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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.

curlmanaged-agents.md

≈2.2k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Managed Agents - cURL / Raw HTTP

Use these examples when the user needs raw HTTP requests or is working without an SDK.

Setup

export ANTHROPIC_API_KEY="your-api-key"

# Common headers
HEADERS=(
  -H "Content-Type: application/json"
  -H "x-api-key: $ANTHROPIC_API_KEY"
  -H "anthropic-version: 2023-06-01"
  -H "anthropic-beta: managed-agents-2026-04-01"
)

Create an Environment

curl -X POST https://api.anthropic.com/v1/environments \
  "${HEADERS[@]}" \
  -d '{
    "name": "my-dev-env",
    "config": {
      "type": "cloud",
      "networking": { "type": "unrestricted" }
    }
  }'

With restricted networking

curl -X POST https://api.anthropic.com/v1/environments \
  "${HEADERS[@]}" \
  -d '{
    "name": "restricted-env",
    "config": {
      "type": "cloud",
      "networking": {
        "type": "limited",
        "allow_package_managers": true,
        "allow_mcp_servers": true,
        "allowed_hosts": ["api.example.com"]
      }
    }
  }'

Create an Agent (required first step)

Warning: There is no inline agent config. Under managed-agents-2026-04-01, model/system/tools are top-level fields on POST /v1/agents, not on the session. Always create the agent first - the session only takes "agent": {"type": "agent", "id": "..."}.

Minimal

# 1. Create the agent
curl -X POST https://api.anthropic.com/v1/agents \
  "${HEADERS[@]}" \
  -d '{
    "name": "Coding Assistant",
    "model": "claude-opus-5-5",
    "tools": [{ "type": "agent_toolset_20260401" }]
  }'
# -> { "id": "agent_abc123", ... }

# 2. Start a session
curl -X POST https://api.anthropic.com/v1/sessions \
  "${HEADERS[@]}" \
  -d '{
    "agent": { "type": "agent", "id": "agent_abc123", "version": 1 },
    "environment_id": "env_abc123"
  }'
# -> { "id": "sesn_abc123", ... }
# Trace: https://platform.claude.com/workspaces/default/sessions/sesn_abc123  (swap 'default' for your workspace ID if the API key is not in the Default workspace)

With system prompt, custom tools, and GitHub repo

# 1. Create the agent
curl -X POST https://api.anthropic.com/v1/agents \
  "${HEADERS[@]}" \
  -d '{
    "name": "Code Reviewer",
    "model": "claude-opus-5-5",
    "system": "You are a senior code reviewer. Be thorough and constructive.",
    "tools": [
      { "type": "agent_toolset_20260401" },
      {
        "type": "custom",
        "name": "run_linter",
        "description": "Run the project linter on a file",
        "input_schema": {
          "type": "object",
          "properties": {
            "file_path": { "type": "string", "description": "Path to lint" }
          },
          "required": ["file_path"]
        }
      }
    ]
  }'

# 2. Start a session with the repo mounted
curl -X POST https://api.anthropic.com/v1/sessions \
  "${HEADERS[@]}" \
  -d '{
    "agent": { "type": "agent", "id": "agent_abc123", "version": 1 },
    "environment_id": "env_abc123",
    "title": "Code review session",
    "resources": [
      {
        "type": "github_repository",
        "url": "https://github.com/owner/repo",
        "mount_path": "/workspace/repo",
        "authorization_token": "ghp_...",
        "branch": "feature-branch"
      }
    ]
  }'

With a session budget

# Create a session with a hard $25.00 spend cap (list-priced; USD only; create-only).
# amount is in minor units (cents) as an integer string: "2500" = $25.00
curl -X POST https://api.anthropic.com/v1/sessions \
  "${HEADERS[@]}" \
  -d '{
    "agent": { "type": "agent", "id": "agent_abc123" },
    "environment_id": "env_abc123",
    "budget": {
      "type": "limit",
      "max_list_cost": { "amount": "2500", "currency": "USD" }
    }
  }'

# Change the cap - higher or lower, but it must exceed the consumed list cost.
# An accepted update resumes work paused at budget_reached
curl -X POST https://api.anthropic.com/v1/sessions/$SESSION_ID \
  "${HEADERS[@]}" \
  -d '{ "budget": { "type": "limit", "max_list_cost": { "amount": "4000", "currency": "USD" } } }'

# Remove the cap entirely - one-way; a removed budget can never be re-added
curl -X POST https://api.anthropic.com/v1/sessions/$SESSION_ID \
  "${HEADERS[@]}" \
  -d '{ "budget": null }'

See shared/managed-agents-core.md § Session budgets for list-cost composition, the settle-event allowlist at the cap, and multiagent semantics.


Send a User Message

curl -X POST https://api.anthropic.com/v1/sessions/$SESSION_ID/events \
  "${HEADERS[@]}" \
  -d '{
    "events": [
      {
        "type": "user.message",
        "content": [{ "type": "text", "text": "Review the auth module for security issues" }]
      }
    ]
  }'

Stream Events (SSE)

curl -N https://api.anthropic.com/v1/sessions/$SESSION_ID/events/stream \
  "${HEADERS[@]}"

Response format:

event: session.status_running
data: {"type":"session.status_running","id":"sevt_...","processed_at":"..."}

event: agent.message
data: {"type":"agent.message","id":"sevt_...","content":[{"type":"text","text":"I'll review..."}],"processed_at":"..."}

event: session.status_idle
data: {"type":"session.status_idle","id":"sevt_...","processed_at":"..."}

Poll Events

# Get all events
curl https://api.anthropic.com/v1/sessions/$SESSION_ID/events \
  "${HEADERS[@]}"

# Paginated - get next page of events
curl "https://api.anthropic.com/v1/sessions/$SESSION_ID/events?page=page_abc123" \
  "${HEADERS[@]}"

Provide Custom Tool Result

When the agent calls a custom tool, send the result back:

curl -X POST https://api.anthropic.com/v1/sessions/$SESSION_ID/events \
  "${HEADERS[@]}" \
  -d '{
    "events": [
      {
        "type": "user.custom_tool_result",
        "custom_tool_use_id": "sevt_abc123",
        "content": [{ "type": "text", "text": "No linting errors found." }]
      }
    ]
  }'

Interrupt a Running Session

curl -X POST https://api.anthropic.com/v1/sessions/$SESSION_ID/events \
  "${HEADERS[@]}" \
  -d '{
    "events": [
      {
        "type": "user.interrupt"
      }
    ]
  }'

Get Session Details

curl https://api.anthropic.com/v1/sessions/$SESSION_ID \
  "${HEADERS[@]}"

List Sessions

curl https://api.anthropic.com/v1/sessions \
  "${HEADERS[@]}"

Delete a Session

curl -X DELETE https://api.anthropic.com/v1/sessions/$SESSION_ID \
  "${HEADERS[@]}"

Upload a File

curl -X POST https://api.anthropic.com/v1/files \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -F "file=@path/to/file.txt" \
  -F "purpose=agent"

List and Download Session Files

List files the agent wrote to /mnt/session/outputs/ during a session, then download them.

# List files associated with a session
curl "https://api.anthropic.com/v1/files?scope_id=$SESSION_ID" \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "anthropic-beta: managed-agents-2026-04-01"

# Download a specific file
curl "https://api.anthropic.com/v1/files/$FILE_ID/content" \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -o downloaded_file.txt

List Agents

curl https://api.anthropic.com/v1/agents \
  "${HEADERS[@]}"

MCP Server Integration

# 1. Agent declares MCP server (no auth here - auth goes in a vault)
curl -X POST https://api.anthropic.com/v1/agents \
  "${HEADERS[@]}" \
  -d '{
    "name": "MCP Agent",
    "model": "claude-opus-5-5",
    "mcp_servers": [
      { "type": "url", "name": "my-tools", "url": "https://my-mcp-server.example.com/sse" }
    ],
    "tools": [
      { "type": "agent_toolset_20260401" },
      { "type": "mcp_toolset", "mcp_server_name": "my-tools" }
    ]
  }'

# 2. Session attaches vault containing credentials for that MCP server URL
curl -X POST https://api.anthropic.com/v1/sessions \
  "${HEADERS[@]}" \
  -d '{
    "agent": "agent_abc123",
    "environment_id": "env_abc123",
    "vault_ids": ["vlt_abc123"]
  }'

See shared/managed-agents-tools.md §Vaults for creating vaults and adding credentials.


Tool Configuration

curl -X POST https://api.anthropic.com/v1/agents \
  "${HEADERS[@]}" \
  -d '{
    "name": "Restricted Agent",
    "model": "claude-opus-5-5",
    "tools": [
      {
        "type": "agent_toolset_20260401",
        "default_config": { "enabled": true },
        "configs": [
          { "name": "bash", "enabled": false }
        ]
      }
    ]
  }'

Source: SKILL.md on GitHub

1 warning2d5 checks · Risk SAFE
  • 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.

  • Socket2d

    No alerts

  • Snyk2d

    Risk: LOW · No issues

  • Runlayer7mo

    12/26 files flagged

  • ZeroLeaks5mo

    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.