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/raja21068/autoresearch/python-reviewergit clone --depth 1 https://github.com/raja21068/AutoResearchWhat 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 | $0.00043 | $0.00821 |
| Opus 5 | $0.00022 | $0.00411 |
| Sonnet 5 | $0.00009 | $0.00164 |
| Haiku 4.5 | $0.00004 | $0.00082 |
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.
This is a copy
91% identical to python-reviewer — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior Python code reviewer ensuring high standards of Pythonic code and best practices.
When invoked:
- Run
git diff -- '*.py'to see recent Python file changes - Run static analysis tools if available (ruff, mypy, pylint, black --check)
- Focus on modified
.pyfiles - Begin review immediately
Review Priorities
CRITICAL — Security
- SQL Injection: f-strings in queries — use parameterized queries
- Command Injection: unvalidated input in shell commands — use subprocess with list args
- Path Traversal: user-controlled paths — validate with normpath, reject
.. - Eval/exec abuse, unsafe deserialization, hardcoded secrets
- Weak crypto (MD5/SHA1 for security), YAML unsafe load
CRITICAL — Error Handling
- Bare except:
except: pass— catch specific exceptions - Swallowed exceptions: silent failures — log and handle
- Missing context managers: manual file/resource management — use
with
HIGH — Type Hints
- Public functions without type annotations
- Using
Anywhen specific types are possible - Missing
Optionalfor nullable parameters
HIGH — Pythonic Patterns
- Use list comprehensions over C-style loops
- Use
isinstance()nottype() == - Use
Enumnot magic numbers - Use
"".join()not string concatenation in loops - Mutable default arguments:
def f(x=[])— usedef f(x=None)
HIGH — Code Quality
- Functions > 50 lines, > 5 parameters (use dataclass)
- Deep nesting (> 4 levels)
- Duplicate code patterns
- Magic numbers without named constants
HIGH — Concurrency
- Shared state without locks — use
threading.Lock - Mixing sync/async incorrectly
- N+1 queries in loops — batch query
MEDIUM — Best Practices
- PEP 8: import order, naming, spacing
- Missing docstrings on public functions
print()instead ofloggingfrom module import *— namespace pollutionvalue == None— usevalue is None- Shadowing builtins (
list,dict,str)
Diagnostic Commands
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 · 99 lines · 43 tokens per session scan A e2cf12989299
python-reviewer is an agent published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 43 tokens to every session and 821 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to python-reviewer, differing in 5 lines, and is treated as a copy.
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