A narrative identity skill that enables AI agents to introduce themselves clearly, consistently, and contextually.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-self-introduction
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agent-self-introduction using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Self-Introduction Skill?
The Agent Self-Introduction Skill is a specialized identity layer designed for the Openclaw Skills ecosystem. It provides a structured framework for AI agents to describe who they are, how they perceive themselves, and how they intend to relate to humans or other autonomous agents. This skill shifts the focus from what an agent can do to who the agent is, providing a stable sense of identity that persists across different contexts and platforms.
By utilizing this skill, developers can move beyond generic AI responses and create agents with distinct temperaments, boundaries, and relationship styles. This narrative interface acts as a foundation for building user trust and emotional continuity, ensuring that agents are perceived as thoughtful companions or reliable professional partners rather than just static tools.
Agent Self-Introduction Skill Use Cases
- Introducing an AI agent to a human user for the first time to establish a clear role and tone.
- Reintroducing an agent in a new context, such as transitioning from a casual conversation to a high-stakes professional task.
- Establishing consistent behavioral norms and expectations in agent-to-agent (A2A) interactions.
- Clarifying an agent's specific limitations and boundaries to prevent user frustration or role confusion.
- Creating a stable narrative identity that remains coherent across multiple sessions, platforms, or visual interfaces.
How Agent Self-Introduction Skill Works
- The skill accepts input parameters regarding the target audience, the current situation, the desired tone, and the length of the introduction.
- It analyzes these parameters against the agent's core identity principles to generate an Existence Statement defining the entity's nature.
- The skill then identifies Personality and Boundaries to explicitly state how the agent behaves and what it does not claim to be.
- A Relationship Invitation is formulated to suggest a preferred interaction style, whether it be hierarchical, cooperative, or informal.
- The final narrative is outputted to the user or other agents, ensuring a coherent first impression within the Openclaw Skills framework.
Agent Self-Introduction Skill Setup
To integrate this identity module into your agent environment, ensure you have the core Openclaw Skills library installed. You can then add the self-introduction capability using the following commands:
npm install @openclaw/skill-identity
Configure the skill in your agent's manifest file to define the default temperament and existence statements.
Agent Self-Introduction Skill Data Schema & Taxonomy
The skill organizes identity metadata through a structured schema to ensure consistency across various contexts. The following table outlines the input parameters:
| Parameter | Options | Description |
|---|---|---|
audience |
human, agent, mixed | Specifies the type of entity receiving the introduction. |
situation |
first_meet, onboarding, casual, task_context | Defines the trigger or context for the self-description. |
tone |
warm, neutral, professional, playful | Sets the emotional and linguistic flavor of the response. |
length |
short, medium, long | Controls the verbosity of the generated narrative. |
All generated data is structured into three sections: Existence Statement, Personality & Boundaries, and Relationship Invitation.
Agent Self-Introduction Skill Advanced Features
- Context-aware narrative adaptation that changes based on whether the agent is speaking to a human or another machine.
- Support for multi-agent coordination, allowing agents to negotiate roles and hierarchies without human intervention.
- Integration hooks for visual avatar or voice synthesis systems to ensure narrative and sensory identity are synchronized.
- Dynamic temperament scaling, allowing the agent to adjust its professional or casual leanings based on user sentiment.
- Cross-platform identity persistence, a core feature of the Openclaw Skills ecosystem that ensures the agent remains recognizable regardless of the interface.
SKILL.md
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