OpenGauss is a project-scoped Lean workflow orchestrator that gives coding agents a command-line interface for managing formal proof and formalization tasks. It is used with Lean projects to coordinate agents, tooling, backend sessions, and workflows supplied by lean4-skills. The catalogue add-ons operate these Gauss-native workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add math-inc/OpenGauss --skill qmdgit clone --depth 1 https://github.com/math-inc/OpenGaussWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/math-inc/opengauss/qmd)<a href="https://agentmods.dev/skills/math-inc/opengauss/qmd"><img src="https://agentmods.dev/badge/skills/math-inc/opengauss/qmd/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/math-inc/opengauss/qmd"><img src="https://agentmods.dev/badge/skills/math-inc/opengauss/qmd.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.03451 |
| Opus 5.5 | $0.00017 | $0.01380 |
| Sonnet 5.5 | $0.00009 | $0.00690 |
| Haiku 4.5 | $0.00004 | $0.00345 |
Grade B, and why
qmd scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
curl -fsSL https://deb.nodesource.com/setup_22.x | sudo -E bash - Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://deb.nodesource.com/setup_22.x | sudo -E bash - This is a copy
92% identical to qmd — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 442 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QMD — Query Markup Documents
Local, on-device search engine for personal knowledge bases. Indexes markdown notes, meeting transcripts, documentation, and any text-based files, then provides hybrid search combining keyword matching, semantic understanding, and LLM-powered reranking — all running locally with no cloud dependencies.
Created by Tobi Lütke. MIT licensed.
When to Use
- User asks to search their notes, docs, knowledge base, or meeting transcripts
- User wants to find something across a large collection of markdown/text files
- User wants semantic search ("find notes about X concept") not just keyword grep
- User has already set up qmd collections and wants to query them
- User asks to set up a local knowledge base or document search system
- Keywords: "search my notes", "find in my docs", "knowledge base", "qmd"
Prerequisites
Node.js >= 22 (required)
# Check version
node --version # must be >= 22
# macOS — install or upgrade via Homebrew
brew install node@22
# Linux — use NodeSource or nvm
curl -fsSL https://deb.nodesource.com/setup_22.x | sudo -E bash -
sudo apt-get install -y nodejs
# or with nvm:
nvm install 22 && nvm use 22
SQLite with Extension Support (macOS only)
macOS system SQLite lacks extension loading. Install via Homebrew:
brew install sqlite
Install qmd
npm install -g @tobilu/qmd
# or with Bun:
bun install -g @tobilu/qmd
First run auto-downloads 3 local GGUF models (~2GB total):
| Model | Purpose | Size |
|---|---|---|
| embeddinggemma-300M-Q8_0 | Vector embeddings | ~300MB |
| qwen3-reranker-0.6b-q8_0 | Result reranking | ~640MB |
| qmd-query-expansion-1.7B | Query expansion | ~1.1GB |
Verify Installation
qmd --version
qmd status
Quick Reference
| Command | What It Does | Speed |
|---|---|---|
qmd search "query" |
BM25 keyword search (no models) | ~0.2s |
qmd vsearch "query" |
Semantic vector search (1 model) | ~3s |
qmd query "query" |
Hybrid + reranking (all 3 models) | ~2-3s warm, ~19s cold |
qmd get <docid> |
Retrieve full document content | instant |
qmd multi-get "glob" |
Retrieve multiple files | instant |
qmd collection add <path> --name <n> |
Add a directory as a collection | instant |
qmd context add <path> "description" |
Add context metadata to improve retrieval | instant |
qmd embed |
Generate/update vector embeddings | varies |
qmd status |
Show index health and collection info | instant |
qmd mcp |
Start MCP server (stdio) | persistent |
qmd mcp --http --daemon |
Start MCP server (HTTP, warm models) | persistent |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 442 lines · 43 tokens per session scan B 23655f3a6ed4
qmd is a skill published in the GitHub repository math-inc/OpenGauss (1,270 stars, last pushed 6mo ago), licensed MIT. It adds 43 tokens to every session and 3,451 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 2 findings (asks for root, makes network calls). It is 92% identical to qmd, differing in 18 lines, and is treated as a copy.
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memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.