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ax-python-signature

Use when writing Python code with `axllm` for string signatures, field descriptors, JSON schema output, validation, and typed tool argument shapes.

64

Quality

81%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

63%Weight 40%Scale 1-5

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

The body provides lean, executable patterns for the core signature API and concrete guardrails, but the dense Typesafe/Jev prose section reads like inline reference documentation (naming variants, probability tolerances, C++/TypeScript asides) that should be trimmed or split out, and the referenced files cannot be found in the skill bundle.

Suggestions

Trim the Typesafe/Jev section: drop off-target language comparisons ('C++ uses valueDescriptions...', 'only TypeScript can infer literal question keys'), consolidate each triple naming variant into one canonical form, and keep only the essential policy facts.

Split the Typesafe/Jev details into a separate reference file (e.g. references/typesafe.md) and keep a short summary with a clear pointer in SKILL.md so the main body stays an overview.

Either ship the referenced files (API.md, axir-api.json, axir-capabilities.json, examples/) in the skill bundle or remove references that cannot be resolved from the skill directory.

DimensionReasoningScore

Conciseness

The code-pattern sections are lean, but the 'Typesafe / Jev' section is dense prose that could be tightened: it lists triple naming variants repeatedly ("trueThreshold (or true_threshold)", "system_one / systemOne / SystemOne", "describe_values / describeValues / DescribeValues", "list_models / listModels / ListModels") and includes off-target facts such as "C++ uses valueDescriptions on its existing field descriptors" and TypeScript-only inference details in a Python skill. The over-explanation is more than minor, matching anchor 3 rather than anchor 4.

3 / 5

Actionability

Mostly executable, copy-paste-ready code covers the common cases: `s("question:string -> answer:string")`, `sig.to_json_schema("outputs")`, the fluent `f()` builder chain, and the `ax(...)` string/class forms. Minor gaps keep it below anchor 5: `program.forward(client, inputs)` references undefined `client`/`inputs`, and the substantial Typesafe/Jev section (trueThreshold, `boolean(...)`, `list_models`) has no code examples at all.

4 / 5

Workflow Clarity

The body progresses clearly from Core Pattern to advanced patterns to API surface, and Guardrails supply checkpoints such as "Start from package examples for exact native syntax before inventing a new call shape" and "if package docs disagree with source code, update the compiler and regenerate packages". It falls short of anchor 5 because no verification step is given after writing code, but the sequence and checkpoints are mostly present.

4 / 5

Progressive Disclosure

Section headers are clear, but the body references bundle files that do not exist alongside it (no `references/`, `scripts/`, or `assets/` directories; `API.md`, `axir-api.json`, `axir-capabilities.json`, and `examples/` are absent), and the ~17-line Typesafe/Jev reference-style detail is inlined rather than split into a separate file. This matches anchor 3: some structure, references present but not verifiable, and content that should be separate is inline.

3 / 5

Total

14

/

20

Passed

Description

92%Weight 40%Scale 1-5

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 description: it explicitly answers both what (signatures, field descriptors, JSON schema output, validation, typed tool arguments) and when (writing Python code with axllm), with a distinctive package-scoped trigger. The only minor weakness is trigger-term coverage, which lacks synonyms beyond one form of each term.

DimensionReasoningScore

Specificity

The description lists five concrete capability areas — "string signatures, field descriptors, JSON schema output, validation, and typed tool argument shapes" — giving comprehensive, specific coverage of the package's surface. It matches anchor 5 (multiple specific concrete actions, comprehensive coverage) rather than anchor 4, which would imply notable gaps.

5 / 5

Completeness

The clause "Use when writing Python code with `axllm`" explicitly and concretely answers 'when' (both language and package name), while the trailing list explicitly answers 'what'. Both are explicit with concrete trigger phrases, matching anchor 5; it is not anchor 4 because the 'when' is as specific as it can be for this domain.

5 / 5

Trigger Term Quality

Natural terms users of this package would say are present: "Python code", "axllm", "string signatures", "JSON schema output", "validation". It falls short of anchor 5 because synonyms and variations are missing (e.g. "contracts", "prompts", "input/output fields", "schemas"), though it clearly exceeds anchor 3's 'some relevant keywords' bar.

4 / 5

Distinctiveness Conflict Risk

The description is scoped by the package name `axllm` and niche terms like "string signatures" and "typed tool argument shapes", forming a clear niche with minimal overlap risk against generic Python skills. This matches anchor 5.

5 / 5

Total

19

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20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
ax-llm/ax
Reviewed

Table of Contents

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