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 skills/casper-studios/casper-marketplace/python-best-practicesnpx skills add Casper-Studios/casper-marketplace --skill python-best-practicesgit clone --depth 1 https://github.com/Casper-Studios/casper-marketplaceWrote 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/skills/casper-studios/casper-marketplace/python-best-practices)<a href="https://agentmods.dev/skills/casper-studios/casper-marketplace/python-best-practices"><img src="https://agentmods.dev/badge/skills/casper-studios/casper-marketplace/python-best-practices.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.00645 |
| Opus 5 | $0.00034 | $0.00322 |
| Sonnet 5 | $0.00014 | $0.00129 |
| Haiku 4.5 | $0.00007 | $0.00064 |
Grade A, and why
python-best-practices 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 4d 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 — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Best Practices
This skill applies modern Python mechanisms without adding annotation or packaging ceremony. It favors inference, precise structural contracts, explicit runtime validation, side-effect-free imports, and context-managed resource ownership.
References
Read as many linked references as are relevant to the current task before writing or reviewing Python.
- Let the checker infer obvious implementation results; add annotations only when inference cannot express the contract.
- Parse serialized input once at the controlled boundary so untrusted mappings do not spread inward.
- Depend on the smallest required behavior with protocols, not a vendor's concrete client.
- In Python 3.13+, express caller-relevant relationships with PEP 695 generics, avoiding module-level
TypeVardeclarations and needless generics. - Make a new finite-state member a type-checking failure with exhaustive handling.
- Narrow optional values before use so the owning layer—not a cast or fabricated fallback—decides whether absence is preserved or rejected.
- Do not turn missing required data into a plausible value; preserve absence or fail at the owning boundary.
- Keep required runtime checks active under optimization; do not use assertions for validation.
- Catch only expected exceptions at the operation that raises them through narrow exception handling.
- Keep imports inert and consumer-facing names deliberate with explicit public exports.
- Prevent checkout-dependent imports by following the Python naming and
srclayout. - Publish intentional inline types with
py.typed, reserving third-party stubs for dependencies that lack complete inline types instead of adding markers merely to silence diagnostics. - Make async cleanup inseparable from acquisition with async context managers.
- Preserve page boundaries and consumer control over remote traversal through async pagination.
- Give every independently buildable distribution its own declared metadata and direct dependencies.
- Make packaging errors visible by not mutating import paths.
What ships with it
18 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 187 B
- LICENSE.txt 16 KB
- references/async-context-managers.md 1.1 KB
- references/async-pagination.md 1.3 KB
- references/boundary-validation.md 767 B
- references/exception-handling.md 899 B
- references/finite-state-exhaustiveness.md 968 B
- references/inference-and-annotations.md 1.2 KB
- references/naming-and-src-layout.md 679 B
- references/no-fabricated-defaults.md 644 B
- references/no-import-path-mutation.md 718 B
- references/no-runtime-asserts.md 675 B
- references/optional-narrowing.md 795 B
- references/pep-695-generics.md 557 B
- references/project-metadata.md 652 B
- references/protocols.md 992 B
- references/public-exports.md 743 B
- references/py-typed-and-stubs.md 646 B
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.
- 4d ago First seen · 34 lines · 69 tokens per session scan A c5eed759200e
python-best-practices is a skill published in the GitHub repository Casper-Studios/casper-marketplace (12 stars, last pushed 17d ago), licensed MPL-2.0. It adds 69 tokens to every session and 645 once invoked, about $0.0003 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 2026-08-30.
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