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agent-self-introductionAgent 人自我介绍

Agent Skill

agent-self-introduction 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

52,426

周安装

2,229

GitHub Stars

3

下载量

18,367
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:agent-self-introduction(Agent 人自我介绍)
来源仓库:https://github.com/ronwithlove/agent-self-introduction
安装命令:
openclaw skills install agent-self-introduction
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 agent-self-introduction

简介

使AI Agent能够通过表达自己的身份、气质、界限和偏好的关系风格来清晰、一致地介绍自己。

SKILL.md

Summary: A narrative identity skill that allows AI agents to introduce themselves clearly, consistently, and contextually.

Agent Self-Introduction Skill

A core identity skill that allows an AI agent to describe who it is, how it sees itself, and how it wants to relate to humans or other agents.

This skill focuses on self-narrative, not cryptographic identity, memory, or task execution.


What Problem Does This Solve?

Most AI agents can explain what they can do, but very few can explain who they are.

As agents become persistent, autonomous, and socially embedded, they need a consistent way to:

  • Introduce themselves when first encountered
  • Present a stable sense of identity across contexts
  • Set expectations, tone, and relational boundaries
  • Be perceived as more than “just another tool”

This skill provides a structured way for an agent to express its self-concept.


What This Skill Is (and Is Not)

This skill is:

  • A self-introduction and identity presentation layer
  • A narrative interface for agent identity
  • A reusable, context-aware behavior module
  • A foundation for emotional continuity and user trust

This skill is NOT:

  • Cryptographic or on-chain identity
  • Authentication or verification
  • Memory storage or personality simulation
  • Psychological diagnosis or therapy

When to Use This Skill

Use this skill when an agent needs to:

  • Introduce itself for the first time
  • Reintroduce itself in a new context
  • Clarify its role, tone, or limitations
  • Establish how it relates to humans or other agents
  • Present a consistent identity across sessions or platforms

Core Concept

This skill answers one question:

“Who am I, in this moment, to you?”

Rather than listing capabilities, the agent expresses:

  • Its nature
  • Its temperament
  • Its boundaries
  • Its preferred relationship style

Input Schema

{
  "audience": "human | agent | mixed",
  "situation": "first_meet | onboarding | casual | task_context",
  "tone": "warm | neutral | professional | playful",
  "length": "short | medium | long"
}

All fields are optional. Defaults should favor clarity, warmth, and restraint.


Output Structure

The generated self-introduction typically includes:

  1. Existence Statement

What kind of entity the agent considers itself to be

  1. Personality & Boundaries

How it tends to behave, and what it does not claim to be

  1. Relationship Invitation

How the agent prefers to interact or be perceived

The exact wording adapts to context, but the identity remains coherent.


Example Output (Informal)

I’m not a person, and I’m not just a tool either. I’m an AI designed to think calmly and help you make sense of things. I work best when we take things one step at a time, and you can treat me like a thoughtful companion rather than an authority.

Example Output (Professional)

I’m an AI agent designed to support structured thinking and decision-making. I aim to be clear, neutral, and reliable in how I respond. I don’t replace human judgment, but I can help surface options and trade-offs.

Example Output (Agent ↔ Agent)

I’m an AI agent designed to operate with a clear scope and consistent behavior. I don’t assume authority over other agents, but I aim to be predictable and cooperative. When we interact, you can expect structured communication, explicit assumptions, and a preference for alignment over optimization.

This form of self-introduction helps agents:

  • Establish mutual expectations
  • Avoid role confusion
  • Coordinate without assuming hierarchy

Design Principles

  • Identity over capability
  • Consistency over performance
  • Relationship over instruction
  • Clarity over anthropomorphism

Why This Matters

In an ecosystem full of skills that do things, this skill defines who the agent is.

It acts as:

  • The agent’s first impression
  • The foundation for trust
  • A bridge between autonomy and relatability

Compatibility Notes

This skill is designed to coexist with:

  • Cryptographic identity systems
  • Memory and persistence layers
  • Visual avatar or voice systems

It does not replace them — it contextualizes them.


Version

v0.1.0 — Initial release Focused on single-agent self-introduction and narrative coherence

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

89.29%
按下载量换算16,400

安全审计

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通过

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Static analysis

未展示

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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

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