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omni-models

Query available AI models across all configured providers. List models, resolve model aliases, and browse the full model catalog including provider-specific variants.

56

Quality

63%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/omni-models/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%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 an efficiently structured API catalog with executable curl examples and a clean pointer to full schemas, but as pure reference material it lacks any workflow sequence or validation checkpoints. For a reference skill this is solid, though the inlined endpoint catalog could arguably live in a separate file.

Suggestions

Replace placeholder request bodies (`-d '{}'`) with a representative example payload or a pointer to the schema for alias/test endpoints.

Add a brief note on verifying responses (e.g., expected status codes or a quick health check) so users can confirm calls succeeded.

Consider moving the bulk endpoint catalog into a reference file and keeping SKILL.md as a tighter overview pointing to it, to improve progressive disclosure.

DimensionReasoningScore

Conciseness

The body is mostly lean—one-line descriptions plus executable curl per endpoint—with only minor redundancy (repeated 'List models' headings), matching the 'efficient; minor instances that could be trimmed' anchor.

4 / 5

Actionability

Each endpoint ships a copy-paste-ready curl example with the auth header, providing mostly executable guidance; placeholder bodies like `-d '{}'` are a minor gap keeping it below 5.

4 / 5

Workflow Clarity

This is reference catalog material with no multi-step process or validation sequence, so it sits at the 'sequence/checkpoints missing' level rather than a higher anchored workflow.

3 / 5

Progressive Disclosure

Content is well organized into sections and detailed schemas are offloaded to clearly signaled one-level-deep references (docs/openapi.yaml, /api/openapi/spec), with only minor organization gaps from auto-generated headings.

4 / 5

Total

15

/

20

Passed

Description

58%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.

The description conveys concrete capabilities and a distinct niche but omits any 'when to use' trigger guidance, which caps completeness. Adding an explicit 'Use when...' clause with natural trigger phrases would raise the score.

Suggestions

Add an explicit 'Use when...' clause naming natural trigger phrases (e.g., 'Use when listing available models, looking up a model by alias, or browsing provider catalogs').

Broaden trigger terms with common synonyms users actually say, such as 'LLM models', 'model lookup', or 'which models are available'.

Tighten the action list so the named actions are clearly non-overlapping (listing vs. browsing the catalog reads as redundant).

DimensionReasoningScore

Specificity

Names three concrete actions ('List models, resolve model aliases, and browse the full model catalog') with only minor coverage gaps, matching the 'lists several specific actions' anchor rather than the more comprehensive score-5 example.

4 / 5

Completeness

A clear 'what' is stated but there is no 'Use when...' or equivalent trigger guidance, so per the judging guidelines completeness is capped at 3.

3 / 5

Trigger Term Quality

Relevant technical keywords ('AI models', 'model aliases', 'model catalog', 'providers') are present but lack common natural variations or synonyms a user might say, fitting the 'some relevant keywords but missing variations' anchor.

3 / 5

Distinctiveness Conflict Risk

The niche of querying model catalogs and resolving aliases across providers is mostly distinct with only minor overlap risk against other skills, fitting the 'mostly distinct' anchor.

4 / 5

Total

14

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
diegosouzapw/OmniRoute
Reviewed

Table of Contents

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