Chain-of-Thought Extractor

Extract and isolate reasoning steps from verbose LLM chain-of-thought output.

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Split the model’s scratch work from the answer it actually gives

When you prompt a model to “think step by step”, the response mixes reasoning with the conclusion. Your users usually want only the clean answer, while you want the reasoning for logging and debugging. This tool detects the common chain-of-thought formats and splits the two apart automatically, so you can show one and store the other.

How it works

Paste the full output and the tool scans for recognizable structure, in priority order. First it looks for XML-style <thinking> or <reasoning> tags and extracts whatever is outside them as the answer. If there are none, it searches for explicit answer markers — “Final answer:”, “Therefore”, “In conclusion”, “The answer is” — and treats everything before the last such marker as reasoning. Failing that, it detects numbered or bulleted step lists and reasoning lead-ins like “Let me think” or “Step 1”. Whichever signal it finds, it returns the reasoning trace and the final answer in separate panels.

Tips and notes

Showing raw chain-of-thought to end users is discouraged by several provider policies and is rarely what users want, so isolating the final answer is a common production task. The tool never discards text: if it finds no structure, it treats the whole thing as the answer and tells you so. For reasoning models that hide their internal trace, this works on the visible output you paste but cannot recover a trace the API never returned. Use the copy buttons to wire the clean answer into your UI and the trace into your logs.

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