# banana-cog

> Use this tool when you need to integrate cellular and cognitive functionalities, as Banana Cog combines the strengths of Banana and CellCog to solve complex problems. It accepts various inputs and provides outputs that facilitate informed decision-making and efficient processing. Ideal for use cases that require synergistic cellular and cognitive capabilities, such as data analysis and knowledge representation.

Canonical page: https://skillsregistry.net/skills/nitishgargiitd-banana-cog  
JSON: https://api.skillsregistry.net/v1/skills/nitishgargiitd-banana-cog

## Description

Banana Cog × CellCog.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-05-17

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/nitishgargiitd-banana-cog)

## 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": "nitishgargiitd-banana-cog"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nitishgargiitd-banana-cog` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nitishgargiitd-banana-cog/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