Flask is a micro-framework for Python web development, designed for building microservices, REST APIs, and flexible web applications. Its minimalist core and extensive extension ecosystem make it ideal for projects requiring lightweight architecture, rapid development, and full control over components.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionflaskExecute the skills CLI command in your project's root directory to begin installation:
Fetches flask from bobmatnyc/claude-mpm-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate flask. Access via /flask in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Flask is a micro-framework for Python web development, designed for building microservices, REST APIs, and flexible web applications. Its minimalist core and extensive extension ecosystem make it ideal for projects requiring lightweight architecture, rapid development, and full control over components.
Key Features:
Installation:
# Basic Flask
pip install flask
# Flask with common extensions
pip install flask flask-restful flask-sqlalchemy flask-login flask-cors
# With database support
pip install flask flask-sqlalchemy psycopg2-binary # PostgreSQL
# Full microservices stack
pip install flask flask-restful marshmallow flask-jwt-extended redis
# app.py
from flask import Flask, jsonify, request
app = Flask(__name__)
@app.route('/')
def hello():
return jsonify({"message": "Hello, World!"})
@app.route('/api/users/<int:user_id>')
def get_user(user_id):
return jsonify({"id": user_id, "name": f"User {user_id}"})
@app.route('/api/users', methods=['POST'])
def create_user():
data = request.get_json()
return jsonify({"id": 123, **data}), 201
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=5000)
Run:
# Development server
python app.py
# Or using flask CLI
export FLASK_APP=app.py
export FLASK_ENV=development
flask run
# Custom port
flask run --port 8000 --host 0.0.0.0
Recommended for production and testing:
# app/__init__.py
from flask import Flask
from app.config import Config
from app.extensions import db, migrate, jwt
def create_app(config_class=Config):
"""Application factory pattern."""
app = Flask(__name__)
app.config.from_object(config_class)
# Initialize extensions
db.init_app(app)
migrate.init_app(app, db)
jwt.init_app(app)
# Register blueprints
from app.routes import api_bp, auth_bp
app.register_blueprint(api_bp, url_prefix='/api')
app.register_blueprint(auth_bp, url_prefix='/auth')
return app
# app/extensions.py
from flask_sqlalchemy import SQLAlchemy
from flask_migrate import Migrate
from flask_jwt_extended import JWTManager
db = SQLAlchemy()
migrate = Migrate()
jwt = JWTManager()
# app/config.py
import os
class Config:
SECRET_KEY = os.environ.get('SECRET_KEY') or 'dev-secret-key'
SQLALCHEMY_DATABASE_URI = os.environ.get('DATABASE_URL') or 'sqlite:///app.db'
SQLALCHEMY_TRACK_MODIFICATIONS = False
JWT_SECRET_KEY = os.environ.get('JWT_SECRET_KEY') or 'jwt-secret'
class DevelopmentConfig(Config):
DEBUG = True
TESTING = False
class ProductionConfig(Config):
DEBUG = False
TESTING = False
# run.py
from app import create_app
app = create_app()
if __name__ == '__main__':
app.run()
Run:
export FLASK_APP=run.py
flask run
from flask import Flask, request, jsonify, make_response, abort
app = Flask(__name__)
@app.route('/api/data', methods=['GET', 'POST'])
def handle_data():
# GET request
if request.method == 'GET':
# Query parameters
page = request.args.get('page', 1, type=int)
limit = request.args.get('limit', 10, type=int)
return jsonify({
"page": page,
"limit": limit,
"data": [...]
})
# POST request
if request.method == 'POST':
# JSON body
data = request.get_json()
# Validation
if not data or 'name' not in data:
abort(400, description="Missing required field: name")
# Custom response with headers
response = make_response(jsonify({"id": 1, **data}), 201)
response.headers['X-Custom-Header'] = 'value'
return response
# Error handling
@app.errorhandler(404)
def not_found(error):
return jsonify({"error": "Resource not found"Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
flask reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for flask matched our evaluation — installs cleanly and behaves as described in the markdown.
We added flask from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
flask fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
flask has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend flask for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in flask — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: flask is the kind of skill you can hand to a new teammate without a long onboarding doc.
flask is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: flask is the kind of skill you can hand to a new teammate without a long onboarding doc.
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