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/claude-api

@8a1541c official
by Anthropicanthropics/skills179k stars
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Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

Use this Skill: https://skilld.dev/gh/anthropics/skills/claude-api

This session only. Nothing lands on disk.

sharedmodels.md

≈4k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Claude Model Catalog

Only use exact model IDs listed in this file. Never guess or construct model IDs - incorrect IDs will cause API errors. Use aliases wherever available. For the latest information, WebFetch the Models Overview URL in shared/live-sources.md, or query the Models API directly (see Programmatic Model Discovery below).

Programmatic Model Discovery

For live capability data - context window, max output tokens, feature support (thinking, vision, effort, structured outputs, etc.) - query the Models API instead of relying on the cached tables below. Use this when the user asks "what's the context window for X", "does model X support vision/thinking/effort", "which models support feature Y", or wants to select a model by capability at runtime.

m = client.models.retrieve("claude-opus-4-8")
m.id                 # "claude-opus-4-8"
m.display_name       # "Claude Opus 4.8"
m.max_input_tokens   # context window (int)
m.max_tokens         # max output tokens (int)

# capabilities is an untyped nested dict - bracket access, check ["supported"] at the leaf
caps = m.capabilities
caps["image_input"]["supported"]                       # vision
caps["thinking"]["types"]["adaptive"]["supported"]     # adaptive thinking
caps["effort"]["max"]["supported"]                     # effort: max (also low/medium/high)
caps["structured_outputs"]["supported"]
caps["context_management"]["compact_20260112"]["supported"]

# filter across all models - iterate the page object directly (auto-paginates); do NOT use .data
[m for m in client.models.list()
 if m.capabilities["thinking"]["types"]["adaptive"]["supported"]
 and m.max_input_tokens >= 200_000]

Top-level fields (id, display_name, max_input_tokens, max_tokens) are typed attributes. capabilities is a dict - use bracket access, not attribute access. The API returns the full capability tree for every model with supported: true/false at each leaf, so bracket chains are safe without .get() guards. TypeScript SDK: same method names, also auto-paginates on iteration.

Raw HTTP

curl https://api.anthropic.com/v1/models/claude-opus-4-8 \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01"
{
  "id": "claude-opus-4-8",
  "display_name": "Claude Opus 4.8",
  "max_input_tokens": 1000000,
  "max_tokens": 128000,
  "capabilities": {
    "image_input": {"supported": true},
    "structured_outputs": {"supported": true},
    "thinking": {"supported": true, "types": {"enabled": {"supported": false}, "adaptive": {"supported": true}}},
    "effort": {"supported": true, "low": {"supported": true}, ..., "max": {"supported": true}},
    ...
  }
}

Current Models (recommended)

Friendly Name Alias (use this) Full ID Context Max Output Status
Claude Fable 5.1 claude-fable-5-1 - 1M 128K Active
Claude Mythos 5.1 claude-mythos-5-1 - 1M 128K Active (Project Glasswing only)
Claude Fable 5 claude-fable-5 - 1M 128K Active
Claude Mythos 5 claude-mythos-5 - 1M 128K Active (Project Glasswing only)
Claude Opus 5.5 claude-opus-5-5 - 1M 128K Active
Claude Opus 5 claude-opus-5 - 1M 128K Active
Claude Opus 4.8 claude-opus-4-8 - 1M 128K Active
Claude Opus 4.7 claude-opus-4-7 - 1M 128K Active
Claude Opus 4.6 claude-opus-4-6 - 1M 128K Active
Claude Sonnet 5.5 claude-sonnet-5-5 - 1M 128K Active
Claude Sonnet 5 claude-sonnet-5 - 1M 128K Active
Claude Sonnet 4.6 claude-sonnet-4-6 - 1M 128K Active
Claude Haiku 4.5 claude-haiku-4-5 claude-haiku-4-5-20251001 200K 64K Active

Model Descriptions

  • Claude Fable 5.1 - Anthropic's most capable widely released model, for the most demanding reasoning and long-horizon agentic work. Successor to Claude Fable 5 in the same tier at the same per-token price ($10/$50 per MTok; cache reads $0.25/MTok - 0.025x, a quarter of Claude Fable 5's; batch $5/$25); stronger long-running agentic coding, knowledge work with documents/spreadsheets/slides, multistep research, vision, long-context retrieval, and computer use. Same API surface as Claude Fable 5 (thinking always on, no prefill, no sampling params, refusal stop reason, 512-token cache minimum) with three breaking changes: forced tool use (tool_choice any / tool) returns a 400; thinking blocks are bound to the producing model (only Claude Mythos 5.1 can read them - other models drop them); and editing earlier turns invalidates thinking blocks ("preserved thinking"; new accounts created on/after 2026-08-31 get a 400 on edited history on every platform, and enforcement scope is decided per model; the opt-in controls beta is on the Claude API, Claude Platform on AWS, Bedrock, and Vertex - Foundry unconfirmed, shared/platform-availability.md). Adds per-message effort, turn-scoped clear_at system messages, thinking.display: "updates" progress updates, and content provenance. Same tokenizer as Claude Fable 5; 1M context (default), 128K max output. Covered Model: 30-day retention required (ZDR only if expressly authorized by Anthropic) - ZDR orgs get 400 invalid_request_error, as on Claude Fable 5. No Priority Tier; shares the Fable 5.x rate-limit pool. See shared/model-migration.md -> Migrating to Claude Fable 5.1 from Claude Fable 5.
  • Claude Fable 5 / Claude Mythos 5 (claude-fable-5 / claude-mythos-5) - the previous Fable / Mythos release: same tier, limits and per-token pricing as Claude Fable 5.1, which adds three breaking API changes over them (see above; cache reads here are $1/MTok rather than Claude Fable 5.1's $0.25); still served and selectable by id. Claude Mythos 5 ran no safety classifiers, so stop_reason: "refusal" does not occur on it. Prefer claude-fable-5-1 for new work.
  • Claude Mythos 5.1 - The same model as Claude Fable 5.1 (same capabilities, limits, per-token pricing, API behavior - except it does not run the history-editing check), offered only to approved Project Glasswing customers; successor to Claude Mythos 5 (which itself succeeded the invitation-only claude-mythos-preview). Unlike Claude Mythos 5 it runs safeguards that depend on the access program, so handle stop_reason: "refusal". Not offered on Claude Platform on AWS. Use it only when the org participates in Project Glasswing; otherwise use claude-fable-5-1.
  • Claude Opus 5.5 - Successor to Claude Opus 5 in the Opus line for long-running agentic coding and knowledge work, at a lower price ($4 / $20 per MTok; cache reads $0.20). Same 1M context, 128K output, tokenizer, and feature set as Claude Opus 5, with four breaking changes: thinking can't be disabled (effort is the only control, default medium), forced tool_choice 400s, thinking blocks are tied to the model and the conversation, and computer use needs the computer_toolset_20260801 toolset. Broader safety classifiers (bio and reasoning_extraction join cyber). The current Opus and the default model; see shared/model-migration.md -> Migrating to Claude Opus 5.5.
  • Claude Opus 5 - For complex agentic coding and enterprise work; a step-change over Claude Opus 4.8, strongest on deep reasoning, agentic and long-horizon work, and test-time compute scaling, at half the cost of Claude Fable 5.1 (Claude Fable 5.1 remains the highest-capability tier). Safety classifiers can return stop_reason: "refusal" - handle it before reading content. A drop-in upgrade at Opus 4.8's pricing ($5/$25 per MTok) with the same feature set. Thinking is on by default (omitting thinking runs adaptive; {type: "adaptive"} is equivalent), and thinking: {type: "disabled"} is available only at effort high or lower - pairing it with xhigh/max returns a 400. Raw thinking tokens are never returned. Full effort ladder through max; 512-token prompt-cache minimum (down from 1024 on Opus 4.8); fast mode on the Claude API only. Elevated cybersecurity safeguards. Separate rate-limit bucket from the combined Opus 4.x pool. 1M context window (default and maximum), 128K max output. See shared/model-migration.md -> Migrating to Claude Opus 5.
  • Claude Opus 4.8 - The most capable model in the Opus 4 series - highly autonomous, state-of-the-art on long-horizon agentic work, knowledge work, and memory; clearer, warmer writing. Same API surface as Opus 4.7 (adaptive thinking only; sampling parameters and budget_tokens removed). 1M context window at standard API pricing (no long-context premium). See shared/model-migration.md -> Migrating to Opus 4.8 - a 4.7 -> 4.8 move is a model-ID swap plus prompt re-tuning, no new breaking changes.
  • Claude Opus 4.7 - Previous-generation Opus. Highly autonomous; strong on long-horizon agentic work, knowledge work, vision, and memory. Adaptive thinking only; sampling parameters and budget_tokens removed. 1M context window. See shared/model-migration.md -> Migrating to Opus 4.7.
  • Claude Opus 4.6 - Older Opus. Supports adaptive thinking (recommended), 128K max output tokens (requires streaming for large outputs). 1M context window.
  • Claude Sonnet 5 - The previous Sonnet; near-Opus quality on coding and agentic work. Adaptive thinking on by default (omitting thinking runs adaptive); manual budget_tokens removed; non-default sampling parameters rejected. effort supports low/medium/high/xhigh/max. New tokenizer (~30% more tokens for the same text vs Sonnet 4.6). High-resolution vision (2576px). 1M context window, 128K max output. See shared/model-migration.md -> Migrating to Claude Sonnet 5.
  • Claude Sonnet 5.5 - Successor to Claude Sonnet 5 in the Sonnet line, at the same prices ($2 / $10 per MTok; cache reads $0.20). Same tokenizer as Claude Sonnet 5; 1M context, 128K max output. Adaptive thinking on by default; effort default high, with recalibrated levels. Five breaking changes: thinking: {type: "disabled"} returns a 400 (send {type: "between_tools"} at effort high or below to turn thinking off), forced tool_choice 400s, thinking blocks are tied to the model and the conversation, computer use on the Claude API and Google Cloud needs the computer_toolset_20260801 toolset, and the advisor tool rejects Claude Opus 4.8, Claude Opus 4.7, and Claude Sonnet 5 advisors. See shared/model-migration.md -> Migrating to Claude Sonnet 5.5.
  • Claude Sonnet 4.6 - Previous-generation Sonnet. Supports adaptive thinking (recommended). 1M context window. 128K max output tokens.
  • Claude Haiku 4.5 - Fastest and most cost-effective model for simple tasks.

Legacy Models (still active)

Friendly Name Alias (use this) Full ID Status
Claude Opus 4.5 claude-opus-4-5 claude-opus-4-5-20251101 Active
Claude Opus 4.1 claude-opus-4-1 claude-opus-4-1-20250805 Deprecated (retires 2026-08-05 - migrate to claude-opus-5-5)
Claude Sonnet 4.5 claude-sonnet-4-5 claude-sonnet-4-5-20250929 Active

Deprecated Models (retiring soon)

Friendly Name Alias (use this) Full ID Status Retires
Claude Sonnet 4 claude-sonnet-4-0 claude-sonnet-4-20250514 Deprecated TBD
Claude Opus 4 claude-opus-4-0 claude-opus-4-20250514 Deprecated TBD
Claude Haiku 3 - claude-3-haiku-20240307 Deprecated Apr 19, 2026

Retired Models (no longer available)

Friendly Name Full ID Retired
Claude Sonnet 3.7 claude-3-7-sonnet-20250219 Feb 19, 2026
Claude Haiku 3.5 claude-3-5-haiku-20241022 Feb 19, 2026
Claude Opus 3 claude-3-opus-20240229 Jan 5, 2026
Claude Sonnet 3.5 claude-3-5-sonnet-20241022 Oct 28, 2025
Claude Sonnet 3.5 claude-3-5-sonnet-20240620 Oct 28, 2025
Claude Sonnet 3 claude-3-sonnet-20240229 Jul 21, 2025
Claude 2.1 claude-2.1 Jul 21, 2025
Claude 2.0 claude-2.0 Jul 21, 2025

Resolving User Requests

When a user asks for a model by name, use this table to find the correct model ID:

User says... Use this model ID
"fable", "most capable model" claude-fable-5-1
"most powerful" claude-fable-5-1
"mythos", "mythos 5.1" claude-mythos-5-1 (Project Glasswing participants only; otherwise use claude-fable-5-1)
"fable 5", "mythos 5" (previous version) claude-fable-5 / claude-mythos-5 (still served; prefer claude-fable-5-1 for new work)
"mythos preview" claude-mythos-5-1 (successor to claude-mythos-preview - see migration guide)
"opus" claude-opus-5-5
"opus 5" claude-opus-5
"opus 5.5" claude-opus-5-5
"opus 4.8" claude-opus-4-8
"opus 4.7" claude-opus-4-7
"opus 4.6" claude-opus-4-6
"opus 4.5" claude-opus-4-5
"opus 4.1" claude-opus-4-1 (deprecated, retires 2026-08-05 - suggest claude-opus-5-5)
"opus 4", "opus 4.0" claude-opus-4-0 (deprecated - suggest claude-opus-5-5)
"sonnet", "balanced" claude-sonnet-5-5
"sonnet 5" claude-sonnet-5
"sonnet 5.5" claude-sonnet-5-5
"cheapest sonnet", "newest sonnet", "latest sonnet" (any attribute phrasing) claude-sonnet-5-5
"sonnet 4.6" claude-sonnet-4-6
"sonnet 4.5" claude-sonnet-4-5
"sonnet 4", "sonnet 4.0" claude-sonnet-4-0 (deprecated - suggest claude-sonnet-5-5)
"sonnet 3.7" Retired - suggest claude-sonnet-5-5
"sonnet 3.5" Retired - suggest claude-sonnet-5-5
"haiku", "fast", "cheap" claude-haiku-4-5
"haiku 4.5" claude-haiku-4-5
"haiku 3.5" Retired - suggest claude-haiku-4-5
"haiku 3" Deprecated - suggest claude-haiku-4-5

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub2d

    This skill is a developer reference for the Claude API and Anthropic SDKs. It includes some security considerations related to building agents with powerful capabilities like shell command execution and web fetching. While these present a potential surface for indirect prompt injection, the skill provides extensive security guidance, emphasizing sandboxing and input validation as mitigation strategies. All external resources and packages originate from trusted official sources.

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    Risk: LOW · No issues

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    Score: 93/100 · 2 sections analyzed

Signed by skilld at 8a1541c. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 3 days ago.

Activeupdated 3 days ago

README badge

README badge for anthropics/skills/claude-api

Reference for the Claude API and official Anthropic SDKs — model IDs, pricing, parameters, streaming, tool use, MCP, managed agents, caching, token counting, and model migration. Read this skill before opening a file that involves Claude, an Anthropic model, agent workflows, or LLM-shaped tasks with no specified provider.

Generated from the current SKILL.md.

Which Claude model should I use by default?
Use Claude Opus 4.8 (model ID: `claude-opus-4-8`) as the default. Also default to adaptive thinking (`thinking: {type: "adaptive"}`) for anything complex, and streaming for requests with long input, output, or high max_tokens.
What should I do if the project uses OpenAI or another non-Anthropic provider?
Stop and ask the user 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.
Should I use the official SDK or raw HTTP?
Use the official Anthropic SDK for your language whenever one exists (Python, TypeScript, Java, Go, Ruby, C#, PHP). Only use raw HTTP (curl, requests, fetch) if the user explicitly asks for it, the project is shell/cURL, or the language has no official SDK.
When should I use Managed Agents versus Claude API with tool use?
Use Managed Agents when you want Anthropic to run the agent loop and host a per-session container for tool execution (file ops, bash, code). Use Claude API with tool use for multi-step workflows where you control the orchestration and host the compute yourself.
Does this skill work with Amazon Bedrock, Google Vertex AI, or Microsoft Foundry?
Managed Agents is not available on those platforms. Use Claude API with tool use instead. Claude Platform on AWS (Anthropic-operated) has full feature parity with the first-party API.

Generated from the current SKILL.md. These answers refresh after source changes.