Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add bobmatnyc/claude-mpm-skills --skill flaskgit clone --depth 1 https://github.com/bobmatnyc/claude-mpm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bobmatnyc/claude-mpm-skills/flask)<a href="https://agentmods.dev/skills/bobmatnyc/claude-mpm-skills/flask"><img src="https://agentmods.dev/badge/skills/bobmatnyc/claude-mpm-skills/flask/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bobmatnyc/claude-mpm-skills/flask"><img src="https://agentmods.dev/badge/skills/bobmatnyc/claude-mpm-skills/flask.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 782 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 906 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 909 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Tool Misuse · line 94 Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
- medium Tool Misuse · line 911 Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
- medium Data Exfiltration · line 1335 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- low Tool Misuse · line 1249 Tool calls are chained to bypass individual safety checks or escalate capabilities beyond what any single tool call would allow.Fix: Limit tool chaining depth and validate the output of each tool before passing it to the next. Require explicit user approval for multi-step chains.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.09992 |
| Opus 5 | $0.00013 | $0.04996 |
| Sonnet 5 | $0.00005 | $0.01998 |
| Haiku 4.5 | $0.00003 | $0.00999 |
Grade A, and why
flask scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(url, timeout=self.timeout, **kwargs) How it starts
The opening of the file, as written. The whole thing — 1,659 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flask - Lightweight Python Web Framework
Overview
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:
- Micro-framework philosophy (minimal core, extensible)
- Flask-RESTful for API development
- Blueprints for modular application structure
- SQLAlchemy integration via Flask-SQLAlchemy
- Jinja2 templating engine
- Built-in development server with auto-reload
- Werkzeug WSGI toolkit foundation
- Large extension ecosystem (Flask-Login, Flask-JWT, Flask-CORS)
- Production deployment with Gunicorn/uWSGI
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
Basic Application Patterns
1. Minimal Flask App
# 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
2. Application Factory Pattern
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()
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 1,659 lines · 25 tokens per session scan A 76857cddb9ce
flask is a skill published in the GitHub repository bobmatnyc/claude-mpm-skills (75 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 9,992 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
flask
Flask - Lightweight Python web framework for microservices, REST APIs, and flexible web applications with extensive extension ecosystem.
flask-expert
Expert-level Flask web development, REST APIs, extensions, and production deployment. Use when the user mentions Python, web framework, REST APIs, or Jinja2, or when the task involves Flask Fundamentals or Flask Extensions.
FastAPI Customer Support Tech Enablement
Comprehensive FastAPI skill for building modern Python web APIs with focus on customer support systems, ticket management, real-time chat, and backend operations.
flask
Build Flask applications with app factories, blueprints, JSON or Jinja responses, extensions, and pytest checks.
fastapi-microservices-development
Comprehensive guide for building production-ready microservices with FastAPI including REST API patterns, async operations, dependency injection, and deployment strategies.
FastAPI Modern Web Development
Production-grade FastAPI development with async patterns, Pydantic v2, dependency injection, ML/AI endpoint design, and modern Python best practices for building high-performance REST APIs.