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pydantic-models-py

Create Pydantic models following the multi-model pattern for clean API contracts.

52

Quality

59%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/pydantic-models-py/SKILL.md

The canonical home for this skill is pydantic-models-py in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

65%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 content is concise and largely actionable with good code examples, but its workflow lacks validation checkpoints and its sole progressive-disclosure reference (assets/template.py) is a broken path with no bundle file behind it.

Suggestions

Add the missing assets/template.py file (or replace the reference with inline template code) so the Quick Start's primary instruction is resolvable.

Insert a verification step into the Integration Steps, e.g. validating that exported models import cleanly and that TS types match the Pydantic fields.

Show the Base/Response model definitions referenced by the Update and InDB examples, or link to a single complete template, so the code examples are fully self-contained.

DimensionReasoningScore

Conciseness

The body is lean with short sections and tight code blocks and avoids explaining concepts Claude already knows, though the opening line repeats the frontmatter description verbatim and could be trimmed.

4 / 5

Actionability

It provides concrete, mostly copy-paste-ready code for camelCase aliases, optional update fields, and the DB document, plus a placeholder-substitution quick start; minor gaps remain (e.g. the referenced MyResponse/Base classes are not shown, and the cited template.py file does not exist in the bundle).

4 / 5

Workflow Clarity

The Integration Steps give a numbered sequence (create models, export, add TS types) but include no validation or verification checkpoint, and the model-construction flow lacks explicit sequencing, so checkpoints are missing or implicit.

3 / 5

Progressive Disclosure

Sections are well-organized, but the Quick Start points to 'assets/template.py' which is not present in the bundle, so the one external reference it relies on is broken, undermining navigation and the overview-to-detail structure.

3 / 5

Total

14

/

20

Passed

Description

53%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 states a clear, specific purpose but omits any 'when to use' trigger guidance, which caps its completeness. It is concise and reasonably distinct, with only moderate natural keyword coverage.

Suggestions

Add an explicit trigger clause, e.g. 'Use when creating request/response models for an API, or when structuring Pydantic schemas for Cosmos DB documents.'

Broaden natural trigger terms to include synonyms users actually say, such as 'schemas', 'request/response models', 'data validation', or 'FastAPI models'.

Name a second concrete action (e.g. 'generate, organize, and export') to lift specificity above a single 'Create' verb.

DimensionReasoningScore

Specificity

It names the domain ('Pydantic models') and one concrete action ('Create') tied to a named pattern ('multi-model pattern'), but lists only a single action rather than comprehensive coverage of what the skill does.

3 / 5

Completeness

It clearly states the 'what' (create Pydantic models via the multi-model pattern for API contracts) but provides no 'when' trigger guidance, and per the rubric a missing 'Use when...' clause caps completeness at 3.

3 / 5

Trigger Term Quality

'Pydantic models' and 'API contracts' are natural terms a user might say, but common synonyms like 'schema', 'validation', 'request/response models', or 'data models' are missing, leaving only partial keyword coverage.

3 / 5

Distinctiveness Conflict Risk

The 'multi-model pattern for clean API contracts' framing carves a fairly specific niche distinct from generic Pydantic helpers, with only minor overlap risk against broader Pydantic/modeling skills.

4 / 5

Total

13

/

20

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

14

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

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