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pythonic-code

Write, refactor, and review Python for clarity, explicit behavior, local reasoning, strong types, and minimal abstraction. Use when creating or changing nontrivial Python, simplifying object-heavy or helper-heavy code, evaluating whether code is Pythonic, or reviewing Python maintainability in Basic Memory repositories.

70

Quality

85%

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, highly actionable instruction skill with clear sequenced workflows and an explicit verification gate. Its sole weakness is conciseness: the volume of abstract heuristic prose could be tightened without losing clarity.

DimensionReasoningScore

Conciseness

The body is directive and free of basic-concept padding, but at ~105 lines it carries substantial abstract heuristic prose (e.g., 'Prefer the form with the fewest concepts, hidden rules, and call hops') that could be tightened, so it is mostly efficient rather than lean with every token earning its place.

2 / 3

Actionability

As an instruction-only skill it gives concrete, specific guidance — 'Use dataclasses for internal values and Pydantic at validation and serialization boundaries', 'Use functools.singledispatch only when...', 'Distinguish absence from falsiness' — naming exact constructs and tools rather than vague direction.

3 / 3

Workflow Clarity

Clear ordered workflows appear in 'Orient Before Coding', 'Make Decisions In This Order', and 'Verify The Result' with an explicit validation gate ('Run the narrowest command that proves the change, then widen according to risk') and a closing instruction to lead with the outcome and verification.

3 / 3

Progressive Disclosure

Content is well-organized into focused sections with no nested or multi-level references; the only referenced paths (AGENTS.md, docs/ENGINEERING_STYLE.md, docs/DOMAIN_MODEL.md) are one-level project files to read, not skill bundle hops, and no bundle files exist to split.

3 / 3

Total

11

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12

Passed

Description

85%Weight 40%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description with explicit what-and-when triggers and a clear Pythonic niche. Its only weakness is trigger phrasing that leans on internal jargon ('object-heavy', 'helper-heavy') instead of natural user language.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Write, refactor, and review Python' plus 'simplifying object-heavy or helper-heavy code' — matching the anchor for several specific concrete actions rather than a single named action.

3 / 3

Completeness

Explicitly states what it does ('Write, refactor, and review Python for clarity, explicit behavior...') and when to use it ('Use when creating or changing nontrivial Python...'), satisfying both halves with an explicit 'Use when' trigger clause.

3 / 3

Trigger Term Quality

Natural terms like 'refactor', 'review', and 'Pythonic' appear, but qualifiers such as 'object-heavy or helper-heavy code', 'nontrivial Python', and 'minimal abstraction' are jargon rather than language users naturally say, and plain variations like 'clean up' or 'readable Python' are missing.

2 / 3

Distinctiveness Conflict Risk

The Python-specific, Pythonic-clarity niche with distinct triggers is unlikely to fire for non-Python or non-maintainability skills, despite the odd 'Basic Memory repositories' scope qualifier.

3 / 3

Total

11

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
basicmachines-co/basic-memory
Reviewed

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