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ax-rust-agent-memory-skills

Use when writing Rust code with `axllm` for agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking.

67

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

76%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 is a lean, well-structured capability reference that assumes competence and points to package docs for detail. Its main gaps are the lack of an explicit validated workflow and only a minimal inline code example.

Suggestions

Add a short numbered workflow (e.g., seed constructor skills -> forward with memories/overrides -> observe loaded/used -> export_runtime_state) with an explicit validation checkpoint so workflow_clarity can rise above 3.

Include one or two more executable Rust snippets covering the common cases (catalog-only search, observer registration) instead of describing them only in prose.

Move the detailed Lifecycle And State behavioral rules into API.md or a dedicated reference file, keeping SKILL.md as a tighter overview, to strengthen progressive disclosure.

DimensionReasoningScore

Conciseness

The body is dense and information-rich with no padding or explanation of concepts Claude already knows; every bullet conveys non-obvious package behavior that earns its place in context.

5 / 5

Actionability

A copy-paste-ready Core Pattern snippet and concrete API symbol names are provided, but only one small inline code example is shown and advanced behaviors are described in prose rather than executable code.

4 / 5

Workflow Clarity

The Lifecycle And State section implies a sequence (constructor seed -> forward override -> observers -> state snapshot) but no explicit numbered workflow or validation checkpoints are given.

3 / 5

Progressive Disclosure

Clear sectioned overview points to package docs (API.md, axir-api.json, examples/) with one-level-deep references, but the dense Lifecycle section inlines reference detail that could live in API.md.

4 / 5

Total

16

/

20

Passed

Description

87%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.

This is a strong, niche-scoped description that pairs an explicit 'Use when' trigger with five concrete capability areas. The only weakness is that capabilities are listed as nouns rather than verb-actions and lack synonyms.

DimensionReasoningScore

Specificity

The description lists several concrete capabilities ('agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking') rather than vague language, but these are capability nouns rather than verb-actions, leaving minor gaps versus the comprehensive anchor.

4 / 5

Completeness

It explicitly answers both 'what' (the five listed capability areas) and 'when' with a concrete 'Use when writing Rust code with axllm' trigger clause.

5 / 5

Trigger Term Quality

Natural phrases a developer would say appear ('writing Rust code', 'axllm', 'agent memory', 'skill discovery'), giving good keyword coverage, but no synonyms or file-extension variants are included.

4 / 5

Distinctiveness Conflict Risk

It targets a narrow niche (Rust code with the generated axllm package for agent memory/skills) with distinct triggers, so conflict with other skills is minimal.

5 / 5

Total

18

/

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.

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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