# context-sherpa

> context-sherpa — hackafterdark-context-sherpa. Use this tool when you need to optimize AI coding agent performance and accuracy, as it provides code mapping, deterministic feedback loops, and tiered inference to streamline token usage. It solves problems related to inefficient coding and inaccurate outputs by offering a robust interface for git integration and feedback loops. Ideal for use cases requiring precise code generation and optimization, the Context Sherpa MCP server takes in coding inputs and outputs refined, accurate code mappings.

Canonical page: https://skillsregistry.net/skills/hackafterdark-context-sherpa  
JSON: https://api.skillsregistry.net/v1/skills/hackafterdark-context-sherpa

## Description

Context Sherpa MCP server provides code mapping, deterministic feedback loops, and tiered inference for AI coding agents to increase accuracy and optimize token usage.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/hackafterdark/context-sherpa)

## 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": "hackafterdark-context-sherpa"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hackafterdark-context-sherpa` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hackafterdark-context-sherpa/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