# m2wise

> m2wise — zengyi-thinking-m2wise. Use this tool when you need to leverage knowledge retrieval and reasoning capabilities to inform decision-making and problem-solving. The m2wise engine takes in large datasets and complex queries as inputs, generating insightful outputs that solve real-world problems. Ideal for applications requiring intelligent information processing, such as expert systems, virtual assistants, and data-driven analytics.

Canonical page: https://skillsregistry.net/skills/zengyi-thinking-m2wise  
JSON: https://api.skillsregistry.net/v1/skills/zengyi-thinking-m2wise

## Description

Memory-to-Wisdom Engine for AI agents.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-24

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-09-13

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/zengyi-thinking-m2wise)

## 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": "zengyi-thinking-m2wise"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zengyi-thinking-m2wise` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zengyi-thinking-m2wise/pull`

---
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