# _gogol

> _gogol — tcmug-gogol. Use this tool when you need to leverage semantic memory for coding tasks, such as recalling code snippets or understanding project structures. It solves problems related to code organization, recall, and comprehension, particularly in git-based projects. The tool accepts code-related inputs and outputs relevant semantic information to aid coder agents in their development workflow.

Canonical page: https://skillsregistry.net/skills/tcmug-gogol  
JSON: https://api.skillsregistry.net/v1/skills/tcmug-gogol

## Description

Yet another vibe coded semantic memory tool for coder agents

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/tcmug/_gogol)

## 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": "tcmug-gogol"
    }
  }
}
```

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