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analyze-model

Analyze an external model URL (typically Hugging Face) to determine implementation style and estimate SD.Next porting difficulty using the port-model workflow.

58

Quality

68%

Does it follow best practices?

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SecuritybySnyk

High

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tessl review fix ./.github/skills/analyze-model/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

75%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 well-structured, lean, and actionable with a clearly sequenced procedure and at least one validation checkpoint. Its main weakness is mild redundancy between Required Outputs and Reporting Format, and the absence of worked examples.

Suggestions

Merge the overlapping 'Required Outputs' and 'Reporting Format' sections into a single output/reporting spec to remove redundancy and tighten conciseness.

Add one short worked example (e.g., the JoyAI-Image-Edit URL carried through to a classification + difficulty rating) to lift actionability and workflow clarity.

Add an explicit validation checkpoint after the difficulty-estimate step (e.g., 'confirm the estimated path exists in the SD.Next integration surface before reporting') to give later procedure steps the checkpoint step 1 already has.

DimensionReasoningScore

Conciseness

The body is lean, list-driven, and does not explain concepts Claude already knows (no 'what is a model/Diffusers' padding), with only minor redundancy between the 'Required Outputs' and 'Reporting Format' sections; not 5 because those two overlapping sections could be merged, and not 3 because the bulk is efficient rather than padded.

4 / 5

Actionability

Concrete guidance is given throughout — specific files to inspect (model_index.json, config.json), specific SD.Next touchpoints (pipelines/model_name.py, modules/sd_detect.py), and a defined Low/Medium/High/Very High difficulty scale; not 5 because it is instruction-only without worked examples covering common cases, and not 3 because the specifics are directly executable.

4 / 5

Workflow Clarity

The 7-step Procedure is explicitly ordered with one validation/feedback checkpoint (gated access: check secrets, retry with auth, abort and report on failure); not 5 because only the first step has an explicit validation checkpoint while later steps lack checkpoints, and not 3 because a clear sequence with a real checkpoint is present.

4 / 5

Progressive Disclosure

Content is well-organized into clear sections (When To Use, Accepted Inputs, Required Outputs, Classification Buckets, Procedure, Reporting Format, Notes) with one clearly signaled external reference (.github/instructions/core.instructions.md) and no nested references; not 5 because there are no bundle files and the body exceeds 50 lines with some content that could be split out, and not 3 because structure is solid and navigation is easy.

4 / 5

Total

16

/

20

Passed

Description

61%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 names a clear, distinct niche and concrete actions with good natural trigger terms, but it omits any explicit "Use when" trigger guidance, which caps completeness. Adding a trigger clause would lift the weakest dimension.

Suggestions

Add an explicit 'Use when...' clause naming the user phrasing that should invoke this skill (e.g., 'Use when a user gives a Hugging Face model URL and asks whether or how to port it to SD.Next').

Include common synonyms/variants (HF, model repo, model card) alongside 'Hugging Face' to broaden natural trigger coverage.

Sharpen the action verbs to concrete outputs (e.g., 'classify implementation, rate porting difficulty, and recommend an integration path') to push specificity above 3.

DimensionReasoningScore

Specificity

Quotes "Analyze an external model URL", "determine implementation style", and "estimate SD.Next porting difficulty" name the domain with 2-3 concrete actions, but coverage is limited to analysis/estimation rather than a comprehensive action set, matching anchor 3; not 4 because the actions are somewhat abstract and not several distinct concrete operations.

3 / 5

Completeness

The description clearly states what ("determine implementation style and estimate SD.Next porting difficulty") but has no "Use when..." clause or equivalent explicit trigger, so per the judging guideline completeness is capped at 3; not 4 because the when is entirely absent rather than merely imprecise.

3 / 5

Trigger Term Quality

Natural terms like "external model URL", "Hugging Face", "porting difficulty", and "SD.Next" are terms a user would plausibly say, giving good keyword coverage; not 5 because synonyms (HF, repo) and file extensions are missing.

4 / 5

Distinctiveness Conflict Risk

The niche (SD.Next porting-difficulty estimation for Hugging Face models) is distinct with specific triggers; not 5 because it overlaps with the referenced port-model skill, leaving minor conflict risk with a closely related skill.

4 / 5

Total

14

/

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.

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
vladmandic/sdnext
Reviewed

Table of Contents

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