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using-model-endpoint

Call a configured Feynman model endpoint and interpret its response. Use when a task needs inference from a registered endpoint, remote model API, local model service, or custom connector-backed predictor.

64

Quality

75%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./skills/using-model-endpoint/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.

The body is concise and well-structured for a simple skill, with a clear workflow and appropriate escalation to sibling skills. It is held back by actionability and workflow clarity, since the steps lack executable examples and explicit validation checkpoints.

Suggestions

Add a small concrete request/response or pseudo-code snippet so the 'build a minimal request' and 'validate response shape' steps are executable.

Make the validation checkpoint explicit (e.g., 'If the response shape does not match, do not proceed; record the error as evidence and retry or escalate').

Optionally surface the endpoint identity/auth fields to confirm as a short checklist to strengthen workflow clarity.

DimensionReasoningScore

Conciseness

The body is lean, assumes Claude's competence, and contains no padding or explanation of concepts Claude already knows, matching the lean-and-efficient anchor where every token earns its place.

5 / 5

Actionability

Steps name what to do ('Build a minimal request', 'Validate response shape') but provide no executable code, command, or request-shape example, leaving concrete execution details missing per the some-concrete-guidance-but-incomplete anchor.

3 / 5

Workflow Clarity

A clear numbered sequence is present, but validation checkpoints are implicit rather than explicit ('handle model errors as evidence'), matching the steps-listed-but-implicit-checkpoints anchor.

3 / 5

Progressive Disclosure

A short, well-organized single-purpose skill under 50 lines with no need for external references, qualifying for the simple-skill exception where well-organized sections score 5.

5 / 5

Total

16

/

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.

The description cleanly answers both what and when with concrete trigger phrasing and a distinct, well-scoped niche. Its main weakness is specificity, naming only two high-level actions rather than enumerating several concrete capabilities.

Suggestions

Add one or two more concrete actions (e.g., 'parse structured predictions, surface latency and status') to lift specificity toward the multi-action anchor.

Include a lay-friendly synonym (e.g., 'model API' or 'inference service') alongside the technical connector terms to broaden natural trigger coverage.

DimensionReasoningScore

Specificity

Names the domain ('model endpoint') with two concrete actions ('Call a configured Feynman model endpoint and interpret its response') but does not enumerate several specific actions, matching the 1-2 concrete actions anchor and falling short of the multi-action anchor above.

3 / 5

Completeness

Explicitly states both what the skill does ('Call... endpoint and interpret its response') and when to use it ('Use when a task needs inference from...'), with concrete trigger phrases, matching the both-what-and-when anchor.

5 / 5

Trigger Term Quality

Provides good keyword coverage across natural variations ('registered endpoint, remote model API, local model service, or custom connector-backed predictor'), though some lay phrasings are absent, keeping it just below the comprehensive synonym anchor.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (configured Feynman endpoints with connector types) but retains minor overlap risk with general inference/API skills, so it does not reach the minimal-conflict anchor.

4 / 5

Total

16

/

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
companion-inc/feynman
Reviewed

Table of Contents

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