# coer-nucleus

> Use this tool when you need to map complex domains into structured talent and ecosystem landscapes, solving problems of information fragmentation and knowledge gaps in niche areas. It takes in domain-specific data and outputs a visual representation of the landscape, allowing users to contribute new information via pull requests. Ideal for use cases where understanding the talent and ecosystem landscape is crucial, such as strategic planning and innovation initiatives.

Canonical page: https://skillsregistry.net/skills/pastarita-coer-nucleus  
JSON: https://api.skillsregistry.net/v1/skills/pastarita-coer-nucleus

## Description

Maps any niche domain into a structured talent and ecosystem landscape using the CoER method. Enables MCP clients to read landscapes and contribute new ones via PRs.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** maps-location
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mtn38ju7uw)
- **Repository:** <https://github.com/pastarita/coer-nucleus>

## 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": "pastarita-coer-nucleus"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pastarita-coer-nucleus` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pastarita-coer-nucleus/pull`

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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