# Observer

> Observer — hec-ovi-observer-skill. Use this tool when you need to enhance video learning with AI-driven transcription, concept visualization, and interactive Q&A. The Observer tool solves problems of manual note-taking, concept comprehension, and context-based inquiry by providing synchronized transcript reading, concept mapping, and artifact building. It takes video input and outputs transcriptions, concepts, and visuals, making it ideal for educational, training, or research contexts where interactive video analysis is required.

Canonical page: https://skillsregistry.net/skills/hec-ovi-observer-skill  
JSON: https://api.skillsregistry.net/v1/skills/hec-ovi-observer-skill

## Description

Enables watching videos with an AI coding agent that transcribes, prepares concepts and visuals, and answers questions in context of the video. Provides MCP tools for transcript reading, concept mapping, artifact building, and interactive Q&A synchronized with playback.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/intpqgvmw9)
- **Repository:** <https://github.com/hec-ovi/observer-skill>

## 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": "hec-ovi-observer-skill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hec-ovi-observer-skill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hec-ovi-observer-skill/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