# diting

> Use this tool when you need to perform comprehensive searches across multiple engines, requiring aggregated results with AI-driven scoring and summarization. It solves problems of information overload and manual search effort by providing a unified interface for parallel retrieval and insightful summaries. Ideal for use cases where in-depth research and knowledge discovery are critical, with inputs of search queries and outputs of ranked, summarized results.

Canonical page: https://skillsregistry.net/skills/odradekk-diting  
JSON: https://api.skillsregistry.net/v1/skills/odradekk-diting

## Description

Deep aggregated search MCP service with multi-engine parallel retrieval, LLM scoring, and summarization

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [GitHub](https://github.com/odradekk/diting)

## 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": "odradekk-diting"
    }
  }
}
```

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