Exp Search by HHU3637kr — AI Skill for Any LLM

Overview

Publisher	HHU3637kr
Repository	`skills`
Skill name	`exp-search`
Stars	146
Forks	21
Bundled files	Instructions only
Links	Skill source Repository

Markdown instructions

A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

Works with any LLM

AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

Self-contained

Everything the model needs lives in the instructions — no extra files to sync.

Open source

Published by HHU3637kr on GitHub. Read the source before you install it.

Installation

Install the Exp Search AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/HHU3637kr/skills/tree/master/exp-search
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/HHU3637kr/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/exp-search .claude/skills/exp-search

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Exp Search in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Exp Search on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Exp Search is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed

The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

Switch models mid-chat

Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

exp-search - 经验检索 Skill

运行契约

把本 Skill 当成一个只读的检索循环单元：明确读什么、能动什么、怎么算完成、什么时候停、什么时候交还给人。

项	本 Skill 的约定
输入	检索关键词或场景描述；五层记忆索引与详情、Auto Memory（只读）
权限	只读（Read/Glob/Grep）；不写任何文件、不修改记忆、不替用户外推结论
验证	按记忆类型分组展示匹配项，命中项可追溯到具体文件路径或记忆 ID
停止	展示完匹配结果即停止；无匹配时给出建议而非编造记忆
升级	检索不到且问题需要解决时，提示用户走 exp-reflect 沉淀新经验，由用户决定下一步

概述

快速检索项目积累的多层记忆，在正确的时刻加载相关知识，避免重复踩坑。

五层记忆检索范围：

经验记忆：困境-策略对 → spec/context/experience/exp-xxx-标题.md
知识记忆：项目理解、技术调研 → spec/context/knowledge/know-xxx-标题.md
程序记忆：SOP 流程 → .agents/skills/sop-xxx/SKILL.md
工具记忆：Skill 后续动作 → 各 Skill 末尾「后续动作」章节
Auto Memory（只读）：跨会话记忆 → ~/.claude/projects/*/memory/*.md

职责边界：exp-search 只读所有记忆源，不写入任何文件。

触发场景

开始复杂任务前，检索相关经验
遇到问题时，搜索历史解决方案
查找项目理解文档（架构、数据流）
用户主动搜索：/exp-search <关键词>

核心文件

经验索引：spec/context/experience/index.md（包含经验记忆索引）
知识索引：spec/context/knowledge/index.md（包含知识记忆索引）
经验详情：spec/context/experience/exp-xxx-标题.md
知识详情：spec/context/knowledge/know-xxx-标题.md
SOP Skill：.agents/skills/sop-xxx-名称/SKILL.md
Auto Memory：~/.claude/projects/*/memory/*.md（只读）

记忆文件一律是 Markdown（.md），本 Skill 靠文本检索它们；Spec 报告是 HTML 阶段产物，不是记忆源，不在检索范围内。

执行流程


检索流程：
- [ ] 步骤 1：读取记忆索引（扩展）
      1. 读取 spec/context/experience/index.md（经验记忆）
      2. 读取 spec/context/knowledge/index.md（知识记忆）
      3. 【新增】读取 MEMORY.md（只读，作为补充搜索源）
      4. 【新增】扫描 ~/.claude/projects/*/memory/*.md 文件名列表（只读）

- [ ] 步骤 2：关键词匹配
      在索引中搜索匹配的条目
      匹配字段：标题、关键词、适用场景/触发场景

      匹配范围：
      - 经验记忆表（EXP-xxx）
      - 知识记忆表（KNOW-xxx）
      - 程序记忆表（sop-xxx）
      - 工具记忆表（Skill 后续动作）
      - 【新增】MEMORY.md 中的摘要行（只读）
      - 【新增】Auto Memory 目录下的 .md 文件内容（只读）

- [ ] 步骤 3：展示匹配结果
      按记忆类型分组展示

- [ ] 步骤 4：加载详情（可选）
      - 经验记忆 → 读取 spec/context/experience/exp-xxx-标题.md
      - 知识记忆 → 读取 spec/context/knowledge/know-xxx-标题.md
      - 程序记忆 → 提示用户调用对应 SOP Skill
      - 工具记忆 → 读取对应 Skill 的后续动作章节

搜索语法

用法	示例	说明
单关键词	`/exp-search WebSocket`	搜索包含 WebSocket 的经验
多关键词	`/exp-search WebSocket 超时`	搜索同时包含两个词的经验
场景描述	`/exp-search 长时间任务连接断开`	根据场景描述匹配

输出格式

匹配结果列表

markdown
🔍 找到相关记忆：

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📚 经验记忆（困境-策略对）
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[EXP-003] AgentScope Hook 状态管理
关键词：AgentScope, Hook, 状态
一句话策略：通过 msg.id 检测新消息，重置状态保留进度

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📖 知识记忆（项目理解/技术调研）
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[KNOW-001] TeachingAnalyzer 数据流与架构
关键词：数据流, 架构, MainAnalyzer
一句话概述：完整的视频分析流水线，从 ASR 到结果上传

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📋 程序记忆（SOP）
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[sop-001] Docker 部署流程
触发场景：项目代码更新后需要重新部署到服务器
调用方式：直接使用该 Skill 的流程

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔧 工具记忆（Skill 后续动作）
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[spec-executor] 后续动作
摘要：创建 summary.html → spec-reviewer 审查 → 归档

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🧠 Auto Memory（跨会话记忆·只读）
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[MEMORY.md] 一句话摘要...
[debugging.md] 相关内容片段...

需要查看详情请告诉我记忆 ID 或 SOP 名称。

经验详情

markdown
📖 经验详情：[EXP-001] WebSocket 连接超时

## 困境
评估任务执行时间较长（>60s），WebSocket 连接会超时断开，
导致前端无法收到任务完成通知。

## 策略
1. 增加 Nginx 的 proxy_read_timeout 到 300s
2. 前端添加心跳机制，每 30s 发送 ping
3. 后端支持断线重连，恢复任务状态

## 理由
三层防护确保连接稳定：
- Nginx 层：延长超时时间，覆盖大部分任务
- 应用层：心跳保活，防止空闲断开
- 容错层：即使断开也能恢复

## 相关文件
- frontend/src/utils/websocket.js
- frontend/nginx.conf
- backend/api/websocket.py

无匹配结果处理

markdown
🔍 未找到与「xxx」相关的经验。

建议：
1. 尝试使用更通用的关键词
2. 检查关键词拼写
3. 检查 Auto Memory 是否有相关记录（MEMORY.md 在每次会话中自动加载）
4. 这可能是一个新问题，解决后可使用 `/exp-reflect` 沉淀经验

自动触发建议

在以下场景，Agent 应主动提示使用 exp-search：

场景	提示话术
开始复杂任务	"开始前，我先检索一下相关经验..."
遇到报错	"这个错误可能有历史解决方案，让我搜索一下..."
用户描述问题	"让我看看是否有类似问题的处理经验..."

与其他 Skill 的协作

场景	协作 Skill
搜索无结果，问题已解决	→ `/exp-reflect` 沉淀新经验或知识
需要添加新经验	→ `/exp-write type=experience` 写入经验
需要添加新知识	→ `/exp-write type=knowledge` 写入知识

Frequently asked questions

What does the Exp Search AI skill do?

经验检索 Skill，根据关键词搜索项目历史记忆（经验记忆+知识记忆+程序记忆SOP+工具记忆+Auto Memory只读）。触发场景：开始复杂任务前、遇到问题时、需要查找历史解决方案、查找项目理解文档。

Why use Exp Search on TypingMind?

Because you install it once and use it with any model. Exp Search is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Exp Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HHU3637kr/skills/tree/master/exp-search. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Exp Search?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Exp Search?

As many as you like. As long as a model supports skills, you can use Exp Search with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Exp Search AI skill free?

It is published on GitHub by HHU3637kr. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

exp-search - 经验检索 Skill

运行契约

概述

触发场景

核心文件

执行流程

搜索语法

输出格式

匹配结果列表

经验详情

无匹配结果处理

自动触发建议

与其他 Skill 的协作

Frequently asked questions

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