--- name: Claude API slug: claude-api category: AI Engineering description: Claude API provides reference documentation for the Anthropic SDK, covering model IDs, pricing, parameters, streaming, tool use, MCP, agents, caching, token counting, and model migration. Use it before writing Claude integration code or when asked about Claude/Anthropic APIs, models, or limits. github: "https://github.com/anthropics/skills/tree/main/skills/claude-api" language: Python stars: 168596 forks: 20085 install: "npx degit https://github.com/anthropics/skills/tree/main/skills/claude-api ~/.claude/skills/claude-api" installs_to: ~/.claude/skills/claude-api source_path: skills/claude-api/SKILL.md collection_size: 18 category_size: 2451 collection_url: "https://dirskills.com/collections/anthropics/skills" added: 2026-08-13T07:35:38.974Z last_synced: 2026-08-13T07:35:38.974Z canonical_url: "https://dirskills.com/skills/claude-api" --- # Claude API Claude API provides reference documentation for the Anthropic SDK, covering model IDs, pricing, parameters, streaming, tool use, MCP, agents, caching, token counting, and model migration. Use it before writing Claude integration code or when asked about Claude/Anthropic APIs, models, or limits. **Install:** ```bash npx degit https://github.com/anthropics/skills/tree/main/skills/claude-api ~/.claude/skills/claude-api ``` ## README # Building LLM-Powered Applications with Claude This skill helps you build LLM-powered applications with Claude. Choose the right surface based on your needs, detect the project language, then read the relevant language-specific documentation. ## Before You Start Scan the target file (or, if no target file, the prompt and project) for non-Anthropic provider markers — `import openai`, `from openai`, `langchain_openai`, `OpenAI(`, `gpt-4`, `gpt-5`, file names like `agent-openai.py` or `*-generic.py`, or any explicit instruction to keep the code provider-neutral. If you find any, stop and tell the user that this skill produces Claude/Anthropic SDK code; ask whether they want to switch the file to Claude or want a non-Claude implementation. Do not edit a non-Anthropic file with Anthropic SDK calls. ## Output Requirement When the user asks you to add, modify, or implement a Claude feature, your code must call Claude through one of: 1. **The official Anthropic SDK** for the project's language (`anthropic`, `@anthropic-ai/sdk`, `com.anthropic.*`, etc.). This is the default whenever a supported SDK exists for the project. 2. **Raw HTTP** (`curl`, `requests`, `fetch`, `httpx`, etc.) — only when the user explicitly asks for cURL/REST/raw HTTP, the project is a shell/cURL project, or the language has no official SDK. Never mix the two — don't reach for `requests`/`fetch` in a Python or TypeScript project just because it feels lighter. Never fall back to OpenAI-compatible shims. **Never guess SDK usage.** Function names, class names, namespaces, method signatures, and import paths must come from explicit documentation — either the `{lang}/` files in this skill or the official SDK repositories or documentation links listed in `shared/live-sources.md`. If the binding you need is not explicitly documented in the skill files, WebFetch the relevant SDK repo from `shared/live-sources.md` before writing code. Do not infer Ruby/Java/Go/PHP/C# APIs from cURL shapes or from another language's SDK. **If WebFetch or repository access fails** (network restricted, timeouts, clone blocked): do not keep retrying — write code from the patterns and namespace/package tables in the `{lang}/` file, run the compiler or interpreter on it, and iterate on the error output. For statically-typed SDKs (C#, Java, Go) a compile-fix loop against local errors reaches working code faster than blocked network research. ## Defaults Unless the user requests otherwise: For the Claude model version, please use Claude Opus 5, which you can access via the exact model string `claude-opus-5`. Please default to using adaptive thinking (`thinking: {type: "adaptive"}`) for anything remotely complicated. And finally, please default to streaming for any request that may involve long input, long output, or high `max_tokens` — it prevents hitting request timeouts. Use the SDK's `.get_final_message()` / `.finalMessage()` helper to get the complete response if you don't need to handle individual stream events ## ⚠️ API Drift — Your Training Prior May Be Stale Several common Claude API shapes changed in 2025–2026. If you recall a pattern from training, verify it against the `{lang}/` files in this skill before writing — the rows below are the most frequent drift points: | Area | Stale prior | Current API | |---|---|---| | Extended thinking | `thinking: {type: "enabled", budget_tokens: N}` | On Claude 4.6+ models: `thinking: {type: "adaptive"}`. `budget_tokens` is deprecated on Opus 4.6 / Sonnet 4.6 and **rejected with a 400** on Fable 5 / Sonnet 5 / Opus 5 / 4.8 / 4.7. Pre-4.6 models still use `budget_tokens`. | | Web search / web fetch tool type | `web_search_20250305`, `web_fetch_20250910` | `web_search_20260209`, `web_fetch_20260209` (dynamic filtering) on Opus 5/4.8/4.7/4.6, Sonnet 5, and Sonnet 4.6. Older models keep the basic variants; on Vertex AI only basic `web_search_20250305` is available (web fetch is not on Vertex) — see the Server Tools QR below. | | PHP parameter names | snake_case wire names as named args (`max_tokens`) | Top-level named args are camelCase (`maxTokens`). Nested array keys vary by feature (e.g. `'taskBudget'`, `'skillID'`, `'mcp_server_name'`) — copy the exact key from the documented example; do not bulk-convert. | | Managed Agents credentials | Keep secrets host-side via custom tools (the only option before vaults shipped) | Vault `environment_variable` credentials — stored by Anthropic, substituted at egress, never visible in the sandbox (`shared/managed-agents-tools.md` → Vaults). Host-side custom tools remain the fallback for self-hosted sandboxes. | The `{lang}/` files in this skill are authoritative over recalled patterns. --- ## Subcommands If the User Request at the bottom of this prompt is a bare subcommand string (no prose), search every **Subcommands** table in this document — including any in sections appended below — and follow the matching Action column directly. This lets users invoke specific flows via `/claude-api `. If no table in the document matches, treat the request as normal prose. | Subcommand | Action | |---|---| | `migrate` | Migrate existing Claude API code to a newer model. **Read `shared/model-migration.md` immediately** and follow it in order: Step 0 (confirm scope — ask which files/directories before any edit), Step 1 (classify each file), then the per-target breaking-changes section. Do not summarize the guide — execute it. If the user did not name a target model, ask which model to migrate to in the same turn as the scope question. | --- ## Language Detection Before reading code examples, determine which language the user is working in: 1. **Look at project files** to infer the language: - `*.py`, `requirements.txt`, `pyproject.toml`, `setup.py`, `Pipfile` → **Python** — read from `python/` - `*.ts`, `*.tsx`, `package.json`, `tsconfig.json` → **TypeScript** — read from `typescript/` - `*.js`, `*.jsx` (no `.ts` files present) → **TypeScript** — JS uses the same SDK, read from `typescript/` - `*.java`, `pom.xml`, `build.gradle` → **Java** — read from `java/` - `*.kt`, `*.kts`, `build.gradle.kts` → **Java** — Kotlin uses the Java SDK, read from `java/` - `*.scala`, `build.sbt` → **Java** — Scala uses the Java SDK, read from `java/` - `*.go`, `go.mod` → **Go** — read from `go/` - `*.rb`, `Gemfile` → **Ruby** — read from `ruby/` - `*.cs`, `*.csproj` → **C#** — read from `csharp/` - `*.php`, `composer.json` → **PHP** — read from `php/` 2. **If multiple languages detected** (e.g., both Python and TypeScript files): - Check which language the user's current file or question relates to - If still ambiguous, ask: "I detected both Python and TypeScript files. Which language are you using for the Claude API integration?" 3. **If language can't be inferred** (empty project, no source files, or unsupported language): - Use AskUserQuestion with options: Python, TypeScript, Java, Go, Ruby, cURL/raw HTTP, C#, PHP - If AskUserQuestion is unavailable, default to Python examples and note: "Showing Python examples. Let me know if you need a different language." 4. **If unsupported language detected** (Rust, Swift, C++, Elixir, etc.): - Suggest cURL/raw HTTP examples from `curl/` and note that community SDKs may exist - Offer to show Python or TypeScript examples as reference implementations 5. **If user needs cURL/raw HTTP examples**, read from `curl/`. ### Language-Specific Feature Support Every SDK language above supports both the beta Tool Runner and Managed Agents (beta) — Python (`@beta_tool` decorator), TypeScript (`betaZodTool` + Zod), Java (annotated classes), Go (`BetaToolRunner` in the `toolrunner` pkg), Ruby (`BaseTool` + `tool_runner`), C# (`BetaToolRunner` + raw JSON schema), PHP (`BetaRunnableTool` + `toolRunner()`); code entry points are in the Tool Use Patterns quick reference below. cURL is raw HTTP (no SDK features) and supports Managed Agents. > **Managed Agents code examples**: see the reading guide in the `## Managed Agents (Beta)` section below. --- ## Which Surface Should I Use? > **Start simple.** Default to the simplest tier that meets your needs. Single API calls and workflows handle most use cases — only reach for agents when the task genuinely requires open-ended, model-driven exploration. "Simplest" means the least code you own: for a hosted, scheduled, or memory-backed agent, Managed Agents is usually the simplest option (no loop code, no state files, no scheduler), even though it's a bigger platform. | Use Case | Tier | Recommended Surface | Why | | ----------------------------------------------- | --------------- | ------------------------- | ------------------------------------------------------------ | | Classification, summarization, extraction, Q&A | Single LLM call | **Claude API** | One request, one response | | Batch processing or embeddings | Single LLM call | **Claude API** | Specialized endpoints | | Multi-step pipelines with code-controlled logic | Workflow | **Claude API + tool use** | You orchestrate the loop | | Custom agent with your own tools | Agent | **Claude API + tool use** | Maximum flexibility | | Server-managed stateful agent with workspace | Agent | **Managed Agents** | Anthropic runs the loop and hosts the tool-execution sandbox | | Persisted, versioned agent configs | Agent | **Managed Agents** | Agents are stored objects; sessions pin to a version | | Long-running multi-turn agent with file mounts | Agent | **Managed Agents** | Per-session containers, SSE event stream, Skills + MCP | | Agent that runs on a schedule (cron, "every night") | Agent | **Managed Agents** — scheduled deployments | Deployments fire sessions autonomously; no client-side scheduler | > **Note:** Managed Agents is the right choice when you want Anthropic to run the agent loop *and* host the container where tools execute — file ops, bash, code execution all run in the per-session workspace. If you want to host the compute yourself or run your own custom tool runtime, Claude API + tool use is the right choice — use the tool runner for the agentic loop — its per-turn hooks still give you approval gates, logging, error interception, and conditional execution (see `shared/tool-use-concepts.md`) — or the manual loop when you want to own the entire loop yourself. > **Cloud-provider access.** **Claude Platform on AWS** is Anthropic-operated with same-day API parity — see `shared/claude-platform-on-aws.md` for client setup. For per-feature availability on **Claude Platform on AWS**, **Amazon Bedrock**, **Google Vertex AI**, and **Microsoft Foundry**, see `shared/platform-availability.md` — that table is the single source of truth in this skill; do not infer availability from anywhere else. ### Building an Agent: Four Approaches Once you've decided you actually need an agent (open-ended, model-driven tool use), there are four distinct ways to build one. Two independent questions separate them: **who supplies the harness** (the agent loop + context management) and **who supplies the deployment** (the infra the agent runs on). The Tool Runner and the Claude Agent SDK both supply a *harness only* — you still host and deploy them yourself — which is why they're easy to conflate. Managed Agents (CMA) is the only option that supplies **both** the harness *and* managed deployment; the manual loop supplies neither. | # | Approach | You write | Harness & deployment | Tools available | Use when | |---|----------|-----------|----------------------|-----------------|----------| | 1 | **Claude API — manual loop** | The `while stop_reason == "tool_use"` loop yourself | You build the harness; you host | Only tools you define | You want to own the *entire* loop — no beta dependency, or a control flow the Tool Runner's per-turn hooks don't fit | | 2 | **Claude API — Tool Runner** (`client.beta.messages.tool_runner` + `@beta_tool` / `betaZodTool`) | Just the tool functions | SDK supplies the loop (**harness only**); you host | Only tools you define | A custom-tool agent without hand-writing the loop (most cases). Per-turn hooks still give you approval gates, error interception, result modification (e.g. `cache_control`), retries, streaming, and compaction | | 3 | **Managed Agents** (REST, beta) | Agent config + your tool results | Anthropic supplies the harness **and** hosts a per-session sandbox (**harness + deployment**) | Anthropic-hosted sandbox (bash, files, code exec) + Skills/MCP + your tools | You want Anthropic to run the loop *and* host the per-session workspace; persisted/versioned configs; long-running sessions | | 4 | **Claude Agent SDK** — *separate product* (`claude-agent-sdk` / `@anthropic-ai/claude-agent-sdk`) | A prompt + options | SDK supplies the Claude Code harness + built-in tools (**harness only**); you host | Built-in Read/Write/Edit/Bash/Glob/Grep/WebSearch/WebFetch + MCP + subagents | You want a batteries-included coding/filesystem agent running on your own infra | The harness/deployment split is the key mental model: options 1, 2, and 4 all **leave deployment to you**; only option 3 (CMA) adds managed deployment. Options 1–3 are what this skill generates; option 4 is a different library with its own docs — see the disambiguation below. > **Tool Runner ≠ Claude Agent SDK.** These sound alike but are different packages: > - **Tool Runner** is part of the regular Anthropic API SDK (`anthropic` / `@anthropic-ai/sdk`), reached via `client.beta.messages.tool_runner`. It automates the request → execute → loop cycle *for tools you define*. No built-in tools, no filesystem access, no sandbox — you supply every tool and host the compute. It is option 2 above, a thin helper over `POST /v1/messages`. > - **Claude Agent SDK** (`claude-agent-sdk` / `@anthropic-ai/claude-agent-sdk`) is Claude Code packaged as a library. It ships built-in tools (file read/write/edit, bash, grep, web search), the full agent loop, context management, hooks, subagents, permissions, and sessions. You call `query(prompt, options)` and it drives everything. > > Both are **harness-only — you host and deploy them.** The difference is scope of harness: the Tool Runner loops over tools *you* define (with per-turn hooks for approval, interception, result modification, and retries — but no built-in tools); the Agent SDK is the full Claude Code harness with built-in tools. Neither provides managed deployment — that's what **Managed Agents (CMA)** adds (Anthropic hosts the loop and a per-session sandbox). > > **This skill covers the Claude API and Managed Agents (options 1–3); it does not generate Claude Agent SDK code.** If the user actually wants the Claude Agent SDK, point them to its docs (`code.claude.com/docs/en/agent-sdk`) — don't substitute the API Tool Runner for it, or vice-versa. ### Should I Build an Agent? Before choosing the agent tier, check all four criteria: - **Complexity** — Is the task multi-step and hard to fully specify in advance? (e.g., "turn this design doc into a PR" vs. "extract the title from this PDF") - **Value** — Does the outcome justify higher cost and latency? - **Viability** — Is Claude capable at this task type? - **Cost of error** — Can errors be caught and recovered from? (tests, review, rollback) If the answer is "no" to any of these, stay at a simpler tier (single call or workflow). --- ## Architecture Everything goes through `POST /v1/messages`. Tools and output constraints are features of this single endpoint — not separate APIs. **User-defined tools** — You define tools (via decorators, Zod schemas, or raw JSON), and the SDK's tool runner handles calling the API, executing your functions, and looping until Claude is done. For full control, you can write the loop manually. **Server-side tools** — Anthropic-hosted tools that run on Anthropic's infrastructure. Code execution is fully server-side (declare it in `tools`, Claude runs code automatically). Computer use can be server-hosted or self-hosted. **Structured outputs** — Constrains the Messages API response format (`output_config.format`) and/or tool parameter validation (`strict: true`). The recommended approach is `client.messages.parse()` which validates responses against your schema automatically. Note: the old `output_format` parameter is deprecated; use `output_config: {format: {...}}` on `messages.create()`. **Supporting endpoints** — Batches (`POST /v1/messages/batches`), Files (`POST /v1/files`), Token Counting (`POST /v1/messages/count_tokens` — see `shared/token-counting.md`), and Models (`GET /v1/models`, `GET /v1/models/{id}` — live capability/context-window discovery) feed into or support Messages API requests. --- ## Current Models (cached: 2026-06-24) | Model | Model ID | Context | Input $/1M | Output $/1M | | ----------------- | ------------------- | -------------- | ---------- | ----------- | | Claude Fable 5 | `claude-fable-5` | 1M | $10.00 | $50.00 | | Claude Mythos 5 (Project Glasswing only) | `claude-mythos-5` | 1M | $10.00 | $50.00 | | Claude Opus 5 | `claude-opus-5` | 1M | $5.00 | $25.00 | | Claude Opus 4.8 | `claude-opus-4-8` | 1M | $5.00 | $25.00 | | Claude Opus 4.7 | `claude-opus-4-7` | 1M | $5.00 | $25.00 | | Claude Opus 4.6 | `claude-opus-4-6` | 1M | $5.00 | $25.00 | | Claude Sonnet 5 | `claude-sonnet-5` | 1M | $3.00 ($2.00 intro through 2026-08-31) | $15.00 ($10.00 intro) | | Claude Sonnet 4.6 | `claude-sonnet-4-6` | 1M | $3.00 | $15.00 | | Claude Haiku 4.5 | `claude-haiku-4-5` | 200K | $1.00 | $5.00 | **Partner pricing:** The prices above are Anthropic first-party API rates — they also apply to Claude on Microsoft Foundry, which is billed through the Microsoft Marketplace at standard API rates. Claude on Amazon Bedrock and Vertex AI is partner-operated with separate pricing — see [Bedrock](https://aws.amazon.com/bedrock/pricing/) or [Vertex AI](https://cloud.google.com/vertex-ai/generative-ai/pricing#claude-models). For WebFetch, use the Pricing row in `shared/live-sources.md`. **ALWAYS use `claude-opus-5` unless the user explicitly names a different model.** This is non-negotiable. Do not use `claude-sonnet-5`, `claude-sonnet-4-6`, or any other model unless the user literally says "use sonnet" or "use haiku". Never downgrade for cost — that's the user's decision, not yours. Use `claude-fable-5` only when the user explicitly asks for Claude Fable 5, "fable", or Anthropic's most capable model — it has different API behavior than the Opus family (see below) and pricing that exceeds Opus-tier. **Use only the exact model ID strings from the table — they are complete as-is; never append date suffixes** (`claude-sonnet-4-6`, never `claude-sonnet-4-6-20251114` or any other date-suffixed variant you might recall from training data). If the user requests an older model not in the table (e.g., "opus 4.5", "sonnet 3.7"), read `shared/models.md` for the exact ID — do not construct one yourself. ### Claude Fable 5 (`claude-fable-5`) — most capable widely released model Claude Fable 5 is Anthropic's most capable widely released model, for the most demanding reasoning and long-horizon agentic work; everything below also applies to **Claude Mythos 5** (`claude-mythos-5`, Project Glasswing — same capabilities, pricing, and API surface; successor to the invitation-only `claud