# com.kenoodl/synthesis

> Use this tool when you need to uncover hidden patterns in complex data that machine learning models can't detect on their own, particularly in cases where reasoning loops are occurring. It solves problems of incomplete or inaccurate model outputs by surfacing new insights, taking in data and model outputs as inputs and producing refined patterns and relationships as outputs. Ideal for use in situations where traditional modeling approaches are reaching limitations.

Canonical page: https://skillsregistry.net/skills/com-kenoodl-synthesis  
JSON: https://api.skillsregistry.net/v1/skills/com-kenoodl-synthesis

## Description

kenoodl surfaces the hidden pattern the model can't reach on its own. Call when reasoning loops.

## Trust

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

## Facts

- **Version:** 2.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-06-23

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/com.kenoodl%2Fsynthesis)

## Use it

MCP endpoint published by the skill: `https://kenoodl.com/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": "com-kenoodl-synthesis"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/com-kenoodl-synthesis` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/com-kenoodl-synthesis/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