Agent skill

Fastapi

by ericrisco in ericrisco/rsc-harness

A skill your agent uses when building, reviewing, testing, securing or shipping a FastAPI / async Python service — routers, Pydantic v2 schemas, dependency injection, async SQLAlchemy 2.0…

MITAuto-check: notesBackend & APIs

Install Fastapi

skills CLI
$ npx skills add ericrisco/rsc-harness --skill fastapi -a claude-code

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

GitHub CLI
$ gh skill install ericrisco/rsc-harness fastapi --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/ericrisco/rsc-harness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/fastapi .claude/skills/fastapi && 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
GitHub stars
167
Token cost
~5k tokens
SKILL.md length
1,051 words
Files
8 (incl. scripts, references)
Skills in repo
227
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when building, reviewing, testing, securing or shipping a FastAPI / async Python service — routers, Pydantic v2 schemas, dependency injection, async SQLAlchemy 2.0…

  • Works in 8 steps: async def for any I/O route + async… → Three Pydantic models per resource —… → Request-scoped resources via… → …
  • Shipping a FastAPI / async Python service — routers
  • SKILL.md covers Decision rules, Project layout, Application factory + lifespan and Configuration…, plus 11 more sections
  • Runs Shell scripts from its folder; calls mypy and pytest

What it does

Fastapi is an agent skill from ericrisco/rsc-harness. Use when building, reviewing, testing, securing or shipping a FastAPI / async Python service — routers, Pydantic v2 schemas, dependency injection, async SQLAlchemy 2.0, OAuth2/JWT, ASGITransport tests, production wiring. NOT language-level Python or packaging (that is python), NOT engine-level SQL (that is postgresdb), NOT framework-agnostic REST contracts (that is api-design).

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `evals/README.md`, `evals/cases.yaml` and `references/database.md`).

It sits in Backend & APIs, covering Backend development, API design and ORMs and data access. It works with FastAPI, Python, Pydantic and SQL. The repository describes itself as: Your agent invents things because it has no memory, and can't touch your database because it has no arms. rsc is the meta-harness that gives it both, plus the trade to know the… The licence is MIT.

When your agent uses it

  • Shipping a FastAPI / async Python service — routers
  • Pydantic v2 schemas
  • Dependency injection
  • Async SQLAlchemy 2.0

Example prompts

  • “/fastapi”

Requirements

  • Python 3
  • A Bash shell
  • Docker

Workflow steps

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

  1. async def for any I/O route + async drivers (asyncpg, httpx); never requests/psycopg2/blocking calls on the loop (offload via await…
  2. Three Pydantic models per resource — XCreate/XUpdate/XResponse (from_attributes=True); responses never leak hashes/tokens/internal flags.
  3. Request-scoped resources via Annotated[T, Depends(...)], never built inline — so tests can override them.
  4. One DB session per request via get_db (commit-on-success / rollback-on-exception); handlers never commit.
  5. One error envelope {"error":{"code","message","details?"}} via centralized handlers; never leak stack traces / SQL.
  6. Settings from pydantic-settings (BaseSettings), never scattered os.getenv.
  7. Validate JWT exp/iss/aud and pin algorithms=["RS256"|"HS256"] explicitly.
  8. Tests: ASGITransport + dependency_overrides on a transactional DB; CI gates on ruff, mypy --strict, pytest --cov, pip-audit.

What it can do on your machine

Read from SKILL.md and the folder at commit e3d5b33. 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

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • mypy
    • pytest

    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 loads about 5k tokens when it runs, and up to ~17k if it reads all its reference files. Until then it costs about 99 tokens; SKILL.md has 1,051 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~17k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:151
    el_config = SettingsConfigDict(env_file=".env", env_prefix="APP_", extra="ignore")
  • NoteMentions a .env fileSKILL.md:167
    ignore[call-arg]  # values come from env/.env

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); the scripts in this folder are not scanned.

SKILL.md

The full file from ericrisco/rsc-harness at commit e3d5b33, republished under its MIT licence (© ericrisco). 1,051 words, ~4,957 tokens.

Download SKILL.mdSave it as .claude/skills/fastapi/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
fastapi
description
Use when building, reviewing, testing, securing or shipping a FastAPI / async Python service — routers, Pydantic v2 schemas, dependency injection, async SQLAlchemy 2.0, OAuth2/JWT, ASGITransport tests, production wiring. NOT language-level Python or packaging (that is `python`), NOT engine-level SQL (that is `postgresdb`), NOT framework-agnostic REST contracts (that is `api-design`).
tags
python, api, async, backend, rest
recommends
postgresdb, secure-coding, deployment
origin
risco

FastAPI & modern Python services

The single authoritative skill for building, reviewing, testing, securing and shipping an async FastAPI service on Python 3.12+. The mental model: the app is a thin async HTTP layer over typed dependencies, a service/repository core, and explicit DB sessions. Routes validate and delegate; they never own business logic, raw SQL, or secrets.

Pinned stack: Python 3.12+, FastAPI 0.136+, Starlette 1.0+ (FastAPI 0.136 requires it; avoid <1.0.1, GHSA-86qp-5c8j-p5mr), Pydantic v2 (2.7+) + pydantic-settings 2.x, SQLAlchemy 2.0 async, Alembic 1.13+, asyncpg 0.30 / psycopg 3, httpx 0.28+, pytest 8 + pytest-asyncio 1.0+ (asyncio_mode=auto), ruff 0.7+, mypy 1.13+ strict, uv 0.5+, uvicorn 0.32+ / gunicorn 23+ + uvicorn-worker 0.3+, PyJWT 2.10+, argon2-cffi 23+, pip-audit 2.7+, PostgreSQL 16. (All lower bounds; install the latest in each line.)

⚠️ SDD new-feature gate — read this first. If this skill fired on a new, non-trivial feature or behaviour change and there is no approved spec + plan under 02-DOCS/wiki/sdd/, STOP — do not write feature code yet. Hand off to ../specify/SKILL.md first: it runs brainstorm → spec → plan → tasks before any code, then routes back here once the plan is approved. Build here directly only for a genuinely one-line / low-risk change. Method: ../sdd/SKILL.md.

Out of scope, and where it goes instead: django for Django; Flask / sync WSGI, notebooks and CLI-only scripts (no skill); language-level Python, typing and packaging → python; framework-agnostic REST contracts — status codes, URL naming, versioning, cursor vs offset → api-design (this skill covers their FastAPI implementation); engine-level schema, indexing, EXPLAIN, zero-downtime migrations, PgBouncer → postgresdb; language-agnostic injection / secret / authz theory → secure-coding; Dockerfile, Compose and CI/CD mechanics → deployment (this skill keeps only a Docker note).

Decision rules

  1. async def for any I/O route + async drivers (asyncpg, httpx); never requests/psycopg2/blocking calls on the loop (offload via await anyio.to_thread.run_sync).
  2. Three Pydantic models per resource — XCreate/XUpdate/XResponse (from_attributes=True); responses never leak hashes/tokens/internal flags.
  3. Request-scoped resources via Annotated[T, Depends(...)], never built inline — so tests can override them.
  4. One DB session per request via get_db (commit-on-success / rollback-on-exception); handlers never commit.
  5. One error envelope {"error":{"code","message","details?"}} via centralized handlers; never leak stack traces / SQL.
  6. Settings from pydantic-settings (BaseSettings), never scattered os.getenv.
  7. Validate JWT exp/iss/aud and pin algorithms=["RS256"|"HS256"] explicitly.
  8. Tests: ASGITransport + dependency_overrides on a transactional DB; CI gates on ruff, mypy --strict, pytest --cov, pip-audit.

Project layout

text
app/
├── main.py            # create_app() factory + lifespan; app = create_app()
├── core/
│   ├── config.py      # Settings(BaseSettings) + get_settings()
│   ├── security.py    # hashing, JWT encode/decode
│   └── logging.py     # structlog / JSON logging setup
├── api/
│   ├── deps.py        # get_db, get_current_user, Pagination, require_roles
│   └── routers/
│       ├── users.py
│       └── health.py
├── schemas/           # Pydantic v2 models (Create/Update/Response)
│   └── user.py
├── models/            # SQLAlchemy 2.0 DeclarativeBase models
│   └── user.py
├── db/
│   ├── base.py        # engine, async_sessionmaker, Base
│   └── repository.py  # generic async Repository[ModelT]
├── services/          # business logic (no FastAPI imports)
│   └── user_service.py
├── exceptions.py      # AppError hierarchy + register_exception_handlers
tests/                 # pytest-asyncio + ASGITransport
alembic/               # async env.py + versions/
pyproject.toml         # ruff + mypy strict + pytest config

Routers stay thin, services hold the logic, the repository/CRUD layer owns persistence.

Application factory + lifespan

python
from contextlib import asynccontextmanager

from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

from app.api.routers import health, users
from app.core.config import Settings, get_settings
from app.db.base import engine
from app.exceptions import register_exception_handlers

# Routers paired with their mount prefix + OpenAPI tag, declared once so the factory
# stays a flat loop instead of a wall of include_router() calls.
ROUTERS = (
    (health.router, "/health", "health"),
    (users.router, "/api/v1/users", "users"),
)


@asynccontextmanager
async def lifespan(_app: FastAPI):
    # Open pools/caches on startup (here), never at import time, so importing the module has
    # no side effects (tests and Alembic import it freely).
    yield
    await engine.dispose()   # release pooled DB connections so workers exit cleanly


def _install_cors(app: FastAPI, settings: Settings) -> None:
    if not settings.cors_origins:
        return  # no browser clients configured -> skip the middleware entirely
    app.add_middleware(
        CORSMiddleware,
        allow_origins=settings.cors_origins,   # explicit per-env list, never ["*"] with creds
        allow_credentials=True,
        allow_methods=["GET", "POST", "PUT", "PATCH", "DELETE"],
        allow_headers=["Authorization", "Content-Type"],
    )


def create_app(settings: Settings | None = None) -> FastAPI:
    settings = settings or get_settings()
    app = FastAPI(title=settings.api_title, version=settings.api_version, lifespan=lifespan)

    register_exception_handlers(app)
    _install_cors(app, settings)
    for router, prefix, tag in ROUTERS:
        app.include_router(router, prefix=prefix, tags=[tag])
    return app


app = create_app()

Accepting an optional settings argument lets tests build the app with overridden config without touching the get_settings cache. Bad = allow_origins=["*"] with allow_credentials=True — browsers reject it and Starlette refuses to echo * for credentialed requests. → references/production.md for proxy headers / logging wiring at startup.

To inject servers / security schemes / a logo into the generated OpenAPI doc, assign a custom builder to app.openapi inside create_app(). → references/production.md (Customizing the OpenAPI schema).

Configuration (pydantic-settings)

python
from functools import lru_cache

from pydantic import PostgresDsn, SecretStr
from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    model_config = SettingsConfigDict(env_file=".env", env_prefix="APP_", extra="ignore")

    api_title: str = "Service API"
    api_version: str = "1.0.0"
    environment: str = "development"
    database_url: PostgresDsn
    jwt_secret: SecretStr
    jwt_algorithm: str = "HS256"
    jwt_issuer: str = "service-api"
    jwt_audience: str = "service-clients"
    access_token_ttl_seconds: int = 900
    cors_origins: list[str] = []


@lru_cache
def get_settings() -> Settings:
    return Settings()  # type: ignore[call-arg]  # values come from env/.env

Bad = DB_URL = os.environ["DB_URL"] at import time (crashes on import, untyped, unmockable). Good = inject get_settings as a dependency so tests override it.

Pydantic v2 models (Create/Update/Response split)

python
from datetime import datetime
from typing import Annotated
from uuid import UUID

from pydantic import BaseModel, ConfigDict, EmailStr, Field, computed_field

# Reusable constrained types keep the same rule in one place across the three models.
FullName = Annotated[str, Field(min_length=1, max_length=100)]
RawPassword = Annotated[str, Field(min_length=12, max_length=128)]


class UserInput(BaseModel):
    """Fields a client may send. Create/Update narrow this; Response never inherits it."""

    email: EmailStr
    full_name: FullName


class UserCreate(UserInput):
    password: RawPassword


class UserUpdate(BaseModel):
    # Every field optional: a PATCH sends only what changes.
    email: EmailStr | None = None
    full_name: FullName | None = None


class UserResponse(BaseModel):
    model_config = ConfigDict(from_attributes=True)  # populate straight off ORM attributes

    id: UUID
    email: EmailStr
    full_name: str
    created_at: datetime

    @computed_field  # type: ignore[prop-decorator]
    @property
    def label(self) -> str:
        return f"{self.full_name} <{self.email}>"

v2 migration cheats: use .model_dump() not .dict(); .model_validate(obj) not .from_orm(); model_config = ConfigDict(...) not class Config; field_validator/model_validator not @validator/@root_validator.

Bad = a response model with hashed_password: str (leaks the hash). Good = the UserResponse above (no secret fields). → references/security.md.

Dependency injection

python
from collections.abc import AsyncIterator
from dataclasses import dataclass
from typing import Annotated

from fastapi import Depends, Query
from sqlalchemy.ext.asyncio import AsyncSession

from app.db.base import async_session_factory


async def get_db() -> AsyncIterator[AsyncSession]:
    session = async_session_factory()
    try:
        yield session
        await session.commit()   # commit only if the handler returned without raising
    except Exception:
        await session.rollback()  # any error (incl. HTTP exceptions) unwinds the txn
        raise
    finally:
        await session.close()    # always release the connection back to the pool


DbSession = Annotated[AsyncSession, Depends(get_db)]


@dataclass(frozen=True)
class Pagination:
    limit: int
    offset: int


def get_pagination(
    limit: Annotated[int, Query(ge=1, le=100)] = 50,
    offset: Annotated[int, Query(ge=0)] = 0,
) -> Pagination:
    return Pagination(limit=limit, offset=offset)


PageParams = Annotated[Pagination, Depends(get_pagination)]

→ references/database.md for async_session_factory wiring; → references/security.md for get_current_user and require_roles.

Routers & endpoints

python
from fastapi import APIRouter, Response, status

from app.api.deps import CurrentUser, DbSession, PageParams
from app.schemas.user import UserCreate, UserResponse
from app.services import user_service

router = APIRouter()


@router.get("", response_model=list[UserResponse])
async def list_users(db: DbSession, page: PageParams) -> list[UserResponse]:
    return await user_service.list_users(db, limit=page.limit, offset=page.offset)


@router.post("", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def create_user(payload: UserCreate, db: DbSession, response: Response) -> UserResponse:
    user = await user_service.create_user(db, payload)
    response.headers["Location"] = f"/api/v1/users/{user.id}"
    return user

Bad = hashing the password + building select() + business rules inline in the route. Good = await user_service.create_user(db, payload) (route stays thin). CurrentUser is defined in references/security.md.

Error handling & envelope

python
from fastapi import FastAPI, Request, status
from fastapi.exceptions import RequestValidationError
from fastapi.responses import JSONResponse

from app.core.logging import logger


class AppError(Exception):
    def __init__(self, message: str, code: str, status_code: int = 500,
                 details: list[dict] | None = None) -> None:
        super().__init__(message)
        self.message = message
        self.code = code
        self.status_code = status_code
        self.details = details or []


class NotFoundError(AppError):
    def __init__(self, resource: str, ident: str) -> None:
        super().__init__(f"{resource} not found: {ident}", "not_found", 404)


def register_exception_handlers(app: FastAPI) -> None:
    @app.exception_handler(AppError)
    async def _app_error(request: Request, exc: AppError) -> JSONResponse:
        return JSONResponse(
            status_code=exc.status_code,
            content={"error": {"code": exc.code, "message": exc.message, "details": exc.details}},
        )

    @app.exception_handler(RequestValidationError)
    async def _validation(request: Request, exc: RequestValidationError) -> JSONResponse:
        details = [{"field": ".".join(map(str, e["loc"][1:])), "message": e["msg"], "code": e["type"]}
                   for e in exc.errors()]
        return JSONResponse(
            status_code=422,
            content={"error": {"code": "validation_error", "message": "Request validation failed",
                               "details": details}},
        )

    @app.exception_handler(Exception)
    async def _unhandled(request: Request, exc: Exception) -> JSONResponse:
        logger.exception("unhandled_error", path=request.url.path)
        return JSONResponse(
            status_code=500,
            content={"error": {"code": "internal_error", "message": "An unexpected error occurred"}},
        )

Keep this envelope identical across every handler — one code/message/details shape so clients parse errors once. Subclass AppError per failure (each fixes a code + status): NotFoundError (404), ConflictError (409), Unauthorized (401), Forbidden (403) — full hierarchy in → references/production.md (AppError subclasses). secure-coding has the why: error responses must never leak internals (stack traces, SQL, secrets).

Async SQLAlchemy 2.0 (essentials)

python
from datetime import datetime
from uuid import UUID, uuid4

from sqlalchemy import func, select
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column

from app.core.config import get_settings

engine = create_async_engine(str(get_settings().database_url), pool_pre_ping=True)
async_session_factory = async_sessionmaker(engine, expire_on_commit=False)


class Base(DeclarativeBase):
    pass


class User(Base):
    __tablename__ = "users"

    id: Mapped[UUID] = mapped_column(primary_key=True, default=uuid4)
    email: Mapped[str] = mapped_column(unique=True, index=True)
    full_name: Mapped[str]
    hashed_password: Mapped[str]
    created_at: Mapped[datetime] = mapped_column(server_default=func.now())


async def list_users(db: AsyncSession, limit: int, offset: int) -> list[User]:
    result = await db.execute(
        select(User).order_by(User.created_at.desc()).limit(limit).offset(offset)
    )
    return list(result.scalars().all())

Fetch by PK with await db.get(Model, pk), by unique key with .scalar_one_or_none(); eager-load with selectinload (collections) / joinedload (many-to-one). → references/database.md for relationships, N+1 / eager loading, repository, Alembic, pooling.

Show full SKILL.md (410 more words)Show less

Background tasks vs real queues

python
from fastapi import BackgroundTasks


# Good: in-request, non-durable side effect (best-effort email).
@router.post("/signup")
async def signup(background: BackgroundTasks) -> dict[str, str]:
    background.add_task(send_welcome_email, "user@example.com")
    return {"status": "accepted"}

Anything needing retries, durability, or cross-process execution (payment webhooks, large jobs) goes to a real broker (Celery / Arq / Dramatiq), never BackgroundTasks — it runs in-process and dies with the worker, with no retry or visibility.

Testing

Drive the app in-process with httpx.AsyncClient(transport=ASGITransport(app=create_app())) and swap real dependencies via app.dependency_overrides[get_db] = lambda: db_session against a transactional fixture — so every test rolls back. Use pytest-asyncio with asyncio_mode = "auto" (no @pytest.mark.asyncio), and assert secrets never serialize (e.g. assert "hashed_password" not in resp.json()). TDD red→green→refactor. Full fixtures (transactional begin_nested, auth overrides, respx, coverage gate) in → references/testing.md.

Security

Full hardening playbook — argon2 hashing, OAuth2 + JWT (claims validated, algorithms pinned), get_current_user/require_roles RBAC, CORS, shared-store rate limiting, injection, SecretStr + log redaction, security headers, pip-audit — lives in → references/security.md — including the exact argon2.PasswordHasher().hash(pw) and jwt.decode(t, key, algorithms=[...], audience=..., issuer=...) calls. See secure-coding for the language-agnostic theory.

Production

ASGI/worker math, structured JSON logging + request-id, liveness vs readiness probes, graceful shutdown, keyset pagination, caching, ORJSONResponse and proxy headers all live in → references/production.md. See deployment for the Dockerfile and CI/CD pipeline.

Anti-patterns

Anti-patternWhy it breaks → do this
requests (or any blocking call) inside an async def routeBlocks the event loop → use httpx.AsyncClient.
.dict() / from_orm() on a modelPydantic v2: use .model_dump(); .dict()/from_orm are deprecated.
Returning the ORM object with no response_modelLeaks columns + lazy-loads in serializer → declare response_model.
allow_origins=['*'] together with credentialsBrowser rejects it; Starlette blocks it. Pin origins.
Decoding a JWT without checking exp/audForged/replayed tokens. Validate exp/iss/aud + pin alg.
Building the WHERE clause with an f-stringSQLi. Bound params / SQLAlchemy expressions only.
One global session shared by the whole appCross-request data bleed + concurrency bugs. One session per request.
Catching Exception and returning its messageLeaks internals. Log it, return generic 500.
BackgroundTasks for a payment-webhook retryNo durability/retry. Use a real broker.
Skipping mypy --strict because it is noisyStrict catches the bugs FastAPI's runtime won't. Keep it.
Committing inside the handlerLet get_db own commit/rollback; handlers stay thin.
Default-mutable arg / engine built at import timeMutable defaults bite; engine must live in lifespan.

Project grounding

In a project with a 02-DOCS/ layer (harness), read 02-DOCS/wiki/stack/fastapi.md first and stay consistent with it; create or update it with this project's real choices — auth model (JWT/OAuth2 provider, token TTLs), DB session + migration tool, error-envelope shape, settings/secrets approach, deployment target — bump its Updated date, and index it in 02-DOCS/wiki/index.md. No 02-DOCS/? Skip silently. Conventions are recorded, not gated — never block the task on this.

Verify gate: scripts/verify.sh.

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

Files

SKILL.md and 7 other files (scripts, references) in skills/fastapi of ericrisco/rsc-harness.

  • SKILL.md
  • evals/README.md
  • evals/cases.yaml
  • references/database.md
  • references/production.md
  • references/security.md
  • references/testing.md
  • scripts/verify.sh

Open the folder on GitHubat commit e3d5b33

Compare with similar skills

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Fastapi Appccplugins/awesome-claude-code-plugins968—~1.1kAutomated safety check: NotesApache-2.0
Fastapi Prodavila7/claude-code-templates32k8 repos~1.6kAutomated safety check: PassMIT
FastAPI ExpertJeffallan/claude-skills12k—~1.8kAutomated safety check: PassMIT
Backend Fastapi Pythonavibebuilder/claude-prime120—~997Automated safety check: PassMIT

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    32k GitHub starsUsed in 8 repos~1.6k tokens
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  • FastAPI Expert

    Jeffallan/claude-skills

    Builds async Python APIs with FastAPI and Pydantic V2, covering endpoints, JWT authentication, async SQLAlchemy, WebSockets and pytest checks against the OpenAPI docs.

    12k GitHub stars~1.8k tokensUpdated 4 days ago
    Backend & APIsAuto-check passed
  • Backend Fastapi Python

    avibebuilder/claude-prime

    A skill your agent uses for any Python backend work in this project: building FastAPI endpoints, writing service functions, defining Pydantic/SQLModel schemas, running Alembic migrations, or…

    120 GitHub stars~997 tokensUpdated 4 mo ago
    Backend & APIsAuto-check passed
  • Python Fastapi Development

    aiskillstore/marketplace

    Python FastAPI backend development with async patterns, SQLAlchemy, Pydantic, authentication, and production API patterns.

    430 GitHub starsUsed in 3 repos~1.2k tokens
    Backend & APIsAuto-check passed

More from ericrisco/rsc-harness

All 227 skills in this repo
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  • Accessibility

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  • Agent Eval

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  • Analytics

    ericrisco/rsc-harness

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Categories

Questions about Fastapi

What does Fastapi do?

A skill your agent uses when building, reviewing, testing, securing or shipping a FastAPI / async Python service — routers, Pydantic v2 schemas, dependency injection, async SQLAlchemy 2.0…. Fastapi is an agent skill from ericrisco/rsc-harness.0, OAuth2/JWT, ASGITransport tests, production wiring.

When should I use Fastapi?

Fastapi fits situations like: shipping a FastAPI / async Python service — routers; pydantic v2 schemas; dependency injection; async SQLAlchemy 2.0.

How do I install Fastapi in Claude Code?

Run `npx skills add ericrisco/rsc-harness --skill fastapi -a claude-code`. Or copy the skill folder (skills/fastapi in ericrisco/rsc-harness) into .claude/skills/fastapi in your project. Claude Code loads it when a task matches its description.

How do I install Fastapi in Codex?

Run `npx skills add ericrisco/rsc-harness --skill fastapi -a codex`. Or copy the skill folder (skills/fastapi in ericrisco/rsc-harness) into .agents/skills/fastapi in your project. Codex loads it when a task matches its description.

Can I use Fastapi 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 ericrisco/rsc-harness --skill fastapi -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, .gemini/skills/fastapi, .github/skills/fastapi and .opencode/skills/fastapi in your project.

What does Fastapi need to run?

Going by SKILL.md and its folder, Fastapi needs a shell for the scripts in its folder and the command-line tools its instructions call (mypy and pytest). Our summary lists: Python 3; A Bash shell; Docker.

Does Fastapi 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 safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Fastapi use?

Fastapi 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 use?

About 5k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 12k tokens, read only when the agent opens those files.

What are the alternatives to Fastapi?

Skills that share tags, products or a category with Fastapi: Fastcrud (benavlabs/fastcrud, 1.6k stars), Fastapi App (ccplugins/awesome-claude-code-plugins, 968 stars), Fastapi Pro (davila7/claude-code-templates, 32k stars) and FastAPI Expert (Jeffallan/claude-skills, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fastapi?

ericrisco (a GitHub user) maintains it in ericrisco/rsc-harness, which has 167 GitHub stars. The repository holds 227 skills in this directory. The repository was last updated on October 7, 2026.

Source: ericrisco/rsc-harness on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.