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/Fmarzochi/EGCWrote 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/agents/fmarzochi/egc/python-reviewer)<a href="https://agentmods.dev/agents/fmarzochi/egc/python-reviewer"><img src="https://agentmods.dev/badge/agents/fmarzochi/egc/python-reviewer/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/agents/fmarzochi/egc/python-reviewer"><img src="https://agentmods.dev/badge/agents/fmarzochi/egc/python-reviewer.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 | $0.00043 | $0.00807 |
| Opus 5.5 | $0.00017 | $0.00323 |
| Sonnet 5.5 | $0.00009 | $0.00161 |
| Haiku 4.5 | $0.00004 | $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 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.
This is a copy
100% identical to python-reviewer — 36 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 — 100 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
mypy . # Type checking
ruff check . # Fast linting
black --check . # Format check
bandit -r . # Security scan
pytest --cov=app --cov-report=term-missing # Test coverage
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 · 100 lines · 43 tokens per session scan A f8137e0c2283
python-reviewer is an agent published in the GitHub repository Fmarzochi/EGC (67 stars, last pushed 2d ago), licensed Apache-2.0. It adds 43 tokens to every session and 807 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to python-reviewer, differing in 36 lines, and is treated as a copy.
Other agents, from other repositories
python-reviewer
Expert Python code reviewer specializing in PEP 8 compliance, Pythonic idioms, type hints, security, and performance. Use for all Python code changes. MUST BE USED for Python projects.
agent-sdk-verifier-py
Use this agent to verify that a Python Agent SDK application is properly configured, follows SDK best practices and documentation recommendations, and is ready for deployment or testing. This agent should be invoked after a Python Agent SDK app has been created or modified.
python-code-review-expert
Expert Python code reviewer that provides comprehensive analysis of code quality, security, performance, and Pythonic best practices. Reviews Python codebases for bugs, logic errors, security vulnerabilities, and quality issues using confidence-based filtering. Use PROACTIVELY for Python code reviews and pull request…
package-reviewer
Use this agent for comprehensive Python package audits — project structure, pyproject.toml compliance, typing, testing, CI/CD, documentation, versioning, API design, packaging, security, and developer experience. Handles both targeted file reviews and full repository audits. Examples: Context: User has a Python…
pep8-reviewer
Python style and coding-standards expert for the review-panel skill. Spawned when the diff touches .py, .pyi, or .ipynb files. Audits PEP 8 layout and naming, PEP 257 docstring content, PEP 484/585/604 typing form, and the repo's own thresholds (complexity, function length, parameter count, nesting) against the…
review-python-practices
Reviews code for Pythonic idioms, Pydantic best practices, SQLAlchemy 2.0 patterns, and async correctness. Read-only -- writes findings to output file.