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ax-java-ai

Use when writing Java code with `dev.axllm:ax` for provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers.

70

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

72%

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

A token-efficient, well-organized API-usage skill with a concrete core snippet and clear routing decision guidance. It is weakest on actionability and workflow clarity, where the routing/balancing and guardrail guidance stays descriptive rather than showing complete executable setup steps with validation.

Suggestions

Add one complete executable example for adaptive balancer setup (route creation, stats store, sampling) so the Routing section moves beyond descriptive rules.

Provide a short numbered workflow for choosing and wiring a routing strategy with an explicit verification checkpoint (e.g., confirm the route key is unique and non-empty before use).

Include a minimal runnable no-key example snippet in the body so the 'scripted transports' guidance has a copy-paste starting point.

DimensionReasoningScore

Conciseness

Lean bullet-based body with no padding or explanations of concepts Claude already knows; every section (Package Facts, Routing, API Surface, Guardrails) earns its tokens.

3 / 3

Actionability

Includes one executable Core Pattern snippet and a concrete API-surface list, but the Routing/Balancing and Guardrails sections are descriptive rules with no complete executable examples for setup or store/reducer syntax.

2 / 3

Workflow Clarity

Decision guidance ('Use ... when') and a loose 'Start with ... then use ...' sequence exist, but there is no numbered multi-step workflow with explicit validation checkpoints for routing/store setup.

2 / 3

Progressive Disclosure

Well under 50 lines, organized into clear labeled sections, with external artifacts (API.md, axir-api.json, examples/) clearly signaled one level deep in Package Facts rather than inlined.

3 / 3

Total

10

/

12

Passed

Description

100%

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 concise, third-person description with an explicit 'Use when' trigger and a specific list of concrete capabilities tied to a named package. It answers both what and when clearly and is highly distinctive.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities — 'provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers' — rather than vague language.

3 / 3

Completeness

Explicitly states both what it does (provider clients, model selection, call types, routers, balancers) and when to use it via the 'Use when writing Java code with dev.axllm:ax' trigger clause.

3 / 3

Trigger Term Quality

'Use when writing Java code' plus provider names (OpenAI, Gemini, Anthropic) and 'routers and balancers' are natural terms users would say for this domain.

3 / 3

Distinctiveness Conflict Risk

The specific package 'dev.axllm:ax' and enumerated provider/routing capabilities carve a clear niche unlikely to trigger for unrelated skills.

3 / 3

Total

12

/

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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