# grepmem

> grepmem — wapa0012-grepmem. Use this tool when you need to efficiently store and retrieve information from HTML data without relying on vector embeddings or databases. It solves problems related to text-based data retrieval, providing a simple and effective way to search and access stored information. The tool takes in HTML data as input and outputs relevant results based on grep queries, making it ideal for use cases where fast and accurate text retrieval is necessary.

Canonical page: https://skillsregistry.net/skills/wapa0012-grepmem  
JSON: https://api.skillsregistry.net/v1/skills/wapa0012-grepmem

## Description

Vectorless agent memory. HTML storage + grep retrieval. LongMemEval-S R@5 = 98.9%. No embedding, no vector DB.

## 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:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/WAPA0012/grepmem)

## 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": "wapa0012-grepmem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/wapa0012-grepmem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/wapa0012-grepmem/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