Enables local hybrid memory search and embedding using QMD to reduce API costs by $50-300/month with automatic setup, smart indexing, and multi-agent sharing.
数据来源：ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一：命令行安装（推荐）
推荐（无需提前安装 clawhub）
npx clawhub@latest --dir ~/.claude/skills install qmd-memory或使用 clawhub CLI（需提前安装）
clawhub --dir ~/.claude/skills install qmd-memory⚠️ 需要 Node.js 18+，没有 Node？请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二：手动下载安装（无需 Node）
下载 ZIP，解压后将文件夹放到以下路径，重启 Agent 即可：
安装路径
~/.claude/skills/qmd-memory/💡解压后将文件夹放到上方路径，重启 Agent 即可生效
Author: As Above Technologies Version: 1.0.0 ClawHub: [Coming Soon]
---
| Operation | API Cost | Frequency | Monthly Cost | |-----------|----------|-----------|--------------| | memory_search (embedding) | $0.02-0.05 | 50-200/day | $30-300 | | Context retrieval | $0.01-0.03 | 100+/day | $30-90 | | Semantic queries | $0.03-0.08 | 20-50/day | $18-120 | | TOTAL | | | $78-510/month |
| Operation | Cost | Why | |-----------|------|-----| | All searches | $0 | Runs on your machine | | Embeddings | $0 | Local GGUF models | | Re-ranking | $0 | Local LLM |
Your savings: $50-300+/month
One-time setup. Forever free searches.
---
# Install the skill
clawhub install asabove/qmd-memory
# Run setup (installs QMD, configures collections)
openclaw skill run qmd-memory setup
# That's it. Your memory is now supercharged.---
Based on your workspace structure, we create optimized collections:
✓ workspace — Core agent files (MEMORY.md, SOUL.md, etc.)
✓ daily-logs — memory/*.md daily logs
✓ intelligence — intelligence/*.md (if exists)
✓ projects — projects/**/*.md (if exists)
✓ documents — Any additional doc folders you specifyWe add context to each collection so QMD understands what's where:
qmd://workspace → "Agent identity and configuration files"
qmd://daily-logs → "Daily work logs and session history"
qmd://intelligence → "Analysis, research, and reference documents"# Auto-update index (nightly at 3am)
0 3 * * * qmd update && qmd embed
# Keep your memory fresh without thinking about itMemory search now uses QMD automatically:
memory_search → routes to QMD hybrid searchmemory_get → retrieves from QMD collections# Start shared memory server
openclaw skill run qmd-memory serve
# All your agents can now query collective memory
# Forge, Thoth, Axis — shared knowledge base---
| Mode | Command | Best For | |------|---------|----------| | Keyword | qmd search "query" | Exact matches, fast | | Semantic | qmd vsearch "query" | Conceptual similarity | | Hybrid | qmd query "query" | Best quality (recommended) |
# Find exact mentions
qmd search "Charlene" -n 5
# Find conceptually related content
qmd vsearch "how should we handle customer complaints"
# Best quality — expansion + reranking
qmd query "what decisions did we make about pricing strategy"
# Search specific collection
qmd search "API keys" -c workspace---
openclaw skill run qmd-memory add-collection ~/Documents/research --name researchopenclaw skill run qmd-memory add-context qmd://research "Market research and competitive analysis"openclaw skill run qmd-memory refresh---
openclaw skill run qmd-memory template tradingCreates:
intelligence — Trading systems, dashboards, signalsmarket-data — Price history, analysisresearch — Due diligence, reportsdaily-logs — Trade journalopenclaw skill run qmd-memory template contentCreates:
articles — Published contentdrafts — Work in progressresearch — Source materialideas — Brainstorms, notesopenclaw skill run qmd-memory template developerCreates:
docs — Documentationnotes — Technical notesdecisions — ADRs, architecture decisionssnippets — Code snippets, examples---
Run this to see your estimated savings:
openclaw skill run qmd-memory calculate-savingsOutput:
Your Current API Memory Costs (estimated):
memory_search calls/day: ~75
Average cost per call: $0.03
Monthly API cost: $67.50
With QMD Local:
Monthly cost: $0.00
YOUR MONTHLY SAVINGS: $67.50
YOUR ANNUAL SAVINGS: $810.00
ROI on skill purchase: 40x (if skill was $20)---
| Model | Purpose | Size | |-------|---------|------| | embeddinggemma-300M-Q8_0 | Vector embeddings | ~300MB | | qwen3-reranker-0.6b-q8_0 | Re-ranking results | ~640MB | | qmd-query-expansion-1.7B-q4_k_m | Query expansion | ~1.1GB |
Total: ~2GB (one-time download)
~/.cache/qmd/
├── index.sqlite # Search index
├── models/ # GGUF models
└── mcp.pid # MCP server PID (if running)---
Questions?
Found it valuable?
---
MIT — Use freely, modify as needed.
QMD itself is created by Tobi Lütke (github.com/tobi/qmd). This skill provides easy OpenClaw integration.
---
"Stop paying for memory. Start compounding knowledge."
As Above Technologies — Agent Infrastructure for Humans
安装 QMD Memory 后，可以对 AI 说这些话来触发它
Help me get started with QMD Memory
Explains what QMD Memory does, walks through the setup, and runs a quick demo based on your current project
Use QMD Memory to local hybrid memory search and embedding using QMD to reduce API co...
Invokes QMD Memory with the right parameters and returns the result directly in the conversation
What can I do with QMD Memory in my documents & notes workflow?
Lists the top use cases for QMD Memory, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/qmd-memory/ 目录（个人级，所有项目可用），或 .claude/skills/qmd-memory/（项目级）。重启 AI 客户端后，用 /qmd-memory 主动调用，或让 AI 根据上下文自动发现并使用。
QMD Memory 支持 Claude、Cursor、OpenClaw，可与这些 AI 平台无缝集成，扩展其能力。
QMD Memory 可免费安装使用。请查阅仓库了解许可证信息。
Enables local hybrid memory search and embedding using QMD to reduce API costs by $50-300/month with automatic setup, smart indexing, and multi-agent sharing.
QMD Memory 属于「Documents & Notes」分类，该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my documents & notes tasks using QMD Memory
Identifies repetitive steps in your workflow and sets up QMD Memory to handle them automatically