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SKILL verified MIT Self-run

Python Libraries

skill-owenlamont-agent-skills-python-libraries · by owenlamont

Reach for this project's preferred, well-supported libraries instead of hand-rolling. Use when choosing a library for HTTP, retries, JSON, or parsing, or whenever you are about to write something the standard library or a maintained package already does.

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Install

$ agentstack add skill-owenlamont-agent-skills-python-libraries

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

Python Libraries

Prefer well-supported libraries (and the standard library) over hand-rolled code — it is less to maintain and less to get wrong than reinventing a solved problem.

Don't reinvent the wheel

  • Don't hand-roll retry or backoff loops — use stamina (it wraps tenacity with sane

defaults: capped attempts, jitter, and retrying only the exceptions you name). Set a timeout and exclude non-retryable errors, such as a 4xx that won't change on retry.

  • Don't reimplement what itertools (stdlib) or more-itertools already provide

(grouping, chaining, windowing, accumulating) — reach for them instead. See python-code-style for the broader "prefer stdlib idioms" rule.

  • Don't parse HTML or XML with regex — use parsel (XPath and CSS selectors).

HTTP

  • Use an HTTP client with async support — this rules out requests and urllib.
  • Match the async client the repo already uses rather than introducing a second one, and

don't add another HTTP client as a (dev) dependency without a concrete reason.

  • Set an explicit timeout on outbound requests; a single client-level default is fine,

but never rely on the library default, which is often None (waits forever).

JSON

  • Use orjson over the standard library json for serialising and deserialising — it is

faster and better-behaved.

  • When a Pydantic model is involved, go straight to and from JSON bytes with

Model.model_validate_json(raw) and model.model_dump_json() — one fast parse-and-validate pass.

  • Don't call an HTTP response's .json() and hand the resulting dict to Pydantic: that

parses twice (the client builds a dict, then Pydantic re-validates it). Pass the raw bytes (response.content) to Model.model_validate_json(...) instead.

See python-async for deploying on uvloop, and python-datetime for dates and times.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.