fastapi-service

fastapi-service is a skill for Claude Code from hamzaPixl/pixl-ai. It costs 83 tokens per session (453 once invoked), scanned A, original, MIT.

A scaffold for adding one FastAPI service—a Python web API framework—to an existing monorepo, a repository containing several related services or packages. It follows the existing repository's patterns and creates the service's main application layers.

In plain words
What is it for?
Creating domain models, API routes and schemas, database wiring and migrations, configuration, a Dockerfile, and a GitHub Actions workflow for a FastAPI microservice.
Why use it?
It removes much of the repetitive setup needed to add a production-oriented Python service beside existing services. It also keeps the new service aligned with shared libraries, infrastructure, containers, and CI/CD.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the pixl-crew plugin — 93 skills, 14 agents, 6 hooks shipped together

Good fit Creating domain models, API routes and schemas, database wiring and migrations, configuration, a Dockerfile, and a GitHub Actions workflow for a FastAPI microservice.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hamzapixl/pixl-ai/fastapi-service
Install

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.

Any agent
npx skills add hamzaPixl/pixl-ai --skill fastapi-service
Clone the repo
git clone --depth 1 https://github.com/hamzaPixl/pixl-ai

Made for: Claude Code.

Or install pixl-crew, the plugin that ships this one along with the rest of its 93 skills, 14 agents, 6 hooks.

Wrote 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.

agentmods badge for fastapi-service

README.md
[![agentmods](https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/fastapi-service/github.svg)](https://agentmods.dev/skills/hamzapixl/pixl-ai/fastapi-service)
Your own site
<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/fastapi-service"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/fastapi-service/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.

agentmods 80×15 button for fastapi-service

Your own site · 80×15
<a href="https://agentmods.dev/skills/hamzapixl/pixl-ai/fastapi-service"><img src="https://agentmods.dev/badge/skills/hamzapixl/pixl-ai/fastapi-service.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 453 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00083 $0.00453
Opus 5 $0.00042 $0.00227
Sonnet 5 $0.00017 $0.00091
Haiku 4.5 $0.00008 $0.00045

Measured 6d ago against content hash 5b39f9e8c5a3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

fastapi-service 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 6d 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.

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.

packages/crew/skills/fastapi-service/SKILL.md · 58 lines

What it actually says

Overview

Scaffolds a complete FastAPI microservice following monorepo conventions: domain layer (entities, repositories), API endpoints (Pydantic schemas, routes), infrastructure (database, config), Dockerfile, and CI/CD.

Step 1: Discovery

  1. Detect monorepo structure and conventions
  2. Identify existing services for pattern reference
  3. Determine the service's domain (name, entities, relationships)
  4. Check for shared libraries and utilities

Step 2: Domain Layer

  1. Create domain entities with Pydantic models
  2. Define repository interfaces
  3. Add domain events if cross-service communication needed

Step 3: API Layer

  1. Create Pydantic request/response schemas
  2. Build CRUD route handlers with dependency injection
  3. Add authentication and authorization middleware
  4. Wire up OpenAPI documentation

Step 4: Infrastructure

  1. Create SQLAlchemy/database models
  2. Implement repository with database backend
  3. Add configuration loading (environment variables)
  4. Create database migrations

Step 5: Dockerfile

  1. Multi-stage build optimized for Python/uv
  2. Pin base image versions
  3. Non-root user in production

Step 6: CI/CD

  1. GitHub Actions workflow for the new service
  2. Test, lint, typecheck, build stages
  3. Deploy job template for Cloud Run

Step 7: Verify

  • Service starts and responds to health checks
  • CRUD endpoints work correctly
  • Tests pass
  • Typecheck passes
  • Docker build succeeds
Changes

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.

  1. 6d ago First seen · 58 lines · 83 tokens per session scan A 5b39f9e8c5a3

Subscribe to this mod's changes

fastapi-service is a skill published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 83 tokens to every session and 453 once invoked, about $0.0004 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.

Related

Other skills, from other repositories

deploy

Elixir/Phoenix deployment patterns — Dockerfile, fly.toml, runtime.exs, mix release, rel/ overlays. Use when configuring Fly.io, Docker, CI/CD, health checks, or production migrations.

oliver-kriska/claude-elixir-phoenix · 46 tokens

bunjs-production

Use when deploying Bun.js to production, containerizing with Docker, setting up AWS ECS/Fargate, implementing Redis caching, hardening security, or configuring CI/CD pipelines. See bunjs for basics, bunjs-architecture for patterns.

MadAppGang/claude-code · 52 tokens

data-processing

Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data.

NeverSight/learn-skills.dev · 58 tokens

nestjs-monorepo-scaffold

Turborepo + NestJS + Drizzle + BullMQ monorepo scaffolding — project structure, shared types, workspace config, Docker, CI/CD, and new feature bootstrapping.

me-cedric/agent-compass · 46 tokens

enterprise

Enterprise-grade systems with microservices, Kubernetes, Terraform, and AI Native methodology. For multi-feature initiatives spanning a release timeline, combine with /sprint master-plan (v2.1.13) to group features into a single 8-phase sprint container with shared scope/budget and 4 auto-pause triggers…

ww-w-ai/bkit-claude-code · 106 tokens

performing-container-security-scanning-with-trivy

Scan container images, filesystems, and Kubernetes manifests for vulnerabilities, misconfigurations, exposed secrets, and license compliance issues using Aqua Security Trivy with SBOM generation and CI/CD integration.

xalgorix/xalgorix · 48 tokens