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ax-go-agent-optimize

Use when writing Go code with `github.com/ax-llm/ax/packages/go` for agent optimization, verified agent-playbook evolution, evaluators, judges, optimizer artifacts, BootstrapFewShot, and GEPA.

63

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./packages/go/skills/ax-go-agent-optimize/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The content is concise and well-structured with a concrete code pattern and API surface, but the core example is not fully executable and the optimization workflow lacks explicit validation checkpoints. Referenced detail files are named but not bundled.

Suggestions

Expand the Core Pattern into a complete, runnable example with imports and construction of the request and evaluator so it is copy-paste ready.

Add an explicit sequenced optimization workflow with a validation checkpoint (e.g. run evaluator → inspect failures → keep only proposals passing the verification gate → persist artifacts).

Either bundle the referenced files (API.md, axir-capabilities.json, examples/) or remove the dangling references so navigation is not broken.

DimensionReasoningScore

Conciseness

The body is lean — short factual bullets, a minimal two-line code pattern, and pointed guardrails with no padding or explanation of concepts Claude already knows, matching the lean-and-efficient anchor.

3 / 3

Actionability

It provides a concrete Core Pattern snippet and a real exported-symbol API list, but the snippet is not copy-paste runnable (missing imports and construction of request/evaluator), fitting the incomplete-but-concrete score-2 anchor.

2 / 3

Workflow Clarity

The "When To Use" bullets state intent and a guardrail hints at a verification gate, but there is no sequenced multi-step optimization workflow with explicit validate→fix→retry checkpoints, matching the steps-present-but-checkpoints-implicit anchor.

2 / 3

Progressive Disclosure

Sections are well organized, but the body references detail files (API.md, axir-api.json, axir-capabilities.json, examples/) that are not present as bundle files, so the advertised one-level-deep navigation is unfulfilled.

2 / 3

Total

9

/

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.

The description is specific, distinct, and provides an explicit "Use when" trigger paired with a clear capability list. Its main weakness is trigger-term quality: it relies on technical jargon and proper nouns rather than the natural phrases a user would say.

Suggestions

Add natural-language trigger variants a user might actually say (e.g. "optimize a Go agent", "improve agent prompts", "add evaluators") alongside the jargon terms like BootstrapFewShot and GEPA.

Lead with a plain verb phrase stating what the skill does before listing the named techniques, so the 'what' reads as an action rather than only a capability inventory.

DimensionReasoningScore

Specificity

Enumerates multiple concrete capability areas — "agent optimization", "verified agent-playbook evolution", "evaluators, judges, optimizer artifacts, BootstrapFewShot, and GEPA" — matching the multiple-specific-actions anchor rather than the partial score-2 anchor.

3 / 3

Completeness

It opens with an explicit "Use when writing Go code..." trigger and pairs it with a concrete what (the enumerated capability areas), answering both what and when as the score-3 anchor requires.

3 / 3

Trigger Term Quality

It includes some relevant keywords ("writing Go code", "agent optimization", "evaluators, judges") but leans heavily on jargon and proper nouns ("agent-playbook evolution", "BootstrapFewShot", "GEPA", a full package path), missing the natural variations a user would actually say.

2 / 3

Distinctiveness Conflict Risk

It targets a specific generated Go package and named optimizer techniques with distinct triggers, making it unlikely to fire for unrelated skills.

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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