[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FVNFYYBJP7V545ZMNQEVTD":3,"skill-same:01M6FVNFYYBJP7V545ZMNQEVTD":82},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":55,"commitSha":56,"skillDirectory":57,"forksCount":58,"repositoryHtmlUrl":59,"repositoryHomepageUrl":6,"ownerHtmlUrl":60,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":61,"install":62,"resources":75},"01M6FVNFYYBJP7V545ZMNQEVTD","qmd",null,"Local hybrid search for markdown notes and docs. Use when searching notes, finding related content, or retrieving documents from indexed collections.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Flevineam\u002Fqmd-external\u002FSKILL.md",[],[5,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35],"Hybrid Search","docs","via","collections","local","bun install","bun","use","install","markdown","shell","https","content","search","notes","documents","linux","github","2026-11-10 10:12:30",false,"---\nname: qmd\ndescription: Local hybrid search for markdown notes and docs. Use when searching notes, finding related content, or retrieving documents from indexed collections.\nhomepage: https:\u002F\u002Fgithub.com\u002Ftobi\u002Fqmd\nmetadata: {\"clawdbot\":{\"emoji\":\"?\",\"os\":[\"darwin\",\"linux\"],\"requires\":{\"bins\":[\"qmd\"]},\"install\":[{\"id\":\"bun-qmd\",\"kind\":\"shell\",\"command\":\"bun install -g https:\u002F\u002Fgithub.com\u002Ftobi\u002Fqmd\",\"bins\":[\"qmd\"],\"label\":\"Install qmd via Bun\"}]}}\n---\n\n# qmd - Quick Markdown Search\n\nLocal search engine for Markdown notes, docs, and knowledge bases. Index once, search fast.\n\n## When to use (trigger phrases)\n\n- \"search my notes \u002F docs \u002F knowledge base\"\n- \"find related notes\"\n- \"retrieve a markdown document from my collection\"\n- \"search local markdown files\"\n\n## Default behavior (important)\n\n- Prefer `qmd search` (BM25). It's typically instant and should be the default.\n- Use `qmd vsearch` only when keyword search fails and you need semantic similarity (can be very slow on a cold start).\n- Avoid `qmd query` unless the user explicitly wants the highest quality hybrid results and can tolerate long runtimes\u002Ftimeouts.\n\n## Prerequisites\n\n- Bun >= 1.0.0\n- macOS: `brew install sqlite` (SQLite extensions)\n- Ensure PATH includes: `$HOME\u002F.bun\u002Fbin`\n\nInstall Bun (macOS): `brew install oven-sh\u002Fbun\u002Fbun`\n\n## Install\n\n`bun install -g https:\u002F\u002Fgithub.com\u002Ftobi\u002Fqmd`\n\n## Setup\n\n```bash\nqmd collection add \u002Fpath\u002Fto\u002Fnotes --name notes --mask \"**\u002F*.md\"\nqmd context add qmd:\u002F\u002Fnotes \"Description of this collection\"  # optional\nqmd embed  # one-time to enable vector + hybrid search\n```\n\n## What it indexes\n\n- Intended for Markdown collections (commonly `**\u002F*.md`).\n- In our testing, \"messy\" Markdown is fine: chunking is content-based (roughly a few hundred tokens per chunk), not strict heading\u002Fstructure based.\n- Not a replacement for code search; use code search tools for repositories\u002Fsource trees.\n\n## Search modes\n\n- `qmd search` (default): fast keyword match (BM25)\n- `qmd vsearch` (last resort): semantic similarity (vector). Often slow due to local LLM work before the vector lookup.\n- `qmd query` (generally skip): hybrid search + LLM reranking. Often slower than `vsearch` and may timeout.\n\n## Performance notes\n\n- `qmd search` is typically instant.\n- `qmd vsearch` can be ~1 minute on some machines because query expansion may load a local model (e.g., Qwen3-1.7B) into memory per run; the vector lookup itself is usually fast.\n- `qmd query` adds LLM reranking on top of `vsearch`, so it can be even slower and less reliable for interactive use.\n- If you need repeated semantic searches, consider keeping the process\u002Fmodel warm (e.g., a long-lived qmd\u002FMCP server mode if available in your setup) rather than invoking a cold-start LLM each time.\n\n## Common commands\n\n```bash\nqmd search \"query\"             # default\nqmd vsearch \"query\"\nqmd query \"query\"\nqmd search \"query\" -c notes     # Search specific collection\nqmd search \"query\" -n 10        # More results\nqmd search \"query\" --json       # JSON output\nqmd search \"query\" --all --files --min-score 0.3\n```\n\n## Useful options\n\n- `-n \u003Cnum>`: number of results\n- `-c, --collection \u003Cname>`: restrict to a collection\n- `--all --min-score \u003Cnum>`: return all matches above a threshold\n- `--json` \u002F `--files`: agent-friendly output formats\n- `--full`: return full document content\n\n## Retrieve\n\n```bash\nqmd get \"path\u002Fto\u002Ffile.md\"       # Full document\nqmd get \"#docid\"                # By ID from search results\nqmd multi-get \"journals\u002F2025-05*.md\"\nqmd multi-get \"doc1.md, doc2.md, #abc123\" --json\n```\n\n## Maintenance\n\n```bash\nqmd status                      # Index health\nqmd update                      # Re-index changed files\nqmd embed                       # Update embeddings\n```\n\n### Keeping the index fresh\n\nSet up a cron job or hook to automatically re-index. For example, a daily 5 AM reindex:\n\n```bash\n# Via Clawdbot cron (isolated job, runs silently):\nclawdbot cron add \\\n  --name \"qmd-reindex\" \\\n  --cron \"0 5 * * *\" \\\n  --tz \"America\u002FNew_York\" \\\n  --session isolated \\\n  --message \"Run: export PATH=\\\"\\$HOME\u002F.bun\u002Fbin:\\$PATH\\\" && qmd update && qmd embed\" \n\n# Or via system crontab:\n0 5 * * * export PATH=\"$HOME\u002F.bun\u002Fbin:$PATH\" && qmd update && qmd embed\n```\n\nThis ensures your vault search stays current as you add or edit notes.\n\n## Models and cache\n\n- Uses local GGUF models; first run auto-downloads them.\n- Default cache: `~\u002F.cache\u002Fqmd\u002Fmodels\u002F` (override with `XDG_CACHE_HOME`).\n\n## Relationship to Clawdbot memory search\n\n- `qmd` searches *your local files* (notes\u002Fdocs) that you explicitly index into collections.\n- Clawdbot's `memory_search` searches *agent memory* (saved facts\u002Fcontext from prior interactions).\n- Use both: `memory_search` for \"what did we decide\u002Flearn before?\", `qmd` for \"what's in my notes\u002Fdocs on disk?\".\n","# qmd - Quick Markdown Search\n\nLocal search engine for Markdown notes, docs, and knowledge bases. Index once, search fast.\n\n## When to use (trigger phrases)\n\n- \"search my notes \u002F docs \u002F knowledge base\"\n- \"find related notes\"\n- \"retrieve a markdown document from my collection\"\n- \"search local markdown files\"\n\n## Default behavior (important)\n\n- Prefer `qmd search` (BM25). It's typically instant and should be the default.\n- Use `qmd vsearch` only when keyword search fails and you need semantic similarity (can be very slow on a cold start).\n- Avoid `qmd query` unless the user explicitly wants the highest quality hybrid results and can tolerate long runtimes\u002Ftimeouts.\n\n## Prerequisites\n\n- Bun >= 1.0.0\n- macOS: `brew install sqlite` (SQLite extensions)\n- Ensure PATH includes: `$HOME\u002F.bun\u002Fbin`\n\nInstall Bun (macOS): `brew install oven-sh\u002Fbun\u002Fbun`\n\n## Install\n\n`bun install -g https:\u002F\u002Fgithub.com\u002Ftobi\u002Fqmd`\n\n## Setup\n\n```bash\nqmd collection add \u002Fpath\u002Fto\u002Fnotes --name notes --mask \"**\u002F*.md\"\nqmd context add qmd:\u002F\u002Fnotes \"Description of this collection\"  # optional\nqmd embed  # one-time to enable vector + hybrid search\n```\n\n## What it indexes\n\n- Intended for Markdown collections (commonly `**\u002F*.md`).\n- In our testing, \"messy\" Markdown is fine: chunking is content-based (roughly a few hundred tokens per chunk), not strict heading\u002Fstructure based.\n- Not a replacement for code search; use code search tools for repositories\u002Fsource trees.\n\n## Search modes\n\n- `qmd search` (default): fast keyword match (BM25)\n- `qmd vsearch` (last resort): semantic similarity (vector). Often slow due to local LLM work before the vector lookup.\n- `qmd query` (generally skip): hybrid search + LLM reranking. Often slower than `vsearch` and may timeout.\n\n## Performance notes\n\n- `qmd search` is typically instant.\n- `qmd vsearch` can be ~1 minute on some machines because query expansion may load a local model (e.g., Qwen3-1.7B) into memory per run; the vector lookup itself is usually fast.\n- `qmd query` adds LLM reranking on top of `vsearch`, so it can be even slower and less reliable for interactive use.\n- If you need repeated semantic searches, consider keeping the process\u002Fmodel warm (e.g., a long-lived qmd\u002FMCP server mode if available in your setup) rather than invoking a cold-start LLM each time.\n\n## Common commands\n\n```bash\nqmd search \"query\"             # default\nqmd vsearch \"query\"\nqmd query \"query\"\nqmd search \"query\" -c notes     # Search specific collection\nqmd search \"query\" -n 10        # More results\nqmd search \"query\" --json       # JSON output\nqmd search \"query\" --all --files --min-score 0.3\n```\n\n## Useful options\n\n- `-n \u003Cnum>`: number of results\n- `-c, --collection \u003Cname>`: restrict to a collection\n- `--all --min-score \u003Cnum>`: return all matches above a threshold\n- `--json` \u002F `--files`: agent-friendly output formats\n- `--full`: return full document content\n\n## Retrieve\n\n```bash\nqmd get \"path\u002Fto\u002Ffile.md\"       # Full document\nqmd get \"#docid\"                # By ID from search results\nqmd multi-get \"journals\u002F2025-05*.md\"\nqmd multi-get \"doc1.md, doc2.md, #abc123\" --json\n```\n\n## Maintenance\n\n```bash\nqmd status                      # Index health\nqmd update                      # Re-index changed files\nqmd embed                       # Update embeddings\n```\n\n### Keeping the index fresh\n\nSet up a cron job or hook to automatically re-index. For example, a daily 5 AM reindex:\n\n```bash\n# Via Clawdbot cron (isolated job, runs silently):\nclawdbot cron add \\\n  --name \"qmd-reindex\" \\\n  --cron \"0 5 * * *\" \\\n  --tz \"America\u002FNew_York\" \\\n  --session isolated \\\n  --message \"Run: export PATH=\\\"\\$HOME\u002F.bun\u002Fbin:\\$PATH\\\" && qmd update && qmd embed\" \n\n# Or via system crontab:\n0 5 * * * export PATH=\"$HOME\u002F.bun\u002Fbin:$PATH\" && qmd update && qmd embed\n```\n\nThis ensures your vault search stays current as you add or edit notes.\n\n## Models and cache\n\n- Uses local GGUF models; first run auto-downloads them.\n- Default cache: `~\u002F.cache\u002Fqmd\u002Fmodels\u002F` (override with `XDG_CACHE_HOME`).\n\n## Relationship to Clawdbot memory search\n\n- `qmd` searches *your local files* (notes\u002Fdocs) that you explicitly index into collections.\n- Clawdbot's `memory_search` searches *agent memory* (saved facts\u002Fcontext from prior interactions).\n- Use both: `memory_search` for \"what did we decide\u002Flearn before?\", `qmd` for \"what's in my notes\u002Fdocs on disk?\".\n",{"name":5,"homepage":41,"metadata":42,"description":7},"https:\u002F\u002Fgithub.com\u002Ftobi\u002Fqmd",{"clawdbot":43},{"os":44,"emoji":46,"install":47,"requires":53},[45,34],"darwin","?",[48],{"id":49,"bins":50,"kind":28,"label":51,"command":52},"bun-qmd",[5],"Install qmd via Bun","bun install -g https:\u002F\u002Fgithub.com\u002Ftobi\u002Fqmd",{"bins":54},[5],"main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Flevineam\u002Fqmd-external",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":8,"skillName":5,"commands":63,"prompt":73,"zipAvailable":74},[64,67,70],{"tool":65,"command":66},"npx","npx skills add kbarbel640-del\u002Fskills --skill qmd",{"tool":68,"command":69},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill qmd",{"tool":71,"command":72},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill qmd","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Flevineam\u002Fqmd-external\u002FSKILL.md",true,[76],{"path":77,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":80,"sourceHtmlUrl":81},"_meta.json","REFERENCE","参考文档",300,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Flevineam\u002Fqmd-external\u002F_meta.json",[83,112,140,160,166,185],{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":94,"publishedAt":36},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[89],{"categoryNo":90,"categoryName":91,"taxonomyType":92,"taxonomyTypeDesc":93},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,29,30,111],"crowd prompting","prompting","api","with","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","ai agents",{"skillNo":113,"name":114,"nameZh":6,"description":115,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":116,"categories":117,"keywords":123,"publishedAt":36},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[118],{"categoryNo":119,"categoryName":120,"taxonomyType":121,"taxonomyTypeDesc":122},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[124,97,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,102,25],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking",{"skillNo":141,"name":142,"nameZh":6,"description":143,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":144,"categories":145,"keywords":149,"publishedAt":36},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[146],{"categoryNo":147,"categoryName":148,"taxonomyType":121,"taxonomyTypeDesc":122},"01JBSEEDCAT000000000000021","资料检索与研究",[150,151,152,153,154,155,156,98,157,138,25,158,97,159,20],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http",{"skillNo":161,"name":142,"nameZh":6,"description":143,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":165,"publishedAt":36},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[164],{"categoryNo":147,"categoryName":148,"taxonomyType":121,"taxonomyTypeDesc":122},[153,152,151,150,20,155,156,98,154,138,25,157,158,97,159],{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":172,"publishedAt":36},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[173,174,175,176,177,178,179,34,180,181,182,183,184],"git","summary","git summary","commits","repository","win32","status","contributors","true","quick","get","branches",{"skillNo":186,"name":187,"nameZh":6,"description":188,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":189,"categories":190,"keywords":195,"publishedAt":36},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[191,192],{"categoryNo":119,"categoryName":120,"taxonomyType":121,"taxonomyTypeDesc":122},{"categoryNo":193,"categoryName":194,"taxonomyType":92,"taxonomyTypeDesc":93},"01JBSEEDCAT000000000000037","律师与法务",[196,197,198,199,98,200,201,55,202,158,203,204,205,206,207,29,208,209,35],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance"]