Claude Api

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 4.8, which you can access via the exact model string claude-opus-4-8. 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 / Opus 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 4.8/4.7/4.6 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. |

The {lang}/ files in this skill are authoritative over recalled patterns.

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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. |

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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/

1. 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?"

1. 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."

1. 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

1. If user needs cURL/raw HTTP examples, read from curl/.

Language-Specific Feature Support

| Language | Tool Runner | Managed Agents | Notes | | ---------- | ----------- | -------------- | ------------------------------------- | | Python | Yes (beta) | Yes (beta) | Full support — @beta_tool decorator | | TypeScript | Yes (beta) | Yes (beta) | Full support — betaZodTool + Zod | | Java | Yes (beta) | Yes (beta) | Beta tool use with annotated classes | | Go | Yes (beta) | Yes (beta) | BetaToolRunner in toolrunner pkg | | Ruby | Yes (beta) | Yes (beta) | BaseTool + tool_runner in beta | | C# | Yes (beta) | Yes (beta) | BetaToolRunner + raw JSON schema | | PHP | Yes (beta) | Yes (beta) | BetaRunnableTool + toolRunner() | | cURL | N/A | Yes (beta) | Raw HTTP, no SDK features |

> Managed Agents code examples: dedicated language-specific READMEs are provided for Python, TypeScript, Go, Ruby, PHP, Java, and cURL ({lang}/managed-agents/README.md, curl/managed-agents.md). Read your language's README plus the language-agnostic shared/managed-agents-*.md concept files. Agents are persistent — create once, reference by ID. Store the agent ID returned by agents.create and pass it to every subsequent sessions.create; do not call agents.create in the request path. The Anthropic CLI (ant) is one convenient way to create agents and environments from version-controlled YAML — see shared/anthropic-cli.md. If a binding you need isn't shown in the README, WebFetch the relevant entry from shared/live-sources.md rather than guess. C# has beta Managed Agents support via client.Beta.Agents and related namespaces.

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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.

| 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 |

> 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 automatic loop handling, or the manual loop for fine-grained control (approval gates, custom logging, conditional execution).

> 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.

Decision Tree

What does your application need?

0. Which provider?
   ├── First-party API or Claude Platform on AWS → continue (full surface available; per-feature exceptions in shared/platform-availability.md).
   └── Amazon Bedrock, Google Vertex AI, or Microsoft Foundry → Claude API (+ tool use for agents); see shared/platform-availability.md for per-feature support.

1. Single LLM call (classification, summarization, extraction, Q&A)
   └── Claude API — one request, one response

2. Do you want Anthropic to run the agent loop and host a per-session
   container where Claude executes tools (bash, file ops, code)?
   └── Yes → Managed Agents — server-managed sessions, persisted agent configs,
       SSE event stream, Skills + MCP, file mounts.
       Examples: "stateful coding agent with a workspace per task",
                 "long-running research agent that streams events to a UI",
                 "agent with persisted, versioned config used across many sessions"

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, you host the compute)
   └── Claude API agentic loop (maximum flexibility)

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).

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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.

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Current Models (cached: 2026-06-04)

| 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 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 4.6 | claude-sonnet-4-6 | 1M | $3.00 | $15.00 | | Claude Haiku 4.5 | claude-haiku-4-5 | 200K | $1.00 | $5.00 |

ALWAYS use claude-opus-4-8 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. 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.

Claude F

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Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: archubbuck
• Source: archubbuck/workspace-architect
• License: ISC

Install and usage instructions live in the source repository linked above.