# basal-ganglia-memory

> basal-ganglia-memory — impkind-basal-ganglia-memory. Use this tool when you need to enable habit formation and procedural learning in AI systems, solving problems related to automation of repetitive tasks and skill acquisition through practice. It takes in patterns of behavior and outputs learned habits and procedures, allowing for more efficient and adaptive AI performance. This tool is particularly useful in contexts where repetitive tasks or skills need to be automated, such as robotics or game playing.

Canonical page: https://skillsregistry.net/skills/impkind-basal-ganglia-memory  
JSON: https://api.skillsregistry.net/v1/skills/impkind-basal-ganglia-memory

## Description

Habit formation and procedural learning for AI.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-21

## Facts

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

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/impkind-basal-ganglia-memory)

## 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": "impkind-basal-ganglia-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/impkind-basal-ganglia-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/impkind-basal-ganglia-memory/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