# kagent-doc2vec-demo

> kagent-doc2vec-demo — charles-hsiao-kagent-doc2vec-demo. Use this tool when you need to vectorize and expose internal documentation, such as runbooks and incident post-mortems, to AI agents for enhanced knowledge retrieval and decision-making. It solves problems of information discovery and accessibility by converting text documents into vector representations that can be queried by AI agents. The tool takes in text documents as input and outputs vectorized representations via an MCP server interface.

Canonical page: https://skillsregistry.net/skills/charles-hsiao-kagent-doc2vec-demo  
JSON: https://api.skillsregistry.net/v1/skills/charles-hsiao-kagent-doc2vec-demo

## Description

A demo project showing how to use doc2vec to vectorize internal runbooks and incident post-mortems, then expose them to a kagent AI agent via an MCP server

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/charles-hsiao/kagent-doc2vec-demo)

## 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": "charles-hsiao-kagent-doc2vec-demo"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/charles-hsiao-kagent-doc2vec-demo` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/charles-hsiao-kagent-doc2vec-demo/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