# sift

> sift — slymnysr-sift. Use this tool when you need to efficiently process large command outputs, as it filters relevant lines and stores the rest on disk, solving data overload issues and providing a streamlined interface for model input. It takes command outputs as input and returns filtered lines, making it ideal for use cases like data processing and logging. Use sift in contexts where disk space is available and command output needs to be optimized for model consumption.

Canonical page: https://skillsregistry.net/skills/slymnysr-sift  
JSON: https://api.skillsregistry.net/v1/skills/slymnysr-sift

## Description

MCP server and CLI that runs your command, keeps every byte on disk, and gives the model only the lines that matter.

## Trust

- **Trust score (0–1):** 0.76
- **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/slymnysr/sift)

## 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": "slymnysr-sift"
    }
  }
}
```

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