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imankha
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api-guidelines

Standardize FastAPI backend patterns for endpoints, R2 storage, and Modal GPU processing.

Updated Nov 5, 2025
Search Tags:#security#fastapi#backend#api-patterns#r2-storage#gpu-processing
One-click install
npx skills add https://github.com/imankha/video-editor --skill api-guidelines
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: api-guidelines
Source: https://github.com/imankha/video-editor/tree/main/src/backend/.claude/skills/api-guidelines
Command: npx skills add https://github.com/imankha/video-editor --skill api-guidelines

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill standardizes FastAPI backend patterns and best practices to streamline endpoint design, data persistence, and storage strategies across projects.

Core Features & Use Cases

  • Endpoint Design: Guidelines for clean, scalable FastAPI endpoints with proper input validation and error handling.
  • Storage & Processing: Best practices for using R2 storage and coordinating GPU-accelerated tasks via Modal.
  • Governance & Quality: References and rules to maintain secure, maintainable backend code.

Quick Start

Apply these guidelines when you are creating new endpoints, integrating R2 storage, or configuring Modal GPU processing in your FastAPI project.

Frequently Asked Questions about api-guidelines

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What are the best practices for structuring FastAPI endpoints and error handling?▼

FastAPI endpoint best practices involve standardizing input validation and applying consistent error handling patterns to ensure clean, scalable API design across projects. These guidelines help maintain secure and maintainable backend code.

How do I integrate R2 storage with my FastAPI backend?▼

To integrate R2 storage with a FastAPI backend, apply standardized storage handling patterns that define how to structure data persistence and manage object storage strategies within your application workflows.

How do I coordinate GPU processing tasks using Modal in a FastAPI application?▼

Modal coordinates GPU-accelerated processing workflows in a FastAPI application by following specific configuration guidelines that offload and manage intensive compute tasks remotely from your backend endpoints.

Do I need external software or dependencies to apply these FastAPI backend patterns?▼

No external software installation is required to apply these FastAPI backend patterns. The guidelines function by referencing rules directly from their internal directory to govern secure, maintainable code quality.

When should I use standardized API patterns for FastAPI backend development?▼

Standardized API patterns should be used when building new endpoints, integrating R2 storage, or configuring GPU processing to solve problems with inconsistent backend design and streamline project scalability.

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