ax-rust-refine

Use when writing Rust code with `axllm` for reward-scored generation, iterative candidate improvement, evaluator feedback, and optimizer-backed refinement patterns.

Quality

64%

Does it follow best practices?

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tessl review fix ./website/static/rust/.well-known/agent-skills/ax-rust-refine/SKILL.md

Quality

Content

57%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.

A compact, well-sectioned reference skill with real API symbols and a concrete core snippet. Its main weaknesses are incomplete executable detail in the code example and references to bundle files that are not actually present.

Suggestions

Make the core snippet self-contained by showing how reflection_client, options, request, and evaluator are constructed, or clearly label it as a pattern to adapt.

Add a brief feedback loop for the refinement workflow (optimize → inspect evaluator feedback → adjust → re-run) to improve workflow clarity.

Either provide the referenced `API.md`, `axir-api.json`, `axir-capabilities.json`, and `examples/` bundle files, or remove the references so navigation is not broken.

Dimension	Reasoning	Score
Conciseness	Lean bullet-based body with a short code snippet and minimal over-explanation ("Use the generated package API, examples, and manifests"), matching anchor 4; not 5 because the intro line restates the description and "When To Use" slightly overlaps the opening.	4 / 5
Actionability	Provides a concrete `AxGEPA::new(...).optimize(...)` snippet and a real API-surface list, but the snippet uses undefined inputs (reflection_client, options, request, evaluator) and several guardrails are abstract ("Treat AxIR as the source of generated package truth"), matching anchor 3.	3 / 5
Workflow Clarity	Only an implicit loose sequence (examples → API → guardrails) with no explicit checkpoints or feedback loops, matching anchor 3; not 4 because no validation steps are present even though the skill involves iterative refinement where they would help.	3 / 5
Progressive Disclosure	Well-organized section headers suit a short skill, but the body references `API.md`, `axir-api.json`, `axir-capabilities.json`, and `examples/` that do not exist in the bundle, so references are signaled but not verifiable, matching anchor 3.	3 / 5
	Total	13 / 20 Passed

Description

71%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 specific, well-triggered description with a clear "Use when..." clause and distinct niche. It would score higher with more natural user-facing trigger phrasing and slightly more concrete action verbs.

Suggestions

Add natural synonyms a user would actually say (e.g., "improve", "refine", "iterate on" Rust/LLM outputs) alongside the technical terms.

Broaden the "when" clause beyond a single package to cover the underlying intent (refining or improving generated outputs) to reduce reliance on the `axllm` keyword.

Dimension	Reasoning	Score
Specificity	Names the domain (Rust + `axllm`) and lists several concrete actions — "reward-scored generation", "iterative candidate improvement", "evaluator feedback", "optimizer-backed refinement patterns" — with only minor coverage gaps, matching anchor 4 rather than 5 since the actions are abstract pattern names rather than fully concrete operations.	4 / 5
Completeness	Explicitly answers both what (refinement patterns for Rust axllm) and when ("Use when writing Rust code with `axllm`"), satisfying the no-cap rule; not a 5 because the "when" is narrow and tied to a single package rather than a range of trigger scenarios.	4 / 5
Trigger Term Quality	Includes a natural "Use when writing Rust code" trigger and package keyword `axllm`, but leans on jargon ("reward-scored", "optimizer-backed") and misses common user phrasings like "improve/refine my LLM outputs", matching anchor 3 rather than 4.	3 / 5
Distinctiveness Conflict Risk	Highly specific niche (Rust + the `axllm` package + refinement/optimizer patterns) with distinct triggers and minimal overlap with other skills, matching anchor 5.	5 / 5
	Total	16 / 20 Passed

Validation

93%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: ax-llm/ax
Path: website/static/rust/.well-known/agent-skills/ax-rust-refine/SKILL.md
Commit: 1abea97

Reviewed: ~19 hours ago

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