fastapi-ml-endpoint
Fastapi Ml Endpoint - Auto-activating skill for ML Deployment. Triggers on: fastapi ml endpoint, fastapi ml endpoint Part of the ML Deployment skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill fastapi-ml-endpointOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped, functioning more as a label than a useful skill description. It lacks any concrete actions, meaningful trigger terms, or guidance on when to use it. The redundant trigger term and boilerplate category mention provide no value for skill selection.
Suggestions
Add specific actions the skill performs, e.g., 'Creates FastAPI endpoints for serving ML models, handles request/response schemas, configures model loading and inference pipelines'
Include a 'Use when...' clause with natural trigger terms like 'deploy ML model', 'create prediction API', 'serve model with FastAPI', 'model inference endpoint'
Add variations of terminology users might use: 'REST API for ML', 'model serving', 'prediction endpoint', 'inference API', '.py API file'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the domain 'FastAPI ML Endpoint' and category 'ML Deployment' without describing any concrete actions. No specific capabilities like 'create endpoints', 'deploy models', or 'configure routes' are mentioned. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond naming itself, and has no explicit 'Use when...' clause or equivalent guidance for when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | The trigger terms are redundant ('fastapi ml endpoint' listed twice) and overly specific/technical. Missing natural variations users might say like 'deploy model', 'API for machine learning', 'serve ML model', 'model endpoint', or 'REST API'. | 1 / 3 |
Distinctiveness Conflict Risk | The FastAPI + ML combination provides some specificity that distinguishes it from generic API or ML skills, but the lack of concrete actions means it could still overlap with other deployment or API-related skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill is a placeholder template with no actual instructional content. It describes what the skill should do in abstract terms but provides zero actionable guidance on creating FastAPI ML endpoints - no code examples, no API patterns, no model serving techniques, no deployment configurations.
Suggestions
Add executable FastAPI code showing a complete ML endpoint with model loading, request/response schemas, and prediction logic
Include specific patterns for common ML serving scenarios (e.g., batch inference, async predictions, model versioning)
Provide a clear workflow for deploying an ML model: load model -> define Pydantic schemas -> create endpoint -> add health checks -> validate
Add references to advanced topics like model caching, GPU inference, monitoring, and scaling considerations
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing specific about FastAPI ML endpoints. Phrases like 'provides automated assistance' and 'follows industry best practices' are filler that Claude doesn't need. | 1 / 3 |
Actionability | No concrete code, commands, or specific guidance is provided. The skill describes what it does abstractly but never shows how to actually create a FastAPI ML endpoint - no example code, no API patterns, no model loading examples. | 1 / 3 |
Workflow Clarity | No workflow or steps are defined. The content only lists vague capabilities without any sequence of actions, validation steps, or process for deploying an ML model with FastAPI. | 1 / 3 |
Progressive Disclosure | No structure beyond generic headings. No references to detailed documentation, no links to examples or advanced topics, and no organization that would help Claude navigate to specific information. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
69%Validation — 11 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 11 / 16 Passed | |
Reviewed
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