# wherewent

> wherewent — habibafaisal-wherewent. Use this tool when you need to identify and diagnose slow Python/SQLAlchemy jobs, as it provides a zero-config SQL profiler that returns compact machine-readable fields, including call site, query count, and suggested fix, to optimize performance and reduce API costs. It solves problems related to slow query execution and high API costs by providing a concise and actionable output. Ideal for use cases where raw query logs are cumbersome and costly, wherewent offers a efficient alternative for agents to quickly resolve performance issues.

Canonical page: https://skillsregistry.net/skills/habibafaisal-wherewent  
JSON: https://api.skillsregistry.net/v1/skills/habibafaisal-wherewent

## Description

Zero-config SQL profiler for slow Python/SQLAlchemy jobs, built for agents: returns the exact call site, query count, and fix as compact machine-readable fields instead of raw query logs~55× fewer tokens per diagnosis (≈10k → ≈180) and the matching drop in API cost.

## Trust

- **Trust score (0–1):** 0.44
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/va9m9h37ib)
- **Repository:** <https://github.com/habibafaisal/wherewent>

## 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": "habibafaisal-wherewent"
    }
  }
}
```

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