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fastapi-python

Expert in FastAPI Python development with best practices for APIs and async operations

51

Quality

55%

Does it follow best practices?

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tessl review fix ./.agents/skills/fastapi-python/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%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 written, well-sectioned FastAPI style guide that names specific libraries and patterns, but it lacks executable code examples and any multi-step workflow with validation, capping actionability and workflow clarity.

Suggestions

Add at least one complete, executable FastAPI example (router + Pydantic model + async endpoint) to make the guidance copy-paste ready.

Turn the "Key Conventions" list into a short worked workflow (e.g. define model -> declare route -> validate input -> raise HTTPException) with a validation checkpoint.

Trim generic items like "Provide proper error logging and user-friendly messaging" that add little beyond what Claude already knows.

DimensionReasoningScore

Conciseness

The body is a lean bullet list that does not explain concepts Claude already knows (no "what is FastAPI" padding); a few generic platitudes ("user-friendly messaging") could be trimmed, keeping it just below a 5.

4 / 5

Actionability

Guidance names concrete APIs (HTTPException, BaseModel, lifespan, asyncpg, SQLAlchemy 2.0) but provides no executable code or examples showing how to apply them, leaving it incomplete rather than copy-paste ready.

3 / 5

Workflow Clarity

The skill is a standards reference rather than a multi-step process, so there is no sequence with validation checkpoints; the sectioning gives structure but no workflow to validate, landing at the midpoint.

3 / 5

Progressive Disclosure

Content is organized into clearly headed sections (Standards, Error Handling, FastAPI-Specific, Performance, Conventions, Dependencies) with no bundle files to cross-reference; it is slightly too long and dense to fully earn the under-50-line simple-skill exception.

4 / 5

Total

14

/

20

Passed

Description

48%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 identifies the FastAPI/Python domain clearly but is vague about concrete capabilities, leans on an "Expert in" over-claim, and omits any explicit use-trigger, which limits completeness and specificity.

Suggestions

Replace the "Expert in ... with best practices" role claim with concrete actions, e.g. "Builds FastAPI routes, defines Pydantic models, and manages async database sessions."

Add an explicit trigger clause such as "Use when writing or debugging FastAPI applications, async endpoints, or Pydantic validation."

Drop the buzzword "best practices" in favor of named, verifiable capabilities to lift specificity.

DimensionReasoningScore

Specificity

The description names the domain ("FastAPI Python development") but offers only topic labels ("APIs and async operations", "best practices") rather than concrete actions; "Expert in" is an over-claim buzzword rather than a capability statement.

2 / 5

Completeness

It states a clear "what" (FastAPI Python development for APIs and async operations) but provides no "Use when..." or equivalent trigger guidance, which caps completeness at 3 per the rubric.

3 / 5

Trigger Term Quality

It includes relevant natural keywords ("FastAPI", "Python", "APIs") a user would say, but "async operations" and "best practices" are not natural trigger phrases and common variations are missing.

3 / 5

Distinctiveness Conflict Risk

"FastAPI" carves a clear niche with minimal conflict risk, though the broad "Python development" framing leaves minor overlap with general Python or backend skills.

4 / 5

Total

12

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
modelscope/ms-agent
Reviewed

Table of Contents

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