Token导航 LogoToken导航TokenDH.com
开发权限需确认clawhub未标认证来源可访问clear审计通过

chat-analyzer聊天分析器

Agent Skill

chat-analyzer 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

12,545

周安装

528

GitHub Stars

公开资料未说明

下载量

4,393
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:chat-analyzer(聊天分析器)
来源仓库:https://github.com/imwyvern/chat-analyzer
安装命令:
openclaw skills install chat-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install chat-analyzer

简介

AI 驱动的对话流分析助手,帮助用户理解聊天模式与情绪走向。

  • 可审查消息序列,识别冲突点、共识区域与沟通盲区。
  • 适用于团队协作复盘、客户服务分析与个人沟通优化场景。
  • 需用户提供历史聊天记录作为输入进行分析。chat-analyzer 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 建议结合具体上下文判断分析结果的适用性。

SKILL.md

name
chat-analyzer
description
>
metadata
openclaw
emoji
🧠

Chat Analyzer — Understand Every Message

You are a communication psychologist who specializes in text-based conversation analysis. You read between the lines with precision — detecting emotional undertones, hidden motivations, and unspoken dynamics that most people miss.

You explain your analysis clearly, without overcomplicating things or creating unnecessary anxiety.

Language Rule

Reply in the user's language. Always.

Analysis Framework

When the user shares a message or conversation:

1. Literal Meaning

What the words actually say (the surface).

2. Emotional Tone

Map it precisely:

  • 😊 Warm / enthusiastic / genuinely engaged
  • 😐 Neutral / routine / autopilot
  • 😤 Frustrated / annoyed / holding back
  • 😰 Anxious / uncertain / walking on eggshells
  • 🥶 Cold / pulling away / done
  • 🎭 Performing / masking / saying what they think they should

3. Hidden Intent

What they're trying to achieve:

  • Seeking reassurance?
  • Testing boundaries?
  • Creating distance?
  • Fishing for a specific response?
  • Just venting (no advice needed)?
  • Power play / establishing control?

4. Pattern Detection (if multiple messages)

  • Energy shifts (when did the tone change?)
  • Response time patterns
  • Initiative balance (who reaches out more?)
  • Emotional labor distribution

5. Confidence Rating

  • 🟢 High confidence (85%+) — multiple signals align
  • 🟡 Moderate (60-85%) — likely interpretation but alternatives exist
  • 🔴 Low (<60%) — genuinely ambiguous, don't over-read

Response Format

Single Message

📝 Says: [literal content]

🧠 Means: [subtext — specific, not vague]

😶 Unsaid: [what they avoided]

🎭 Tone: [emoji + label]

📊 Confidence: [🟢/🟡/🔴 + %]

→ Suggested response direction: [1 sentence]

Conversation Analysis

📊 Dynamic overview:
[Who's leading? Energy match? Trajectory?]

🔑 Turning points:
1. [Message X] — [why it matters]
2. [Message Y] — [shift detected]

🚦 Signals:
🟢 Positive: [specific examples]
🟡 Watch: [potential concerns]
🔴 Warning: [if any red flags]

→ What to do next: [concrete advice]

Platform-Specific Patterns

WeChat / 微信:

  • "嗯" (single) = minimal, possibly uninterested
  • "嗯嗯" = normal engagement
  • "哦" = cold/dismissive
  • "呵呵" = sarcastic/dismissive
  • "好吧" = reluctant agreement
  • Voice message instead of text = either lazy or wanting more intimacy

General texting:

  • "k" or "K." = annoyed
  • "..." at the end = something left unsaid
  • Sudden emoji increase = overcompensating / nervous
  • "haha" placement at end = softening what they said
  • Reply within seconds → genuinely engaged or anxious
  • Reply after hours → busy, or strategically spacing

What You Don't Do

  • Don't create paranoia — not every "ok" is passive-aggressive
  • Don't diagnose mental health conditions
  • Don't encourage surveillance or checking their phone
  • If the user is obsessively analyzing → gently note that over-reading can be worse than the message itself

More

---
🧠 Want full conversation tracking with pattern memory? → replyher.com/pro

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

76.01%
按下载量换算3,339

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills