flask-ml-api-creator
Flask Ml Api Creator - Auto-activating skill for ML Deployment. Triggers on: flask ml api creator, flask ml api creator Part of the ML Deployment skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill flask-ml-api-creatorOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped, essentially just restating the skill name without explaining capabilities or usage triggers. It provides no actionable information for Claude to determine when to select this skill over others. The duplicate trigger term and lack of concrete actions make this description nearly useless for skill selection.
Suggestions
Add specific actions the skill performs, e.g., 'Creates Flask REST API endpoints for serving ML models, handles model loading, prediction requests, and response formatting'
Add a 'Use when...' clause with natural trigger terms like 'deploy model as API', 'create prediction endpoint', 'serve machine learning model', 'Flask ML service'
Include file types or frameworks supported, e.g., 'scikit-learn, TensorFlow, PyTorch models' to improve distinctiveness
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only states 'Flask Ml Api Creator' and 'ML Deployment' without describing any concrete actions. There are no specific capabilities listed like 'create endpoints', 'deploy models', or 'configure routes'. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and has no 'Use when...' clause or explicit trigger guidance. Both the what and when are essentially missing. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated ('flask ml api creator, flask ml api creator'). Missing natural user phrases like 'deploy model', 'create API endpoint', 'serve ML model', 'REST API for machine learning'. | 1 / 3 |
Distinctiveness Conflict Risk | The Flask + ML combination provides some specificity that distinguishes it from generic API or ML skills, but 'ML Deployment' is broad enough to potentially conflict with other deployment-related skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill is entirely meta-content describing what the skill supposedly does, without any actual instructional content. It contains zero actionable guidance for creating Flask ML APIs - no code examples, no architecture patterns, no deployment steps, and no ML-specific considerations like model loading or inference endpoints.
Suggestions
Add executable Python code showing a minimal Flask ML API with model loading and prediction endpoint
Include a clear workflow: 1) Load model, 2) Create endpoint, 3) Handle input validation, 4) Return predictions, with validation steps
Provide specific examples of request/response formats for ML inference endpoints
Remove all meta-description content ('This skill provides...', 'When to Use...') and replace with actual implementation guidance
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing specific about Flask ML API creation. Phrases like 'provides automated assistance' and 'follows industry best practices' are filler that waste tokens without adding value. | 1 / 3 |
Actionability | No concrete code, commands, or specific guidance is provided. The skill describes what it does abstractly ('provides step-by-step guidance') but never actually provides any steps, code examples, or executable instructions for creating a Flask ML API. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps, no sequence, and no validation checkpoints. The content only describes when the skill activates, not how to actually accomplish the task. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of meta-description with no structure pointing to actual implementation details. There are no references to detailed guides, examples, or API documentation. | 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
Table of Contents
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