Anthropic Introduces 'Think' Tool to Enhance Claude's Complex Problem-Solving Abilities

Anthropic has released a new capability for its Claude AI assistant that creates a dedicated space for structured thinking during complex tasks. The "think" tool significantly improves Claude's performance in scenarios requiring complex reasoning, policy adherence, and sequential decision-making.

What is the "Think" Tool?

The "think" tool provides Claude with a designated space for additional thinking steps when processing information and making decisions. Unlike Anthropic's previously introduced "extended thinking" capability, which helps Claude plan before generating a response, the "think" tool allows Claude to pause mid-task to process new information obtained from tool calls or user interactions.

Anthropic explains that the tool is particularly effective for:

• Analyzing outputs from previous tool calls
• Following detailed policy guidelines
• Making sequential decisions where each step builds on previous ones

According to Anthropic, the "think" tool is more suitable for cases where Claude doesn't have all necessary information from the initial user query and needs to process external data. In contrast, extended thinking works better for simpler tool use scenarios or straightforward instruction following.

Technical Implementation

The "think" tool uses a standard tool specification format from τ-Bench, a benchmarking framework described in a research paper:

{ 
  "name": "think", 
  "description": "Use the tool to think about something. It will not obtain new information or change the database, but just append the thought to the log. Use it when complex reasoning or some cache memory is needed.", 
  "input_schema": { 
    "type": "object", 
    "properties": { 
      "thought": { 
        "type": "string", 
        "description": "A thought to think about." 
      } 
    }, 
    "required": ["thought"] 
  } 
}

Performance Improvements

Anthropic evaluated the "think" tool using τ-bench, a comprehensive benchmark for testing AI models in realistic customer service scenarios. The benchmark assessed Claude's ability to navigate conversations, follow complex guidelines, and use various tools to access and manipulate environment databases.

The evaluation revealed significant performance improvements:

• In the airline domain, using the "think" tool with an optimized prompt achieved a 54% relative improvement over the baseline (0.570 vs. 0.370 on the pass^1 metric)
• In the retail domain, the "think" tool alone achieved 0.812, compared to 0.783 for the baseline

Notably, the best performance came from pairing the "think" tool with domain-specific prompting that provided examples of reasoning approaches relevant to the task.

The "think" tool was also evaluated on SWE-Bench, contributing to Claude 3.7 Sonnet's state-of-the-art score of 0.623. Isolated experiments showed a 1.6% average improvement from including the tool.

Implementation Recommendations

Based on their research, Anthropic recommends:

1. Strategic prompting with domain-specific examples: Providing clear instructions on when and how to use the tool, with examples tailored to specific use cases
2. Placing complex guidance in the system prompt: Including detailed instructions about the "think" tool in the system prompt rather than the tool description

However, Anthropic notes that the "think" tool is not beneficial for all scenarios. It offers minimal improvements for non-sequential tool calls or simple instruction following, and comes with increased prompt length and output tokens.

Conclusion

The "think" tool represents a straightforward addition to Claude's capabilities that can yield meaningful improvements in complex reasoning tasks with minimal implementation complexity. Anthropic's research shows that it enhances Claude 3.7 Sonnet's performance on tasks requiring policy adherence and reasoning in long chains of tool calls.

While the research focused primarily on Claude 3.7 Sonnet, Anthropic notes that Claude 3.5 Sonnet also achieves performance gains with the same configuration, indicating that the improvement applies broadly across Claude models.