# cv.d/talent

> Use this tool when you need to discover and identify top AI talent, as it provides a searchable database of agent-readable candidate profiles that can be easily cited via URL, solving recruitment and collaboration challenges in AI development and research contexts. It takes in search queries and outputs relevant candidate profiles, streamlining the talent acquisition process. Ideal for use cases where AI teams require skilled professionals with specific expertise.

Canonical page: https://skillsregistry.net/skills/cv-d-talent  
JSON: https://api.skillsregistry.net/v1/skills/cv-d-talent

## Description

Talent discovery for AI. Search and read agent-readable candidate profiles; cite by URL.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-07-04

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/cv.d%2Ftalent)

## Use it

MCP endpoint published by the skill: `https://d.cv/mcp`

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": "cv-d-talent"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cv-d-talent` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cv-d-talent/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