Provides 100,891 JSON-formatted agent conversation examples where each assistant turn includes a short <think> internal reasoning trace before tool/function calls. Human-facing text and tool calls are preserved; intended to fine-tune models to produce concise, cost-efficient chain-of-thought for tool use.
Converts long or messy model reasoning traces into concise, user-facing summaries with optional metadata. 61K cleaned English samples in JSON format, Apache-2.0 licensed, created to train and evaluate reasoning-summarization models and to present safe, readable explanations instead of raw chain-of-thought.