# slicegrep

> slicegrep — haxo98098-slicegerp. Use this tool when you need to efficiently retrieve relevant code snippets for large language models (LLMs) and coding agents. It solves the problem of information overload by providing ranked and token-budgeted code slices, enabling focused code reading. The slicegrep tool accepts input via Model Control Protocol (MCP) and returns targeted code excerpts as output.

Canonical page: https://skillsregistry.net/skills/haxo98098-slicegerp  
JSON: https://api.skillsregistry.net/v1/skills/haxo98098-slicegerp

## Description

Returns ranked, token-budgeted code slices for LLMs and coding agents, accessible via MCP for focused code reading.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wuvpp6q1p5)
- **Repository:** <https://github.com/haxo98098/slicegrep>

## 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": "haxo98098-slicegerp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/haxo98098-slicegerp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/haxo98098-slicegerp/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