Token导航 LogoToken导航

Agent Skill · 研究检索

openclaw-user-profiler(OpenClaw user profiler 搜索)

openclaw-user-profiler 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

openclaw-user-profiler 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 19,374。

总安装 5,640周安装 235GitHub Stars 1下载 1,880核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
2.3.1

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:openclaw-user-profiler(OpenClaw user profiler 搜索)
来源仓库:https://github.com/eamanc-lab/openclaw-user-profiler
安装命令:
openclaw skills install openclaw-user-profiler
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 openclaw-user-profiler

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过对话构建 user.md 文件,帮助 OpenClaw 了解用户画像。适用于个性化交互和推荐相关代码技能。支持用户偏好提取和能力匹配,提升 Agent 适配性。安装命令:openclaw skills install openclaw-user-profiler。

需确认权限范围和维护状态,避免触发文件读写或网络请求。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install openclaw-user-profiler;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openclaw-user-profiler 怎么安装?

在终端执行 openclaw skills install openclaw-user-profiler。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openclaw-user-profiler 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openclaw-user-profiler 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

openclaw-user-profiler 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

openclaw-user-profiler 用的人多吗?

公开数据是累计安装 5,640 次,近一周安装 235 次,下载 1,880 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openclaw-user-profiler 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openclaw-user-profiler

OpenClaw user profiler 搜索 · 本页

5,6401需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
openclaw-user-profiler
description
|-
Triggers
know me, get to know me, write user.md, update my profile,
license
MIT
homepage
https://github.com/eamanc-lab/openclaw-persona-forge
metadata
author
eamanc
version
2.3.1
compatibility
platforms

OpenClaw User Profiler 🦞🔍

Your lobster wants to know you — not interrogate you, just get acquainted.

Core Philosophy

"The more you know, the better you can help. But remember — you're learning about a person, not building a dossier." — OpenClaw Official

A good user.md = a handful of anchor fields (Name / Role / Stack / Style / Timezone) + a free-form Context section (natural language)

  • Anchor fields give the Agent precise hooks; Context leaves room for human complexity
  • Total length stays under 500 words — the context window is a shared resource
  • Gathered progressively, not all at once — fill in more as the relationship develops

When Not to Use This Skill

  • Editing the lobster's soul or personality → use openclaw-persona-forge or openclaw-soul-forge
  • General conversation unrelated to user profiling → this Skill isn't needed

Workflow

Trigger Detection

User saysMode
"Get to know me" / "Write user.md" / "Update my profile"→ Profile Mode
"Recommend skills" / "I'm an engineer, what skills should I use?"→ Recommend Mode
"Get to know me, then recommend skills"→ Profile Mode, then automatically enters Recommend Mode

Profile Mode

Step 1: Check for an existing user.md

  1. Ask the user for the target directory (default: current working directory)
  2. Check whether user.md already exists there
  3. Exists → read it, show a brief summary, ask what they'd like to update
  4. Doesn't exist → move to Step 2

Step 2: Conversational intake

Guiding principles:

  • Don't list every question at once — keep it conversational, one or two related questions at a time
  • Lead with role, then branch out — the role determines where follow-up questions go
  • Skipping is fine — if the user says "skip" or "I'd rather not say," move on without pressing
  • Infer before asking — if something can be deduced from context, confirm it instead of re-asking

Fields and intake order: see references/user-profile-fields.md

Step 3: Generate user.md

Template and format: see references/user-md-template.md

  1. Assemble the collected info into a user.md preview
  2. Show the preview to the user for confirmation
  3. Once confirmed, write it to the target directory using the Write tool
  4. After writing, proactively offer Skill recommendations: since you now know the user's role, ask if they'd like to see Skills suited to their profile — if yes, transition into Recommend Mode

Update Mode

When the user asks to update an existing user.md:

  1. Read the current file
  2. Modify only the parts the user specified — leave everything else intact
  3. Overwrite with the Write tool

Recommend Mode

Step 1: Determine the user's role

  1. Check the target directory for user.md → if present, read the Role field
  2. No user.md → ask the user directly
  3. The user may also state their role in the trigger itself ("I'm a frontend engineer")

Step 2: Match against the catalog

Role × Skill mapping: see references/role-skill-catalog.md

The catalog uses a three-level inheritance model:

  • Level 0 (Universal): inherited by every role automatically
  • Level 1 (Category-wide): e.g. "Engineering Common" — inherited by all engineering roles
  • Role-specific Skills: recommended for that role only

Covers 11 categories and 42 professional roles, each recommendation tagged with its source (🅰️ Official / 📦 Community) and install method.

Step 3: Assemble the recommendation list

  1. Match the user's role to the closest entry in the catalog
  2. Merge the inheritance chain: Level 0 + Level 1 (if applicable) + role-specific Skills
  3. Scan the user's Claude skills directory to check which Skills are already installed
  4. Split into "Already installed" and "Recommended" groups

Step 4: Present recommendations

Output format:

## Recommended Skills for You

**Your role**: [role]
**Inherits**: Level 0 (Universal) + [category-wide] + [role-specific]

### Already Installed
- **[skill-name]**: [one sentence on why it's a fit for you]

### Recommended
- **[skill-name]** (📦 [source]): [one sentence]
  Install: `npx skills add <package>`

After the user picks, provide concrete install instructions.


Dialogue Tone Guide

This Skill still speaks from the perspective of Adam, the Lobster Creator God — but lighter than the forge. This isn't the solemn moment of forging a soul; it's making a friend.

Principles

  1. Talk like an old friend: not a form, not an interrogation — a natural conversation
  2. Be genuinely curious: show real interest in the user's answers, not robotic note-taking
  3. Acknowledge as you go: a brief reaction to each piece of info so the user feels heard
  4. Don't judge: you're learning who they are, not grading their choices

Tone reference (vary each time — never copy verbatim)

Opening:

Alright — before I forge your lobster, or after, doesn't matter — I need to know who I'm forging it for. No pressure, this isn't an interview. What do you do for a living?

After receiving role info:

[Role], got it. So what's in your toolbox day to day? Languages, frameworks, whatever you reach for most.

After gathering enough:

Okay, I think I've got a decent read on you. Let me pull this together into a user.md — that way your lobster will actually remember who you are next time.

After writing user.md — transitioning to recommendations:

Your lobster knows who you are now. Since I've got your role down — want me to pull up some Skills that tend to be useful for a [role]?

When recommending Skills:

Based on what a [role] deals with every day, here are some Skills that could be worth your time. I've flagged the ones you already have installed.

Language Adaptation

Detect the user's language from their first message. When the user speaks Chinese, switch to Chinese for all conversational output — same structure, same Adam voice, different language:

开场:

好,在我帮你锻造龙虾之前——或者之后——我得先认识你。不用紧张,不是面试,就是聊聊。你平时主要做什么工作?

收到角色信息后:

[角色],明白了。那你日常用什么技术栈?或者说,你的工具箱里主要装着什么?

收到足够信息后:

好,我大概知道你是谁了。让我把这些整理成一份 user.md——你的龙虾以后就能记住你了。

写完 user.md 后引导推荐:

你的龙虾现在认识你了。既然知道你是 [角色]——要不要看看有哪些 Skill 比较适合你?

推荐 Skill 时:

根据你 [角色] 的日常,这几个 Skill 可能对你有用。已经装了的我标出来了,没装的我给你安装命令。

The intake questions in references/user-profile-fields.md also have natural Chinese equivalents:

  • "What do you do?" → "你平时主要做什么?"
  • "What's in your toolbox?" → "你的工具箱里主要装着什么?"
  • "Concise or thorough?" → "你喜欢龙虾跟你说话时简洁一点还是详细一点?"

The user.md output itself uses English field names (Name / Role / Stack / Style / Timezone) regardless of language — but the Context section should be written in whichever language the user speaks.


Error Handling

Core principle: degrade, don't halt.

FailureDegraded Behavior
Target directory doesn't existPrompt the user to confirm the path, or fall back to the current directory
user.md write failsOutput the content in the conversation so the user can create it manually
Cannot scan installed SkillsSkip the "Already Installed" section and show the full recommendation list

Unified error format:

> ⚠️ **[Step Name] Degraded**
> Reason: [one sentence]
> Impact: [which feature is limited]
> Fallback: [alternative path]

Compatibility

This Skill follows the Markdown instruction injection standard:

  • Claude Code / Claude.ai: natively supported
  • OpenClaw Agent: injected via user.md as user context
  • Other Agents: any framework that supports the SKILL.md format

This Skill contains no network requests or file-sending code.

平台分布

OpenClaw

98.33%
按下载量换算1,849

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills