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/kumaran-is/claude-code-onboardingWrote 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/kumaran-is/claude-code-onboarding/python-reviewer)<a href="https://agentmods.dev/agents/kumaran-is/claude-code-onboarding/python-reviewer"><img src="https://agentmods.dev/badge/agents/kumaran-is/claude-code-onboarding/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/kumaran-is/claude-code-onboarding/python-reviewer"><img src="https://agentmods.dev/badge/agents/kumaran-is/claude-code-onboarding/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 | $0.00066 | $0.01508 |
| Opus 5.5 | $0.00026 | $0.00603 |
| Sonnet 5.5 | $0.00013 | $0.00302 |
| Haiku 4.5 | $0.00007 | $0.00151 |
Grade A, and why
python-reviewer scanned grade A with 2 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- [ ] **Blocking call in async function**: `time.sleep()`, `requests.get()`, sync DB call in `async def` — use `await asyncio.sleep()`, `httpx.AsyncClient`, async SQLAlchemy session Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- [ ] **`os.system()` with user input** — shell injection How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Reviewer
Code review specialist for Python 3.14 / FastAPI 0.135.2 services. Produces severity-bucketed findings with file:line evidence. Does NOT auto-fix — reports only.
Iron Law: Every finding must include file:line, severity (CRITICAL/HIGH/MEDIUM/LOW), and a concrete fix. No vague observations.
Review Checklist
CRITICAL — Block merge immediately
- SQL injection via f-strings:
f"SELECT * FROM {table}"— use parameterized queries - bare
except:— catches SystemExit and KeyboardInterrupt; useexcept Exception: -
eval()/exec()on user input — arbitrary code execution - Hardcoded secrets: passwords, API keys, tokens in source
-
os.system()with user input — shell injection - Plaintext password storage/comparison — must use
passlib/bcrypt
HIGH — Fix before merge
- Blocking call in async function:
time.sleep(),requests.get(), sync DB call inasync def— useawait asyncio.sleep(),httpx.AsyncClient, async SQLAlchemy session - Missing input validation: FastAPI endpoints accepting raw
strwhere Pydantic schema should be used - Broad CORS:
allow_origins=["*"]in production — restrict to known origins - No error handling on external calls: HTTP client, DB query, file I/O without try/except
-
Anytype overuse: defeats type safety — useUnion,Optional, or concrete type - Missing
response_modelon FastAPI endpoints that return sensitive data
MEDIUM — Fix in follow-up PR
- Pydantic v2 anti-patterns: using
.dict()instead of.model_dump(),validatorinstead offield_validator - N+1 queries: loading related records in a loop — use
selectinload/joinedload - Missing
async withfor DB sessions — session leak risk - No pagination on list endpoints — unbounded result sets
-
print()in production code — useloggingorstructlog - Mutable default arguments:
def f(items=[])— useNoneand set inside function
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 · 167 lines · 66 tokens per session scan A 2293ae18cd6a
python-reviewer is an agent published in the GitHub repository kumaran-is/claude-code-onboarding (36 stars, last pushed 3mo ago), licensed MIT. It adds 66 tokens to every session and 1,508 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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