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ax-rust-playbook

Use when writing Rust code with `axllm` for the playbook() context-engineering surface, agent-bound verified evolution, run-end learning, online updates, and rendering a playbook into a program.

63

Quality

79%

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tessl review fix ./website/static/rust/.well-known/agent-skills/ax-rust-playbook/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%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.

An admirably lean, fact-dense reference card with real API call shapes and useful guardrails, but its follow-through fails: every referenced artifact (API.md, axir-api.json, axir-capabilities.json, examples/) is missing from the bundle, the Core Pattern snippet is not self-contained, and the evolve/rollback workflow — explicitly flagged as risky — has no validation checkpoints. Conciseness is excellent; actionability and workflow structure are where the skill falls short.

Suggestions

Ship the referenced bundle files (API.md, axir-api.json, axir-capabilities.json, examples/) or inline the minimal call shapes they would provide — every reference in 'Package Facts' and the guardrails currently points to a file that does not exist.

Make the Core Pattern snippet compile as written: define or comment out the placeholders ('llm', 'examples', 'metric_fn') and include the imports and json! macro.

Add an explicit numbered workflow for the evolve cycle with verification and exact-rollback checkpoints, since the skill itself flags this as a risky operation.

DimensionReasoningScore

Conciseness

The body is lean fact-lists, one compact code snippet, and terse guardrails — every line adds package-specific information Claude could not know, with zero padding or explanation of known concepts. This matches the anchor 'Lean and efficient; assumes Claude's competence; every token earns its place', and there is nothing to trim that would justify a 4.

5 / 5

Actionability

The Core Pattern shows real, concrete call shapes ('axllm::ax("question:string -> answer:string")', 'axllm::playbook(program, student, None::<Rc<RefCell<OpenAICompatibleClient>>>, json!({}))', 'pb.evolve(&examples, &mut metric_fn, &json!({}))') plus specific guardrails, fitting 'Mostly executable guidance; concrete code or commands with minor gaps'. It is not 5 because the snippet is not copy-paste ready ('llm', 'examples', 'metric_fn' are undefined; imports and the json! macro are not shown) and the 'examples/' and 'API.md' it directs the agent to are absent from the bundle; it is not 3 because the guidance is genuine executable Rust with real API shapes, not pseudocode.

4 / 5

Workflow Clarity

The Core Pattern implies a sequence (build program → construct playbook → evolve), but there is no explicit step sequence and no validation checkpoints — even though the body itself names risky operations ('mine grounded weaknesses with verification and exact rollback'). This matches 'Steps listed but validation gaps; sequence present but checkpoints missing or implicit'. It is not 4 because verification/rollback checkpoints are never spelled out as steps, and not 2 because a rough, coherent sequence is present.

3 / 5

Progressive Disclosure

Sections are well organized and references are clearly signaled ('Package API docs: `API.md` and `axir-api.json`', 'Runnable examples: `examples/`'), but none of the referenced files exist in the bundle — navigation dead-ends at every pointer. This fits 'Some structure but could be better organized; references present but...' broken navigation. It is not 4 because the referenced paths dangle, and not 2 because the body itself is well structured rather than a monolithic wall with buried references.

3 / 5

Total

15

/

20

Passed

Description

78%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, trigger-first description with an explicit 'Use when' clause, several enumerated capabilities, and a highly distinctive niche. Its main weakness is jargon-heavy phrasing ('context-engineering surface', 'run-end learning') that blunts both plain-action specificity and natural trigger-term matching, and it merges what and when into one clause instead of stating both explicitly.

Suggestions

Rewrite the action phrases in plain language (e.g., 'Build, evolve, and refine a context playbook for `axllm` Rust programs; render it into a program context') to reduce jargon like 'context-engineering surface'.

Add natural synonyms users might say (e.g., 'optimize prompts', 'playbook evolution', 'few-shot optimization') to broaden trigger matching.

Split the single dense clause into separate what and when sentences so both answers read explicitly.

DimensionReasoningScore

Specificity

The description names several concrete actions — 'playbook() context-engineering surface', 'agent-bound verified evolution', 'run-end learning', 'online updates', and 'rendering a playbook into a program' — matching the anchor 'Lists several specific actions; minor gaps in coverage'. It is not 5 because phrases like 'context-engineering surface' lean on package jargon rather than plain concrete actions, and it is not 3 because multiple specific actions are enumerated, not just one or two.

4 / 5

Completeness

It has an explicit trigger clause ('Use when writing Rust code with `axllm` for...') and the what (the enumerated capabilities) is stated, fitting 'Has both what and when; when could be more explicit or specific'. It is not 5 because what and when are fused into a single dense clause rather than clearly separated, and the trigger situations are not phrased as concrete user-side events (e.g., 'when the user mentions...').

4 / 5

Trigger Term Quality

Natural terms a user would say are present: 'writing Rust code', 'axllm', 'playbook', 'online updates' — matching 'Good keyword coverage; a few natural terms missing'. It is not 5 because there are no synonyms or variations of key terms, and phrases like 'agent-bound verified evolution' and 'run-end learning' are internal jargon users would not naturally say.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche — Rust code with the generated `axllm` package and its playbook/optimizer APIs — with distinct triggers ('axllm', 'playbook', 'Rust') and minimal conflict risk with other skills, matching the top anchor.

5 / 5

Total

17

/

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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