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ax-python-agent-context

Use when writing Python code with `axllm` for deciding between context maps, trajectory context policy, offline optimization (ACE/GEPA), and memory recall for long-context agents.

70

Quality

86%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

87%

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

A concise, actionable, well-organized skill body with a real code pattern and explicit reference pointers; its only gap is the absence of a sequenced, validated workflow for routing among the four features.

Suggestions

Add a short decision sequence for choosing among contextMap, contextPolicy, optimization, and recall (e.g., a 3-step 'identify task type -> match feature -> verify against examples' flow) with a validation checkpoint.

Format the referenced materials (API.md, examples/) as explicit navigational pointers (e.g., 'See API.md for full method reference') to strengthen progressive-disclosure signaling.

DimensionReasoningScore

Conciseness

The body is lean — terse Package Facts bullets, a minimal code pattern, and short Guardrails — with no padding or explanation of concepts Claude already knows, matching the 'every token earns its place' anchor.

3 / 3

Actionability

It provides a concrete executable Core Pattern snippet plus a specific Relevant API Surface listing real symbols (agent, AxAgent, optimize, AxGEPA, etc.) and actionable guardrails, fitting the 'fully executable code/commands; specific examples' anchor.

3 / 3

Workflow Clarity

The When To Use section gives routing guidance across four features but presents no sequenced workflow or validation checkpoints for the multi-feature selection, matching the 'steps listed but validation gaps / checkpoints missing' anchor; the simple-skill exception does not apply since this is a multi-path selection skill.

2 / 3

Progressive Disclosure

At under 50 lines the body is organized into clear, well-labeled sections and signals one-level-deep reference materials (API.md, axir-api.json, axir-capabilities.json, examples/), matching the well-organized compact-skill anchor.

3 / 3

Total

11

/

12

Passed

Description

85%

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 specific, well-triggered description with an explicit 'Use when' clause and a distinct niche; its main weakness is trigger terms that skew toward internal jargon over natural user phrasing.

Suggestions

Add more natural user-level phrasings alongside the technical terms (e.g., 'long-context LLM agents', 'context window management') so non-expert users land on this skill.

Consider shortening the parenthetical '(ACE/GEPA)' or pairing it with a plain-language gloss to broaden trigger coverage.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete capabilities — "context maps, trajectory context policy, offline optimization (ACE/GEPA), and memory recall" — rather than vague language, matching the anchor that lists several specific actions.

3 / 3

Completeness

It explicitly answers what (writing Python code with axllm for the listed capabilities) and when (leading "Use when writing Python code with axllm for..."), satisfying the both-what-and-when anchor with an explicit trigger.

3 / 3

Trigger Term Quality

It includes relevant domain terms ("context maps", "optimization", "GEPA", "memory recall", "long-context agents") a practitioner would say, but leans technical and misses common user-level phrasings/variations, fitting the 'some relevant keywords but missing common variations' anchor.

2 / 3

Distinctiveness Conflict Risk

The axllm-specific, long-context-agent niche with distinct feature triggers is unlikely to overlap with unrelated skills, matching the clear-niche anchor.

3 / 3

Total

11

/

12

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.

Validation15 / 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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