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python-fastapi-development

Python FastAPI backend development with async patterns, SQLAlchemy, Pydantic, authentication, and production API patterns.

Quality

67%

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/python-fastapi-development/SKILL.md

The canonical home for this skill is python-fastapi-development in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

53%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.

A well-sequenced 8-phase orchestration workflow with clear skill-to-phase mapping and copy-paste prompts. Its weaknesses are the absence of interleaved validation checkpoints with feedback loops (validation is only a terminal Quality Gates checklist), no executable code or commands, and duplication between skill lists and prompt blocks that could be trimmed.

Suggestions

Add per-phase validation checkpoints with feedback loops (e.g., after Phase 6: run pytest; if coverage < 80%, fix and re-run before proceeding) instead of relying solely on the terminal Quality Gates checklist.

Make actions concrete with actual commands or short code examples (uv, alembic, pytest, docker) — e.g. "Run `alembic revision --autogenerate -m 'add users'`" — or move per-phase detail into reference files.

Merge "Skills to Invoke" and "Copy-Paste Prompts" into one combined per-phase list to remove duplication and cut tokens.

DimensionReasoningScore

Conciseness

The body is mostly structural with no tutorial padding, but each phase duplicates its skill list in "Copy-Paste Prompts" and generic action items like "Set up logging" and "Configure production settings" add little beyond what Claude already knows. It fits "mostly efficient but includes some unnecessary content that could be tightened."

3 / 5

Actionability

Concrete elements exist (literal copy-paste prompts, named skills per phase, a specific stack table with versions like "SQLAlchemy 2.0" and "Pydantic v2"), but there is no executable code or commands, and action lists are high-level directives with all detail delegated to skills outside this bundle. Not 2 because the prompts and stack table give real, specific direction; not 4 because most actions lack executable specifics.

3 / 5

Workflow Clarity

The 8 phases are clearly sequenced and a "Quality Gates" checklist provides end-state validation, but there are no per-phase checkpoints and no feedback loops describing what to do when a gate fails — validation is a single terminal checklist rather than interleaved checkpoints. Fits the anchor "steps listed but validation gaps; checkpoints missing or implicit."

3 / 5

Progressive Disclosure

The bundle is a single self-contained SKILL.md with clean section headers, no nested or buried references, and per-phase pointers to named external skills; scored against the actual (empty) bundle structure, structure is good with minor gaps. Not 5 because per-phase detail (skills, actions, prompts) is all inline where reference files could carry it, and no reference files exist.

4 / 5

Total

13

/

20

Passed

Description

66%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.

A specific, technology-dense description that clearly identifies the FastAPI niche and would trigger correctly for FastAPI, SQLAlchemy, or Pydantic requests. Its main weakness is the missing 'Use when...' trigger clause, which caps completeness and leaves invocation conditions implicit.

Suggestions

Add an explicit trigger clause, e.g. "Use when building new FastAPI services, adding endpoints to an existing FastAPI app, or setting up SQLAlchemy models, Pydantic validation, or JWT authentication."

Include natural trigger variations users actually say — "REST API", "backend API", "JWT", "uvicorn" — to broaden keyword coverage toward the top anchor.

Convert the technology list into concrete actions ("Build async REST APIs, design SQLAlchemy models, implement JWT auth, deploy FastAPI services") to raise specificity from 4 to 5.

DimensionReasoningScore

Specificity

"backend development with async patterns, SQLAlchemy, Pydantic, authentication, and production API patterns" names the domain plus five concrete capability areas, matching the "several specific actions; minor gaps" anchor. Not 5 because these are technology nouns rather than explicit actions, and workflow stages (testing, deployment) named in the body are absent from the description.

4 / 5

Completeness

It has a clear, specific "what" (Python FastAPI backend development across named technologies) but no "Use when..." clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. Not 2 because the "what" is concrete and multi-faceted, not vague.

3 / 5

Trigger Term Quality

"FastAPI", "SQLAlchemy", "Pydantic", "authentication", and "backend" are terms users naturally say, fitting "good keyword coverage; a few natural terms missing". Not 5 because common variations like "REST API", "JWT", "OAuth", "uvicorn", and "microservices" are missing.

4 / 5

Distinctiveness Conflict Risk

The FastAPI niche (with SQLAlchemy/Pydantic) is mostly distinct from general Python, Flask, or Django skills; only minor overlap risk with generic backend/API-development skills. Not 5 because "production API patterns" is broad enough to overlap with general API skills.

4 / 5

Total

15

/

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.

Validation — 15 / 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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/python-fastapi-development/SKILL.md

Reviewed

Table of Contents

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