name: chat-distill description: > Distill a person's chat style from exported conversation records and generate replies that mimic their voice. Use when (1) analyzing chat history to extract vocabulary, tone, emoji habits, sentence patterns, and personality traits, (2) generating replies in someone's specific chat style, (3) creating a style profile from WeChat, TG, Discord, or text chat exports, (4) asking to analyze chat records or mimic a speaker's tone. Supports .txt, .json, and WeChat chat export formats.

Chat Distill — Style Analysis & Mimicry

Workflow

1. Parse → extract messages per speaker from raw export (see references/format-parsers.md)
2. Analyze → build style profile (see references/style-dimensions.md)
3. Report → output analysis report using template in references/output-template.md
4. Mimic → generate replies on demand using the profile

Quick Start

Given a chat export file:

1. Read the file and identify the format (WeChat export, plain text, JSON array, TG export).
2. Normalize into { speaker, text, time? } messages using parsing rules in references/format-parsers.md.
3. Pick the target speaker — the one whose style to learn. If multiple speakers exist, ask which one.
4. Run analysis following references/style-dimensions.md.
5. Output the report per references/output-template.md § Analysis Report.
6. When the user asks for a mimicked reply, use the profile + references/output-template.md § Mimic Reply.

Key Principles

• Show, don't tell: Include concrete examples from the actual chat when reporting style traits.
• Preserve quirks: Capture tics the speaker doesn't notice — repeated filler words, capitalization habits, punctuation style.

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• Respect privacy: Never echo sensitive content (passwords, addresses, financials) from chats into reports. Anonymize if needed.
• Minimum sample: Require at least 20 messages from the target speaker. If fewer, warn that analysis may be unreliable.

这是一个实用性不错的聊天风格分析工具，能够从聊天记录中提炼出说话风格并模仿生成回复。优点是支持平台多、分析维度全面、输出格式规范。缺点是使用指南比较简略，新手可能不容易把握分析标准，缺少实际案例参考。总体质量中等偏上，对于需要模仿特定人说话风格的用户有一定帮助。