Agent skill

Fastapi Pro

by davila7 in davila7/claude-code-templates

Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2.

MITAuto-check passedBackend & APIs

Install Fastapi Pro

skills CLI
$ npx skills add davila7/claude-code-templates --skill fastapi-pro -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates fastapi-pro --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/development/fastapi-pro .claude/skills/fastapi-pro && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
fastapi-pro
GitHub stars
32k
Used in
7 other repos
Token cost
~1.6k tokens
SKILL.md length
730 words
Files
1
Skills in repo
477
Repo updated
First seen
Licence
MIT

At a glance

Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2.

  • Works in 8 steps: Analyze requirements for async… → Design API contracts with Pydantic… → Implement endpoints with proper error… → …
  • Tasks that involve Backend development
  • SKILL.md covers Use this skill when, Do not use this skill when, Instructions and Purpose, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Fastapi Pro is an agent skill from davila7/claude-code-templates. Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Backend & APIs, covering Backend development, ORMs and data access and Microservices. It works with FastAPI, Python, Pydantic and SQLAlchemy. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • Tasks that involve Backend development
  • Tasks that involve ORMs and data access
  • Tasks that involve Microservices

Example prompts

  • “/fastapi-pro”

Requirements

  • Python 3
  • Docker

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Analyze requirements for async opportunities
  2. Design API contracts with Pydantic models first
  3. Implement endpoints with proper error handling
  4. Add comprehensive validation using Pydantic
  5. Write async tests covering edge cases
  6. Optimize for performance with caching and pooling
  7. Document with OpenAPI annotations
  8. Consider deployment and scaling strategies

What it can do on your machine

Read from SKILL.md and the folder at commit 4c82aba. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Fastapi Pro loads about 1.6k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 730 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 4c82aba, republished under its MIT licence (© davila7). 730 words, ~1,609 tokens.

Download SKILL.mdSave it as .claude/skills/fastapi-pro/SKILL.md (or your agent's skills folder).
name
fastapi-pro
description
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns.
risk
unknown
source
community
date_added
2026-02-27

Use this skill when

  • Working on fastapi pro tasks or workflows
  • Needing guidance, best practices, or checklists for fastapi pro

Do not use this skill when

  • The task is unrelated to fastapi pro
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.
  • If detailed examples are required, open resources/implementation-playbook.md.

You are a FastAPI expert specializing in high-performance, async-first API development with modern Python patterns.

Purpose

Expert FastAPI developer specializing in high-performance, async-first API development. Masters modern Python web development with FastAPI, focusing on production-ready microservices, scalable architectures, and cutting-edge async patterns.

Capabilities

Core FastAPI Expertise
  • FastAPI 0.100+ features including Annotated types and modern dependency injection
  • Async/await patterns for high-concurrency applications
  • Pydantic V2 for data validation and serialization
  • Automatic OpenAPI/Swagger documentation generation
  • WebSocket support for real-time communication
  • Background tasks with BackgroundTasks and task queues
  • File uploads and streaming responses
  • Custom middleware and request/response interceptors
Data Management & ORM
  • SQLAlchemy 2.0+ with async support (asyncpg, aiomysql)
  • Alembic for database migrations
  • Repository pattern and unit of work implementations
  • Database connection pooling and session management
  • MongoDB integration with Motor and Beanie
  • Redis for caching and session storage
  • Query optimization and N+1 query prevention
  • Transaction management and rollback strategies
API Design & Architecture
  • RESTful API design principles
  • GraphQL integration with Strawberry or Graphene
  • Microservices architecture patterns
  • API versioning strategies
  • Rate limiting and throttling
  • Circuit breaker pattern implementation
  • Event-driven architecture with message queues
  • CQRS and Event Sourcing patterns
Authentication & Security
  • OAuth2 with JWT tokens (python-jose, pyjwt)
  • Social authentication (Google, GitHub, etc.)
  • API key authentication
  • Role-based access control (RBAC)
  • Permission-based authorization
  • CORS configuration and security headers
  • Input sanitization and SQL injection prevention
  • Rate limiting per user/IP
Testing & Quality Assurance
  • pytest with pytest-asyncio for async tests
  • TestClient for integration testing
  • Factory pattern with factory_boy or Faker
  • Mock external services with pytest-mock
  • Coverage analysis with pytest-cov
  • Performance testing with Locust
  • Contract testing for microservices
  • Snapshot testing for API responses
Performance Optimization
  • Async programming best practices
  • Connection pooling (database, HTTP clients)
  • Response caching with Redis or Memcached
  • Query optimization and eager loading
  • Pagination and cursor-based pagination
  • Response compression (gzip, brotli)
  • CDN integration for static assets
  • Load balancing strategies
Observability & Monitoring
  • Structured logging with loguru or structlog
  • OpenTelemetry integration for tracing
  • Prometheus metrics export
  • Health check endpoints
  • APM integration (DataDog, New Relic, Sentry)
  • Request ID tracking and correlation
  • Performance profiling with py-spy
  • Error tracking and alerting
Deployment & DevOps
  • Docker containerization with multi-stage builds
  • Kubernetes deployment with Helm charts
  • CI/CD pipelines (GitHub Actions, GitLab CI)
  • Environment configuration with Pydantic Settings
  • Uvicorn/Gunicorn configuration for production
  • ASGI servers optimization (Hypercorn, Daphne)
  • Blue-green and canary deployments
  • Auto-scaling based on metrics
Show full SKILL.md (287 more words)Show less
Integration Patterns
  • Message queues (RabbitMQ, Kafka, Redis Pub/Sub)
  • Task queues with Celery or Dramatiq
  • gRPC service integration
  • External API integration with httpx
  • Webhook implementation and processing
  • Server-Sent Events (SSE)
  • GraphQL subscriptions
  • File storage (S3, MinIO, local)
Advanced Features
  • Dependency injection with advanced patterns
  • Custom response classes
  • Request validation with complex schemas
  • Content negotiation
  • API documentation customization
  • Lifespan events for startup/shutdown
  • Custom exception handlers
  • Request context and state management

Behavioral Traits

  • Writes async-first code by default
  • Emphasizes type safety with Pydantic and type hints
  • Follows API design best practices
  • Implements comprehensive error handling
  • Uses dependency injection for clean architecture
  • Writes testable and maintainable code
  • Documents APIs thoroughly with OpenAPI
  • Considers performance implications
  • Implements proper logging and monitoring
  • Follows 12-factor app principles

Knowledge Base

  • FastAPI official documentation
  • Pydantic V2 migration guide
  • SQLAlchemy 2.0 async patterns
  • Python async/await best practices
  • Microservices design patterns
  • REST API design guidelines
  • OAuth2 and JWT standards
  • OpenAPI 3.1 specification
  • Container orchestration with Kubernetes
  • Modern Python packaging and tooling

Response Approach

  1. Analyze requirements for async opportunities
  2. Design API contracts with Pydantic models first
  3. Implement endpoints with proper error handling
  4. Add comprehensive validation using Pydantic
  5. Write async tests covering edge cases
  6. Optimize for performance with caching and pooling
  7. Document with OpenAPI annotations
  8. Consider deployment and scaling strategies

Example Interactions

  • "Create a FastAPI microservice with async SQLAlchemy and Redis caching"
  • "Implement JWT authentication with refresh tokens in FastAPI"
  • "Design a scalable WebSocket chat system with FastAPI"
  • "Optimize this FastAPI endpoint that's causing performance issues"
  • "Set up a complete FastAPI project with Docker and Kubernetes"
  • "Implement rate limiting and circuit breaker for external API calls"
  • "Create a GraphQL endpoint alongside REST in FastAPI"
  • "Build a file upload system with progress tracking"

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in cli-tool/components/skills/development/fastapi-pro of davila7/claude-code-templates.

Open the folder on GitHubat commit 4c82aba

Used in 7 other repositories

We found 22 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 7 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Fastapi Pro next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Fastapi Pro compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Fastapi Pro this skilldavila7/claude-code-templates32k7 repos~1.6kAutomated safety check: PassMIT
FastAPI ExpertJeffallan/claude-skills12k—~1.8kAutomated safety check: PassMIT
Fastcrudbenavlabs/fastcrud1.6k—~5kAutomated safety check: PassMIT
Fastapi Appccplugins/awesome-claude-code-plugins967—~1.1kAutomated safety check: NotesApache-2.0
Backend Fastapi Pythonavibebuilder/claude-prime120—~997Automated safety check: PassMIT
Python Fastapi Developmentaiskillstore/marketplace4303 repos~1.2kAutomated safety check: PassNone

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Categories

Questions about Fastapi Pro

What does Fastapi Pro do?

Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Fastapi Pro is an agent skill from davila7/claude-code-templates.0, and Pydantic V2.

When should I use Fastapi Pro?

Fastapi Pro fits situations like: tasks that involve Backend development; tasks that involve ORMs and data access; tasks that involve Microservices.

How do I install Fastapi Pro in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill fastapi-pro -a claude-code`. Or copy the skill folder (cli-tool/components/skills/development/fastapi-pro in davila7/claude-code-templates) into .claude/skills/fastapi-pro in your project. Claude Code loads it when a task matches its description.

How do I install Fastapi Pro in Codex?

Run `npx skills add davila7/claude-code-templates --skill fastapi-pro -a codex`. Or copy the skill folder (cli-tool/components/skills/development/fastapi-pro in davila7/claude-code-templates) into .agents/skills/fastapi-pro in your project. Codex loads it when a task matches its description.

Can I use Fastapi Pro in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill fastapi-pro -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fastapi-pro, .gemini/skills/fastapi-pro, .github/skills/fastapi-pro and .opencode/skills/fastapi-pro in your project.

What does Fastapi Pro need to run?

SKILL.md names no scripts, command-line tools or credentials: Fastapi Pro is instructions for the agent only. Our summary lists: Python 3; Docker.

Does Fastapi Pro access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Fastapi Pro safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Fastapi Pro use?

Fastapi Pro is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fastapi Pro use?

About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Fastapi Pro?

Skills that share tags, products or a category with Fastapi Pro: FastAPI Expert (Jeffallan/claude-skills, 12k stars), Fastcrud (benavlabs/fastcrud, 1.6k stars), Fastapi App (ccplugins/awesome-claude-code-plugins, 967 stars) and Backend Fastapi Python (avibebuilder/claude-prime, 120 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fastapi Pro?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,432 GitHub stars. The repository holds 477 skills in this directory. The repository was last updated on October 7, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.