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SKILL verified MIT Self-run

Python Foundational

skill-microsoft-hve-core-python-foundational · by microsoft

Foundational Python best practices, idioms, and code quality fundamentals

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Install

$ agentstack add skill-microsoft-hve-core-python-foundational

✓ 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 No
  • Filesystem access Used
  • 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 →

Verified badge

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
1mo ago

Declared compatibility

Claude CodeClaude Desktop

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

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About

Python Foundational Coding Standards Skill

Overview

Foundational Python excellence that every diff must satisfy. This skill is loaded first for any .py change. All higher-order skills build on it.

This content is a skill rather than an instructions file for three reasons: skills are distributed through the CLI plugin and VS Code extension without requiring consumers to copy files into their repo; new language skills can be added without modifying the review agent itself; and skills are loaded on demand, keeping the context window small when the diff contains no Python.

Core Checklist

1. Readability & Style
  • Use Python naming: PascalCase classes, snake_case functions/variables, UPPER_SNAKE_CASE constants, _ private members.
  • Group imports: stdlib → third-party → local (blank line between groups, no trailing whitespace).
2. Pythonic Idioms
  • Prefer comprehensions for simple transforms; use explicit loops for complex logic/side-effects.
  • Always use with for files, locks, DB connections.
  • Prefer dataclass / NamedTuple / Enum for data holders.
  • Use pathlib over os.path; timezone-aware datetime when relevant.
  • Use * keyword-only arguments for multi-optional functions.
  • Never use mutable defaults or global/nonlocal unless strictly required.
3. Function & Class Design
  • Keep functions small and single-responsibility.
  • Add docstrings to all public APIs (follow repo style).
  • Document unavoidable side-effects.
  • Follow codebase’s class-member ordering (if defined).
4. Type Safety Foundations
  • Add type hints to all public APIs, module vars, and class attributes.
  • Use PEP 695 (3.12+) or TypeVar for generics.
  • Avoid Any except in thin wrappers.
5. Error Handling
  • Raise specific exceptions; never bare except: (broad except Exception: only at app boundaries with logging).
  • No silent failures or generic error messages.
  • Provide context, expected state, and guidance in every exception.
6. Anti-Patterns to Avoid
  • Never use eval, exec, or pickle on untrusted data.
  • Never hard-code secrets.
7. Maintainability
  • Prefer self-documenting code; comments only for "why".
  • Use structured logging instead of print.
  • Flag overly long/complex functions that resist testing.
8. Architectural Fit
  • Align with existing patterns; do not re-implement shared functionality or bypass established layers.
  • Place code in the correct module/package.
9. Design Principles
  • Eliminate duplication: extract repeated logic into a shared helper so fixes propagate automatically.
  • Prefer the simplest implementation that satisfies current requirements. Introduce abstractions only when a second concrete use case appears.
  • Limit change breadth: every modified line should trace to the stated purpose of the change.
  • Before flagging seemingly unused code, verify it is not a protocol implementation, framework hook, public API, or entry point invoked externally.
  • Match solution complexity to problem complexity. A duplicated function warrants a shared helper, not an event-driven architecture.

References

| File | Covers | Purpose | |-------------------------------------------------------------|--------------|-----------------------------------------------------------------------------------------| | [design-principles.md](references/design-principles.md) | Section 9 | Rationale and examples for the design principles | | [code-style-patterns.md](references/code-style-patterns.md) | Sections 1–5 | Concrete code examples for style, idioms, type safety, class design, and error handling |

Severity Rubric

| Severity | Definition | |----------|----------------------------------------------------------------------------------------------------------| | High | Causes incorrect behavior, data loss, or security exposure at runtime | | Medium | Degrades maintainability, readability, or violates a project convention with no immediate runtime impact | | Low | Cosmetic, stylistic, or minor improvement opportunity |

Troubleshooting

| Symptom | Check | |------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Skill not loaded | Confirm the diff contains .py files. The agent selects skills by matching file types in the changed files against skill descriptions. | | No findings generated | Verify the Skills Loaded footer in the review output lists python-foundational. If listed but no findings appear, the diff may already satisfy the checklist. | | Severity seems miscalibrated | Compare against the Severity Rubric above. High requires runtime impact; medium is maintainability-only. |

Contributing

Follow these conventions when extending this skill:

  • Checklist items belong in SKILL.md. Each bullet is a single, actionable check an agent or reviewer can apply to a diff. Keep bullets concise: one sentence, no code.
  • Reference files live in references/ and provide examples or rationale for the covered checklist items. Each reference file covers a contiguous range of sections. Update the References table when adding a new file.
  • Before adding a new checklist item, confirm it does not duplicate an existing bullet in any section. Place it in the section that matches its primary concern. If it spans concerns, prefer the more specific section.
  • Name new reference files after the topic they cover (e.g., async-patterns.md). Include a frontmatter description that states which sections the file supports. Add a row to the References table in SKILL.md.
  • Checklist items and examples must be portable across codebases. Use generic module names and describe anti-patterns by their behavior, not by specific directory or file names.

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.