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 commands/galaxyproject/claude-galaxy-plugins/py-review-code-structuregit clone --depth 1 https://github.com/galaxyproject/claude-galaxy-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/galaxyproject/claude-galaxy-plugins/py-review-code-structure)<a href="https://agentmods.dev/commands/galaxyproject/claude-galaxy-plugins/py-review-code-structure"><img src="https://agentmods.dev/badge/commands/galaxyproject/claude-galaxy-plugins/py-review-code-structure.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00373 |
| Opus 5 | $0.00000 | $0.00187 |
| Sonnet 5 | $0.00000 | $0.00075 |
| Haiku 4.5 | $0.00000 | $0.00037 |
Grade A, and why
py-review-code-structure 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 3d 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
Perform a Python code review on the provided code. Accept input in any of following forms:
- A working directory path (analyze git diff in that directory)
- A Git commit reference (analyze changes in that commit)
- A list of Python file paths (analyze those files)
- A planning document (analyze the Python files in the plan)
Review the code focusing on these two criteria:
1. Type Annotations
- Methods and functions should have type annotations on parameters and return types
- Don't over-type: basic operations and obvious cases don't need extensive annotations
- Flag missing annotations on public methods and functions with non-obvious signatures
- Local helper functions and simple internal methods may not need annotations if context is clear
- Annotate complex parameter types (dicts, lists of objects, unions)
2. Import Organization
- All imports must be at the top of the file (after module docstring if present)
- Inline imports (imports appearing mid-file) should be moved to the top UNLESS they have an inline comment explaining why (e.g., # circular import, # lazy load, # conditional)
- Flag any inline imports without explanation and move them to the top
- Don't reorganize import groups - isort handles that
Output Format: For each file reviewed, provide:
- File: filename
- Typing Issues: List missing or problematic type annotations (or "None" if clear)
- Import Issues: List inline imports found and moved (or "None" if correct)
- Summary: Brief assessment of the file's adherence to standards
At the end, provide:
- Overall Assessment: How many files pass review / total files
- Key Recommendations: Top 3-5 items to address across all files
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.
- 3d ago First seen · 32 lines · 0 tokens per session scan A 3cba66660e5b
py-review-code-structure is a command published in the GitHub repository galaxyproject/claude-galaxy-plugins (4 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 373 tokens. 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.
Other commands, from other repositories
git
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checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.