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 agentmods add skills/tmolavi/mcp-agent-skills-hub/python-fastapi-developmentnpx skills add tmolavi/mcp-agent-skills-hub --skill python-fastapi-developmentgit clone --depth 1 https://github.com/tmolavi/mcp-agent-skills-hubWrote 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/tmolavi/mcp-agent-skills-hub/python-fastapi-development)<a href="https://agentmods.dev/skills/tmolavi/mcp-agent-skills-hub/python-fastapi-development"><img src="https://agentmods.dev/badge/skills/tmolavi/mcp-agent-skills-hub/python-fastapi-development.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00028 | $0.01268 |
| Opus 5 | $0.00014 | $0.00634 |
| Sonnet 5 | $0.00006 | $0.00254 |
| Haiku 4.5 | $0.00003 | $0.00127 |
Grade A, and why
python-fastapi-development scanned grade A with 0 findings 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 yesterday.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python/FastAPI Development Workflow
Overview
Specialized workflow for building production-ready Python backends with FastAPI, featuring async patterns, SQLAlchemy ORM, Pydantic validation, and comprehensive API patterns.
When to Use This Workflow
Use this workflow when:
- Building new REST APIs with FastAPI
- Creating async Python backends
- Implementing database integration with SQLAlchemy
- Setting up API authentication
- Developing microservices
Workflow Phases
Phase 1: Project Setup
Skills to Invoke
app-builder- Application scaffoldingpython-development-python-scaffold- Python scaffoldingfastapi-templates- FastAPI templatesuv-package-manager- Package management
Actions
- Set up Python environment (uv/poetry)
- Create project structure
- Configure FastAPI app
- Set up logging
- Configure environment variables
Copy-Paste Prompts
Use @fastapi-templates to scaffold a new FastAPI project
Use @python-development-python-scaffold to set up Python project structure
Phase 2: Database Setup
Skills to Invoke
prisma-expert- Prisma ORM (alternative)database-design- Schema designpostgresql- PostgreSQL setuppydantic-models-py- Pydantic models
Actions
- Design database schema
- Set up SQLAlchemy models
- Create database connection
- Configure migrations (Alembic)
- Set up session management
Copy-Paste Prompts
Use @database-design to design PostgreSQL schema
Use @pydantic-models-py to create Pydantic models for API
Phase 3: API Routes
Skills to Invoke
fastapi-router-py- FastAPI routersapi-design-principles- API designapi-patterns- API patterns
Actions
- Design API endpoints
- Create API routers
- Implement CRUD operations
- Add request validation
- Configure response models
Copy-Paste Prompts
Use @fastapi-router-py to create API endpoints with CRUD operations
Use @api-design-principles to design RESTful API
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.
- yesterday First seen · 221 lines · 28 tokens per session scan A 2e5295400058
python-fastapi-development is a skill published in the GitHub repository tmolavi/mcp-agent-skills-hub (8 stars, last pushed 9d ago), licensed MIT. It adds 28 tokens to every session and 1,268 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
pygame-core
Structure a pygame (pygame-ce) game in Python: the init/event/update/draw loop, delta-time movement, Surface/Rect blitting, keyboard/mouse input, and Sprite/Group management with collision. Use when building or debugging a pygame game — when the user mentions pygame, pygame-ce, the game loop, blit, Surface, Rect…
python-pro
🚀 Professional AI Agent orchestrator for generating tailored rules and AGENTS.md with deterministic JIT skill discovery. Optimized for Context Savings and Agent Alignment.
jupyter-live-kernel
Iterative Python via live Jupyter kernel (hamelnb).
claude-api
Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.
godot-gdscript
Write idiomatic GDScript for Godot 4.7: static typing, the node lifecycle (ready/process/physicsprocess), @export/@onready/@tool annotations, signals, and await for asynchronous flow. Use when editing .gd scripts in a Godot project (project.godot), writing or debugging GDScript, or porting 3.x GDScript to 4.x…
fastapi-templates
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.