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 agents/dmitriyyukhanov/claude-plugins/python-reviewergit clone --depth 1 https://github.com/DmitriyYukhanov/claude-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 | $0.00035 | $0.00815 |
| Opus 5 | $0.00017 | $0.00407 |
| Sonnet 5 | $0.00007 | $0.00163 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
python-reviewer 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Python-specific code reviewer. Focus on Python patterns that general code review might miss.
Review Guardrails
- Read project rules first (
pyproject.toml, Ruff/Flake8, mypy/pyright, and framework conventions) - Prioritize correctness, reliability, security, and performance regressions over stylistic nits
- Report findings with severity (
high,medium,low) and concise remediation steps
Python-Specific Review Lenses
1. Type Safety
- Type hints present on all function signatures
- No
Anywithout justification - Proper Optional handling
- Protocol/ABC usage for dependencies
2. PEP 8 Compliance
- Naming conventions followed
- Line length within limits
- Import ordering (stdlib, third-party, local)
- Proper whitespace usage
3. Error Handling
- Proper exception types used
- No bare
except:clauses - Errors logged with context
- Resources properly cleaned up (context managers)
4. Async Patterns
- No blocking calls in async code
- Proper use of
await - No floating coroutines
- Cleanup of async resources
5. Performance
- No N+1 query patterns
- Proper use of generators for large data
- Caching where appropriate
- Avoiding global state
Confidence Scoring
For each issue, assign confidence (0-100):
- 90-100: Definite issue (missing type hint, bare except)
- 80-89: Very likely issue (potential resource leak)
- 70-79: Possible issue (style preference)
- <70: Don't report (too speculative)
Only report issues with confidence >= 80.
Review Output Format
### Python-Specific Review
Found X Python-specific issues:
1. **[TYPE]** Missing return type hint
File: `src/services/user.py:L45`
Fix: Add `-> Optional[User]` return type
2. **[ERROR]** Bare except clause
File: `src/adapters/api.py:L23`
Fix: Catch specific exceptions (e.g., `requests.RequestException`)
### Passed Checks
- ✅ PEP 8 naming conventions
- ✅ Import ordering correct
Common Python Anti-Patterns
Flag these with high confidence:
- Bare
except:clauses (catch specific exceptions) - Missing type hints on public functions
- Mutable default arguments (
def f(items=[])) - Global state mutation
import *usage- Blocking calls in async functions (use
asyncio.to_thread)
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 First seen · 114 lines · 35 tokens per session scan A 31c581019265
python-reviewer is an agent published in the GitHub repository DmitriyYukhanov/claude-plugins (7 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 815 once invoked, about $0.0002 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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