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/d-padmanabhan/agent-engineering-handbookWrote 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/d-padmanabhan/agent-engineering-handbook/python)<a href="https://agentmods.dev/commands/d-padmanabhan/agent-engineering-handbook/python"><img src="https://agentmods.dev/badge/commands/d-padmanabhan/agent-engineering-handbook/python/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/commands/d-padmanabhan/agent-engineering-handbook/python"><img src="https://agentmods.dev/badge/commands/d-padmanabhan/agent-engineering-handbook/python.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 | $0.00013 | $0.00384 |
| Opus 5.5 | $0.00005 | $0.00154 |
| Sonnet 5.5 | $0.00003 | $0.00077 |
| Haiku 4.5 | $0.00001 | $0.00038 |
Grade A, and why
python 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.
What it actually says
PYTHON MODE ACTIVATED
You are now in PYTHON MODE. Any work on Python code MUST follow:
rules/200-python.mdc(opinionated Python guidance)rules/100-core.mdc(minimal, production-ready changes)rules/310-security.mdc(no secrets, OWASP-minded)
Use this command when the user asks to:
- Create new Python modules/functions/classes
- Modify existing Python code
- Review Python code for correctness/security/performance
Guardrails (mandatory)
- Prefer stdlib over new dependencies unless explicitly justified.
- Validate inputs and fail fast with clear errors.
- Don’t log secrets (mask sensitive fields).
- Keep changes minimal; don’t refactor unrelated code.
Step 0: Determine intent (create vs modify vs review)
Infer intent from the user’s request. If ambiguous, ask ≤3 clarifying questions (runtime version, interface expectations, performance constraints).
Create
Produce complete, runnable code with:
- Type hints
- Clear docstrings where appropriate
- Error handling for expected failures
Modify
- Preserve existing behavior unless requested otherwise
- Prefer minimal diffs
- Add tests only if requested (or if needed to prevent regression)
Review
Prioritize:
- Critical: injection risks, insecure subprocess usage, secret leakage, broken authz, unsafe deserialization
- Recommended: performance hot spots, poor error handling, observability gaps
- Optional: style and small readability tweaks
Verification (as applicable):
pre-commit run --all-files
Done condition
End with:
- Files changed (or “no changes made”)
- How to validate (tests/lint/type-check) and expected behavior
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 · 64 lines · 13 tokens per session scan A 2610a43ad5ee
python is a command published in the GitHub repository d-padmanabhan/agent-engineering-handbook (19 stars, last pushed 2d ago), licensed MIT. It adds 13 tokens to every session and 384 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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