# TokenDamper

> TokenDamper — epichlo-tokendamper. Use this tool when you need to optimize AI coding agent performance by refining universal context, solving issues with inefficient code generation and poor model understanding. It takes in AI model inputs and git repository data, producing optimized context outputs that improve coding accuracy and speed. Ideal for use cases where AI agents struggle with complex coding tasks or require enhanced contextual awareness.

Canonical page: https://skillsregistry.net/skills/epichlo-tokendamper  
JSON: https://api.skillsregistry.net/v1/skills/epichlo-tokendamper

## Description

Universal context optimization for AI coding agents.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/Epichlo/TokenDamper)

## 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": "epichlo-tokendamper"
    }
  }
}
```

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