claude-api

Implement Claude API integrations with provider-specific SDK usage and caching.

Updated May 15, 2026
One-click install
npx skills add https://github.com/lth0/codexSkill --skill claude-api-lth0
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: claude-api
Source: https://github.com/lth0/codexSkill/tree/main/skills/agents/claude-api
Command: npx skills add https://github.com/lth0/codexSkill --skill claude-api-lth0

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you design and implement Claude (Anthropic) API integrations that work correctly across common surfaces (single-call, streaming, tool use, and managed agents) while enforcing best practices like provider consistency, prompt caching, and robust tool-result handling.

Core Features & Use Cases

  • Claude API app construction: Guides how to call POST /v1/messages correctly and choose the right request surface for your workflow.
  • Streaming & UI-ready output: Provides streaming handling guidance for long responses and real-time interfaces.
  • Tool use & agentic loops: Covers function calling patterns, tool runner vs manual loops, and safe continuation logic.
  • Prompt caching optimization: Teaches prefix-stability rules, cache breakpoint placement, and how to verify cache hits.
  • Extended thinking & effort control: Recommends adaptive thinking for Claude 4.6 and explains effort tuning.
  • Managed Agents (beta) workflows: Explains the agent → session flow, event streaming/steering, and integration constraints.

Quick Start

Use the claude-api skill when you want to add Claude API support to an app by using the official Anthropic SDK for your language, enabling prompt caching where appropriate, and implementing tool-use handling (streaming and tool-result round-trips) if your feature requires function calls.

Frequently Asked Questions about claude-api

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

FAQPage Schema
How do I implement tool use and function calling with the Claude API?

To implement tool use with the Claude API, you need to construct function calling patterns using tool runners or manual loops, ensuring safe tool-result continuation logic without mixing incompatible SDK providers. This skill provides production-ready patterns for agentic loops and streaming tool round-trips.

What is the best way to optimize prompt caching when using the Anthropic API?

Prompt caching optimization in the Anthropic API requires maintaining prefix-stability rules, placing cache breakpoints correctly, and verifying cache hits. This skill guides you through caching verification to ensure your application correctly leverages prompt caching for reduced latency.

How does streaming work with the Claude API for real-time chat UIs?

Streaming with the Claude API works by handling long responses and real-time interfaces through the official Anthropic SDK. This skill provides streaming handling guidance to build UI-ready output that processes continuous data flows correctly across single-call and agentic workflows.

Can I use Managed Agents beta workflows with the Claude API?

Yes, you can use Managed Agents beta workflows with the Claude API by following the agent to session flow, event streaming, and steering integration constraints. This skill explains how to implement these beta features while maintaining provider-specific SDK usage and adaptive thinking defaults.

Why does my Claude API application fail when mixing different SDK abstractions?

Claude API applications fail when mixing incompatible providers or SDK abstractions because the API requires strict provider consistency and correct model ID usage. This skill enforces provider-specific SDK usage and safe tool-result continuation to prevent integration failures.

Do I need adaptive thinking defaults to build Claude API apps correctly?

Yes, building Claude API apps correctly requires adaptive thinking defaults, particularly for Claude 4.6 models, along with effort tuning. This skill recommends adaptive thinking configurations and explains how to satisfy strict requirements for model ID usage and API surface selection.