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Build apps with the Claude API / Anthropic SDKs (TypeScript, Python, Agent SDK), choosing the right surface and language-specific patterns; not for OpenAI or other providers. USE WHEN code imports anthropic/@anthropic-ai/sdk/claude_agent_sdk or a user asks to use the Claude API or Anthropic Agent SDK.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Sheshiyer/skill-clusters --skill claude-api命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Arcplume runs Grok through the Grok Build CLI's own OAuth-authenticated session (grok login) for image generation, with strict preflight validation, secret-safe handling, and headless CLI-driven execution -- no separate XAI_API_KEY billing. Video falls back to the billed xAI API. USE WHEN a user wants to generate an image via a locally logged-in Grok Build CLI session, e.g. 'generate an image with grok', 'use grok build', or 'use my logged-in grok session'.
Shared reference for the Selemene cluster: the two report surfaces (deterministic Rust reports vs. narrative witness-pipeline readings), the @selemene/bridge CLI contract, the output manifest format, and non-prescriptive witnessing tone. USE WHEN deciding which Selemene surface to invoke or when routing between birth/compatibility/transit reports and solo/dyadic readings.
Route Selemene Engine tasks to the right surface: deterministic reports (birth/compatibility/transit) via selemene-core and the @selemene/bridge CLI, or narrative witness readings via selemene-report. USE WHEN the user wants anything under the Selemene/Noesis umbrella but has not named the exact surface.
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基于 SOC 职业分类
| name | claude-api |
| description | Build apps with the Claude API / Anthropic SDKs (TypeScript, Python, Agent SDK), choosing the right surface and language-specific patterns; not for OpenAI or other providers. USE WHEN code imports anthropic/@anthropic-ai/sdk/claude_agent_sdk or a user asks to use the Claude API or Anthropic Agent SDK. |
| cluster | ai-agents-meta |
| version | 1.0.0 |
| origin | antigravity-awesome-skills (MIT) |
| risk | unknown |
| source | https://github.com/anthropics/skills |
| date_added | 2026-03-21 |
| license | Complete terms in LICENSE.txt |
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.
anthropic, @anthropic-ai/sdk, or related Claude SDK packages.Unless the user requests otherwise:
For the Claude model version, please use Claude Opus 4.6, which you can access via the exact model string claude-opus-4-6. 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
Before reading code examples, determine which language the user is working in:
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/*.scalabuild.sbtjava/*.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/If multiple languages detected (e.g., both Python and TypeScript files):
If language can't be inferred (empty project, no source files, or unsupported language):
If unsupported language detected (Rust, Swift, C++, Elixir, etc.):
curl/ and note that community SDKs may existIf user needs cURL/raw HTTP examples, read from curl/.
| Language | Tool Runner | Agent SDK | Notes |
|---|---|---|---|
| Python | Yes (beta) | Yes | Full support — @beta_tool decorator |
| TypeScript | Yes (beta) | Yes | Full support — betaZodTool + Zod |
| Java | Yes (beta) | No | Beta tool use with annotated classes |
| Go | Yes (beta) | No | BetaToolRunner in toolrunner pkg |
| Ruby | Yes (beta) | No | BaseTool + tool_runner in beta |
| cURL | N/A | N/A | Raw HTTP, no SDK features |
| C# | No | No | Official SDK |
| PHP | No | No | Official SDK |
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.
| 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 |
| AI agent with file/web/terminal access | Agent | Agent SDK | Built-in tools, safety, and MCP support |
| Agentic coding assistant | Agent | Agent SDK | Designed for this use case |
| Want built-in permissions and guardrails | Agent | Agent SDK | Safety features included |
Note: The Agent SDK is for when you want built-in file/web/terminal tools, permissions, and MCP out of the box. If you want to build an agent with your own tools, Claude API is the right choice — use the tool runner for automatic loop handling, or the manual loop for fine-grained control (approval gates, custom logging, conditional execution).
What does your application need?
1. Single LLM call (classification, summarization, extraction, Q&A)
└── Claude API — one request, one response
2. Does Claude need to read/write files, browse the web, or run shell commands
as part of its work? (Not: does your app read a file and hand it to Claude —
does Claude itself need to discover and access files/web/shell?)
└── Yes → Agent SDK — built-in tools, don't reimplement them
Examples: "scan a codebase for bugs", "summarize every file in a directory",
"find bugs using subagents", "research a topic via web search"
3. Workflow (multi-step, code-orchestrated, with your own tools)
└── Claude API with tool use — you control the loop
4. Open-ended agent (model decides its own trajectory, your own tools)
└── Claude API agentic loop (maximum flexibility)
Before choosing the agent tier, check all four criteria:
If the answer is "no" to any of these, stay at a simpler tier (single call or workflow).
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), and Token Counting feed into or support Messages API requests.
| Model | Model ID | Context | Input $/1M | Output $/1M |
|---|---|---|---|---|
| Claude Opus 4.6 | claude-opus-4-6 | 200K (1M beta) | $5.00 | $25.00 |
| Claude Sonnet 4.6 | claude-sonnet-4-6 | 200K (1M beta) | $3.00 | $15.00 |
| Claude Haiku 4.5 | claude-haiku-4-5 | 200K | $1.00 | $5.00 |
ALWAYS use claude-opus-4-6 unless the user explicitly names a different model. This is non-negotiable. Do not use claude-sonnet-4-6, claude-sonnet-4-5, 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.
CRITICAL: Use only the exact model ID strings from the table above — they are complete as-is. Do not append date suffixes. For example, use claude-sonnet-4-5, never claude-sonnet-4-5-20250514 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.
A note: if any of the model strings above look unfamiliar to you, that's to be expected — that just means they were released after your training data cutoff. Rest assured they are real models; we wouldn't mess with you like that.
Opus 4.6 — Adaptive thinking (recommended): Use thinking: {type: "adaptive"}. Claude dynamically decides when and how much to think. No budget_tokens needed — budget_tokens is deprecated on Opus 4.6 and Sonnet 4.6 and must not be used. Adaptive thinking also automatically enables interleaved thinking (no beta header needed). When the user asks for "extended thinking", a "thinking budget", or budget_tokens: always use Opus 4.6 with thinking: {type: "adaptive"}. The concept of a fixed token budget for thinking is deprecated — adaptive thinking replaces it. Do NOT use budget_tokens and do NOT switch to an older model.
Effort parameter (GA, no beta header): Controls thinking depth and overall token spend via output_config: {effort: "low"|"medium"|"high"|"max"} (inside output_config, not top-level). Default is high (equivalent to omitting it). max is Opus 4.6 only. Works on Opus 4.5, Opus 4.6, and Sonnet 4.6. Will error on Sonnet 4.5 / Haiku 4.5. Combine with adaptive thinking for the best cost-quality tradeoffs. Use low for subagents or simple tasks; max for the deepest reasoning.
Sonnet 4.6: Supports adaptive thinking (thinking: {type: "adaptive"}). budget_tokens is deprecated on Sonnet 4.6 — use adaptive thinking instead.
Older models (only if explicitly requested): If the user specifically asks for Sonnet 4.5 or another older model, use thinking: {type: "enabled", budget_tokens: N}. budget_tokens must be less than max_tokens (minimum 1024). Never choose an older model just because the user mentions budget_tokens — use Opus 4.6 with adaptive thinking instead.
Beta, Opus 4.6 only. For long-running conversations that may exceed the 200K context window, enable server-side compaction. The API automatically summarizes earlier context when it approaches the trigger threshold (default: 150K tokens). Requires beta header compact-2026-01-12.
Critical: Append response.content (not just the text) back to your messages on every turn. Compaction blocks in the response must be preserved — the API uses them to replace the compacted history on the next request. Extracting only the text string and appending that will silently lose the compaction state.
See {lang}/claude-api/README.md (Compaction section) for code examples. Full docs via WebFetch in shared/live-sources.md.
After detecting the language, read the relevant files based on what the user needs:
Single text classification/summarization/extraction/Q&A:
→ Read only {lang}/claude-api/README.md
Chat UI or real-time response display:
→ Read {lang}/claude-api/README.md + {lang}/claude-api/streaming.md
Long-running conversations (may exceed context window):
→ Read {lang}/claude-api/README.md — see Compaction section
Function calling / tool use / agents:
→ Read {lang}/claude-api/README.md + shared/tool-use-concepts.md + {lang}/claude-api/tool-use.md
Batch processing (non-latency-sensitive):
→ Read {lang}/claude-api/README.md + {lang}/claude-api/batches.md
File uploads across multiple requests:
→ Read {lang}/claude-api/README.md + {lang}/claude-api/files-api.md
Agent with built-in tools (file/web/terminal):
→ Read {lang}/agent-sdk/README.md + {lang}/agent-sdk/patterns.md
Read the language-specific Claude API folder ({language}/claude-api/):
{language}/claude-api/README.md — Read this first. Installation, quick start, common patterns, error handling.shared/tool-use-concepts.md — Read when the user needs function calling, code execution, memory, or structured outputs. Covers conceptual foundations.{language}/claude-api/tool-use.md — Read for language-specific tool use code examples (tool runner, manual loop, code execution, memory, structured outputs).{language}/claude-api/streaming.md — Read when building chat UIs or interfaces that display responses incrementally.{language}/claude-api/batches.md — Read when processing many requests offline (not latency-sensitive). Runs asynchronously at 50% cost.{language}/claude-api/files-api.md — Read when sending the same file across multiple requests without re-uploading.shared/error-codes.md — Read when debugging HTTP errors or implementing error handling.shared/live-sources.md — WebFetch URLs for fetching the latest official documentation.Note: For Java, Go, Ruby, C#, PHP, and cURL — these have a single file each covering all basics. Read that file plus
shared/tool-use-concepts.mdandshared/error-codes.mdas needed.
Read the language-specific Agent SDK folder ({language}/agent-sdk/). Agent SDK is available for Python and TypeScript only.
{language}/agent-sdk/README.md — Installation, quick start, built-in tools, permissions, MCP, hooks.{language}/agent-sdk/patterns.md — Custom tools, hooks, subagents, MCP integration, session resumption.shared/live-sources.md — WebFetch URLs for current Agent SDK docs.Use WebFetch to get the latest documentation when:
Live documentation URLs are in shared/live-sources.md.
thinking: {type: "adaptive"} — do NOT use budget_tokens (deprecated on both Opus 4.6 and Sonnet 4.6). For older models, budget_tokens must be less than max_tokens (minimum 1024). This will throw an error if you get it wrong.output_config.format) or system prompt instructions to control response format instead.max_tokens, but the SDKs require streaming for large max_tokens to avoid HTTP timeouts. Use .stream() with .get_final_message() / .finalMessage().input fields (e.g., Unicode or forward-slash escaping). Always parse tool inputs with json.loads() / JSON.parse() — never do raw string matching on the serialized input.output_config: {format: {...}} instead of the deprecated output_format parameter on messages.create(). This is a general API change, not 4.6-specific.stream.finalMessage() instead of wrapping .on() events in new Promise(); use typed exception classes (Anthropic.RateLimitError, etc.) instead of string-matching error messages; use SDK types (Anthropic.MessageParam, Anthropic.Tool, Anthropic.Message, etc.) instead of redefining equivalent interfaces.Anthropic.MessageParam for messages, Anthropic.Tool for tool definitions, Anthropic.ToolUseBlock / Anthropic.ToolResultBlockParam for tool results, Anthropic.Message for responses. Defining your own interface ChatMessage { role: string; content: unknown } duplicates what the SDK already provides and loses type safety.python-docx, python-pptx, matplotlib, pillow, and pypdf pre-installed. Claude can generate formatted files (DOCX, PDF, charts) and return them via the Files API — consider this for "report" or "document" type requests instead of plain stdout text.