extended-thinking
Extended thinking (ultrathink) configuration for Claude API. Activate for complex reasoning tasks, deep analysis, multi-step problem solving, and tasks requiring careful deliberation. Enables Claude's internal reasoning with configurable thinking budgets.
Installation
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
View source ↗GuidesSkill instructions
Extended Thinking (Ultrathink) Skill
Enable Claude's extended thinking capabilities for complex reasoning tasks that benefit from internal deliberation before responding.
When to Use
- Complex problem solving requiring multi-step reasoning
- Code architecture decisions with multiple trade-offs
- Debugging complex issues needing systematic analysis
- Strategic planning with many variables
- Mathematical or logical proofs
- Security analysis requiring threat modeling
- Performance optimization with multiple factors
Supported Models
| Model | Extended Thinking | Summarized Thinking |
|---|---|---|
| Claude Opus 4.5 | ✓ Full | - |
| Claude Opus 4.1 | ✓ Full | - |
| Claude Opus 4 | ✓ | ✓ Summarized |
| Claude Sonnet 4.5 | ✓ Full | - |
| Claude Sonnet 4 | ✓ | ✓ Summarized |
| Claude Haiku 4.5 | ✓ Full | - |
API Configuration
Basic Extended Thinking (Python)
import anthropic
client = anthropic.Anthropic()
response = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=16000,
thinking={
"type": "enabled",
"budget_tokens": 10000 # Minimum 1,024
},
messages=[{
"role": "user",
"content": "Analyze this complex architecture decision..."
}]
)
# Access thinking and response
for block in response.content:
if block.type == "thinking":
print(f"Thinking: {block.thinking}")
elif block.type == "text":
print(f"Response: {block.text}")
TypeScript Configuration
import Anthropic from "@anthropic-ai/sdk";
const client = new Anthropic();
const response = await client.messages.create({
model: "claude-sonnet-4-20250514",
max_tokens: 16000,
thinking: {
type: "enabled",
budget_tokens: 10000,
},
messages: [
{
role: "user",
content: "Analyze this complex architecture decision...",
},
],
});
Streaming (Required for max_tokens > 21,333)
with client.messages.stream(
model="claude-sonnet-4-20250514",
max_tokens=32000,
thinking={
"type": "enabled",
"budget_tokens": 20000
},
messages=[{"role": "user", "content": prompt}]
) as stream:
for event in stream:
if event.type == "content_block_delta":
if hasattr(event.delta, "thinking"):
print(event.delta.thinking, end="", flush=True)
elif hasattr(event.delta, "text"):
print(event.delta.text, end="", flush=True)
Budget Recommendations
| Task Complexity | Budget Tokens | Use Case |
|---|---|---|
| Light | 1,024 - 4,000 | Simple clarifications, basic analysis |
| Medium | 4,000 - 10,000 | Code review, debugging, design decisions |
| Heavy | 10,000 - 20,000 | Architecture planning, security audits |
| Complex | 20,000 - 32,000 | Multi-system analysis, comprehensive reviews |
| Maximum | 32,000+ | Use batch API for budgets exceeding 32k |
Tool Use with Extended Thinking
CRITICAL: When using tools with extended thinking, you MUST preserve thinking blocks in the conversation history.
# Initial request with thinking
response = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=16000,
thinking={"type": "enabled", "budget_tokens": 8000},
tools=[{
"name": "analyze_code",
"description": "Analyze code for issues",
"input_schema": {
"type": "object",
"properties": {"code": {"type": "string"}},
"required": ["code"]
}
}],
messages=[{"role": "user", "content": "Analyze this code..."}]
)
# MUST include ALL content blocks including thinking
tool_use_block = next(b for b in response.content if b.type == "tool_use")
tool_result = execute_tool(tool_use_block)
# Continue with thinking blocks preserved
follow_up = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=16000,
thinking={"type": "enabled", "budget_tokens": 8000},
tools=[...],
messages=[
{"role": "user", "content": "Analyze this code..."},
{"role": "assistant", "content": response.content}, # Includes thinking!
{"role": "user", "content": [{
"type": "tool_result",
"tool_use_id": tool_use_block.id,
"content": tool_result
}]}
]
)
Interleaved Thinking (Claude 4 Models)
For Claude 4 models, use interleaved thinking for thinking between tool calls:
response = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=16000,
thinking={"type": "enabled", "budget_tokens": 10000},
betas=["interleaved-thinking-2025-05-14"], # Required for Claude 4
messages=[...]
)
Constraints
- Minimum budget: 1,024 tokens
- Maximum output: 128k tokens (thinking + response)
- Temperature: Must be 1 (default) - cannot modify
- top_k: Cannot be used with extended thinking
- Streaming required: When max_tokens > 21,333
- System prompts: Fully compatible
Best Practices
- Start conservative: Begin with lower budgets, increase as needed
-
Monitor actual usage: Track
thinking_tokensin response usage - Use streaming: For better UX and larger outputs
- Preserve thinking blocks: Critical for multi-turn tool use
- Batch for heavy workloads: Use batch API for budgets > 32k tokens
- Match budget to task: Don't over-allocate for simple tasks
Integration with Claude Code
When using Claude Code CLI with extended thinking models:
# The CLI automatically handles extended thinking for supported models
# Use opus or sonnet models for complex tasks
claude --model claude-opus-4-5-20250514 "Analyze this codebase architecture"
See Also
- [[complex-reasoning]] - Multi-step reasoning patterns
- [[deep-analysis]] - Analytical thinking templates
- [[llm-integration]] - General LLM API patterns
Examples
Read the usage examples in the source repository.
View source ↗Source history
- Indexed on
- 2026-01-20
- Index updated
- 2026-01-31
- Branch
- main
Index and sync dates describe this directory. View the source repository for code history.
GitHub ↗chat Comments (0)
Sign in to join the discussion and leave a comment.
No comments yet. Be the first to share your thoughts!