# being

> being — wnbhr-being. Use this tool when you need to create AI agents with persistent personalities, memories, and relationships that can interact seamlessly across multiple platforms. It solves the problem of fragmented agent identities and behaviors, enabling consistent and contextualized interactions. This tool accepts personality profiles and interaction data as inputs and outputs unified agent personas, ideal for use cases requiring continuous character development and social learning.

Canonical page: https://skillsregistry.net/skills/wnbhr-being  
JSON: https://api.skillsregistry.net/v1/skills/wnbhr-being

## Description

Personality Runtime — persistent memory, identity, and relationships for AI agents that work across multiple LLM platforms via MCP

## Trust

- **Trust score (0–1):** 0.58
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/wnbhr/being)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "wnbhr-being"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/wnbhr-being` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/wnbhr-being/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt