk2095/jko-claude-plugins/py-harden"><img src="https://agentmods.dev/badge/commands/mathisk2095/jko-claude-plugins/py-harden.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 | $0.00032 | $0.00478 |
| Opus 5.5 | $0.00013 | $0.00191 |
| Sonnet 5.5 | $0.00006 | $0.00096 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
py-harden 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
Systematically scan the Python backend for anti-patterns and fix every instance found. If $ARGUMENTS is provided, scan that file or directory. Otherwise scan the entire src/ directory.
First: Use the python-backend-expert skill. Read references/anti-patterns.md for the full catalog.
Process
-
Scan phase (read-only):
- Read every
.pyfile in scope - Check each file against all anti-patterns AP-01 through AP-22
- Record findings with file, line, pattern ID, and severity
- Read every
-
Report phase:
- Present all findings grouped by severity (blocking first)
- For each finding, show the problematic code and the proposed fix
- Ask user which findings to fix (or "all")
-
Fix phase:
- Apply fixes in order: blocking -> important -> nit
- After each fix, verify the file still parses (no syntax errors)
- Run any available linters/formatters
Priority Order
Fix in this order:
- blocking: AP-01 (fat controller), AP-05 (N+1), AP-07 (session leak), AP-08 (expire_on_commit), AP-09 (blocking in async), AP-11 (bare except), AP-12 (mutable default), AP-14 (global state), AP-19 (god class)
- important: AP-02 (god module), AP-03 (import spaghetti), AP-06 (naked SQLAlchemy), AP-10 (fire-forget), AP-13 (stringly config), AP-15 (star imports), AP-17 (dict return), AP-22 (exception flow control)
- nit: AP-04 (anemic service), AP-16 (missing types), AP-18 (print debug), AP-20 (premature abstraction), AP-21 (boolean params)
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 · 35 lines · 32 tokens per session scan A 72aa55401c60
py-harden is a command published in the GitHub repository mathisk2095/jko-claude-plugins (3 stars, last pushed 11d ago), licensed MIT. It adds 32 tokens to every session and 478 once invoked, about $0.0001 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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