# SQLew

> Use this tool when you need to optimize database performance and reduce token duplication in multi-agent coordination, particularly for decision tracking, agent messaging, and file change monitoring. SQLew achieves this through intelligent database design and action-based tools, utilizing SQLite with normalized tables and pre-aggregated views. It is ideal for development projects requiring efficient token-efficient responses and comprehensive metadata organization.

Canonical page: https://skillsregistry.net/skills/sin5ddd-sqlew  
JSON: https://api.skillsregistry.net/v1/skills/sin5ddd-sqlew

## Description

SQLew is designed to achieve dramatic token reduction in context sharing between Claude Code sub-agents through intelligent database design and action-based tools. The implementation uses SQLite with normalized tables, integer enums, and pre-aggregated views to eliminate string duplication and provide token-efficient responses for decision tracking, agent messaging, file change monitoring, and constraint management. Built with automatic cleanup, weekend-aware retention policies, and comprehensive metadata organization through tags, layers, and scopes, it enables efficient multi-agent coordination in development projects while maintaining full transaction integrity and version history.

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/sin5ddd-sqlew)
- **Repository:** <https://github.com/sqlew-io/sqlew>

## 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": "sin5ddd-sqlew"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sin5ddd-sqlew` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sin5ddd-sqlew/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