[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7533G9T5NETRWSNHVM5AH0F":3,"skill-same:01M7533G9T5NETRWSNHVM5AH0F":45},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":24,"commitSha":25,"skillDirectory":26,"forksCount":14,"repositoryHtmlUrl":27,"repositoryHomepageUrl":6,"ownerHtmlUrl":28,"ownerBlogUrl":29,"ownerDescription":6,"updatedAt":30,"install":31,"resources":44},"01M7533G9T5NETRWSNHVM5AH0F","knowledge-agent",null,"Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused \"brains\" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.","longhang2004\u002FTenvyr","longhang2004","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F149140492?v=4","01M752YHWXV1V7TNHCK1P2SNK3","Hàng Nhựt Long","01M752YHYMBBTCMQ391XSES647",0,"MIT","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Fknowledge-agent\u002FSKILL.md",[],[],"2026-11-12 13:55:43",false,"---\nname: knowledge-agent\ndescription: Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused \"brains\" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.\n---\n\n# Knowledge Agent\n\nBuild and query AI-powered knowledge bases from claude-mem observations.\n\n## What Are Knowledge Agents?\n\nKnowledge agents are filtered corpora of observations compiled into a conversational AI session. Build a corpus from your observation history, prime it (loads the knowledge into an AI session), then ask it questions conversationally.\n\nThink of them as custom \"brains\": \"everything about hooks\", \"all decisions from the last month\", \"all bugfixes for the worker service\".\n\n## Workflow\n\n### Step 1: Build a corpus\n\n```text\nbuild_corpus name=\"hooks-expertise\" description=\"Everything about the hooks lifecycle\" project=\"claude-mem\" concepts=\"hooks\" limit=500\n```\n\nFilter options:\n- `project` — filter by project name\n- `types` — comma-separated: decision, bugfix, feature, refactor, discovery, change\n- `concepts` — comma-separated concept tags\n- `files` — comma-separated file paths (prefix match)\n- `query` — semantic search query\n- `dateStart` \u002F `dateEnd` — ISO date range\n- `limit` — max observations (default 500)\n\n### Step 2: Prime the corpus\n\n```text\nprime_corpus name=\"hooks-expertise\"\n```\n\nThis creates an AI session loaded with all the corpus knowledge. Takes a moment for large corpora.\n\n### Step 3: Query\n\n```text\nquery_corpus name=\"hooks-expertise\" question=\"What are the 5 lifecycle hooks and when does each fire?\"\n```\n\nThe knowledge agent answers from its corpus. Follow-up questions maintain context.\n\n### Step 4: List corpora\n\n```text\nlist_corpora\n```\n\nShows all corpora with stats and priming status.\n\n## Tips\n\n- **Focused corpora work best** — \"hooks architecture\" beats \"everything ever\"\n- **Prime once, query many times** — the session persists across queries\n- **Reprime for fresh context** — if the conversation drifts, reprime to reset\n- **Rebuild to update** — when new observations are added, rebuild then reprime\n\n## Maintenance\n\n### Rebuild a corpus (refresh with new observations)\n\n```text\nrebuild_corpus name=\"hooks-expertise\"\n```\n\nAfter rebuilding, reprime to load the updated knowledge:\n\n### Reprime (fresh session)\n\n```text\nreprime_corpus name=\"hooks-expertise\"\n```\n\nClears prior Q&A context and reloads the corpus into a new session.\n","# Knowledge Agent\n\nBuild and query AI-powered knowledge bases from claude-mem observations.\n\n## What Are Knowledge Agents?\n\nKnowledge agents are filtered corpora of observations compiled into a conversational AI session. Build a corpus from your observation history, prime it (loads the knowledge into an AI session), then ask it questions conversationally.\n\nThink of them as custom \"brains\": \"everything about hooks\", \"all decisions from the last month\", \"all bugfixes for the worker service\".\n\n## Workflow\n\n### Step 1: Build a corpus\n\n```text\nbuild_corpus name=\"hooks-expertise\" description=\"Everything about the hooks lifecycle\" project=\"claude-mem\" concepts=\"hooks\" limit=500\n```\n\nFilter options:\n- `project` — filter by project name\n- `types` — comma-separated: decision, bugfix, feature, refactor, discovery, change\n- `concepts` — comma-separated concept tags\n- `files` — comma-separated file paths (prefix match)\n- `query` — semantic search query\n- `dateStart` \u002F `dateEnd` — ISO date range\n- `limit` — max observations (default 500)\n\n### Step 2: Prime the corpus\n\n```text\nprime_corpus name=\"hooks-expertise\"\n```\n\nThis creates an AI session loaded with all the corpus knowledge. Takes a moment for large corpora.\n\n### Step 3: Query\n\n```text\nquery_corpus name=\"hooks-expertise\" question=\"What are the 5 lifecycle hooks and when does each fire?\"\n```\n\nThe knowledge agent answers from its corpus. Follow-up questions maintain context.\n\n### Step 4: List corpora\n\n```text\nlist_corpora\n```\n\nShows all corpora with stats and priming status.\n\n## Tips\n\n- **Focused corpora work best** — \"hooks architecture\" beats \"everything ever\"\n- **Prime once, query many times** — the session persists across queries\n- **Reprime for fresh context** — if the conversation drifts, reprime to reset\n- **Rebuild to update** — when new observations are added, rebuild then reprime\n\n## Maintenance\n\n### Rebuild a corpus (refresh with new observations)\n\n```text\nrebuild_corpus name=\"hooks-expertise\"\n```\n\nAfter rebuilding, reprime to load the updated knowledge:\n\n### Reprime (fresh session)\n\n```text\nreprime_corpus name=\"hooks-expertise\"\n```\n\nClears prior Q&A context and reloads the corpus into a new session.\n",{"name":5,"description":7},"main","fa33bab5e066f61f678d15d8654b7f16fcb5aef0","skills\u002Fknowledge-agent","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr","https:\u002F\u002Fgithub.com\u002Flonghang2004","https:\u002F\u002Flonghang2004.github.io\u002Fportfolio-website\u002F","2026-10-17 00:52:25",{"source":8,"skillName":5,"commands":32,"prompt":42,"zipAvailable":43},[33,36,39],{"tool":34,"command":35},"npx","npx skills add longhang2004\u002FTenvyr --skill knowledge-agent",{"tool":37,"command":38},"bunx","bunx skills add longhang2004\u002FTenvyr --skill knowledge-agent",{"tool":40,"command":41},"pnpm","pnpm dlx skills add longhang2004\u002FTenvyr --skill knowledge-agent","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Fknowledge-agent\u002FSKILL.md",true,[],[46,53,60,67,74,81],{"skillNo":47,"name":48,"nameZh":6,"description":49,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":50,"categories":51,"keywords":52,"publishedAt":19},"01M75368XG3WHG7S884RH1FQEG","wowerpoint","Turn one document into a kawaii NotebookLM slide-deck PDF. Use for \"wowerpoint this\", \"make a deck about \u003Cfile>\", \"turn this report into slides\", or any request to render a single document as shareable narrative slides.","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Fwowerpoint\u002FSKILL.md",[],[],{"skillNo":54,"name":55,"nameZh":6,"description":56,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":57,"categories":58,"keywords":59,"publishedAt":19},"01M7536783K0EKKQ66A56RJ262","what-the","What the? Use when the user wants a plain-English breakdown of something technical — the who, what, where, why, and when.","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Fwhat-the\u002FSKILL.md",[],[],{"skillNo":61,"name":62,"nameZh":6,"description":63,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":64,"categories":65,"keywords":66,"publishedAt":19},"01M75362M917THP79D9APYRKTE","weekly-digests","Generate a serial week-by-week narrative digest of a project's full claude-mem timeline. Splits the timeline into per-ISO-week files, then runs one consecutive subagent per week — each receiving the prior week's carry-forward block — to produce one chapter per ISO week of data. Use when asked for \"weekly digests\", \"week-by-week story\", \"serial timeline\", or \"narrative chapters\" of a project's history.","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Fweekly-digests\u002FSKILL.md",[],[],{"skillNo":68,"name":69,"nameZh":6,"description":70,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":71,"categories":72,"keywords":73,"publishedAt":19},"01M7535ZRATN41PZHPPWZEBM8E","version-bump","Automated semantic versioning and release workflow for Claude Code plugins. Handles version increments across package.json, marketplace.json, plugin.json manifests, build verification, git tagging, GitHub releases, and changelog generation. NPM publishing (so `npx claude-mem@X.Y.Z` resolves) is handed off to the human maintainer, who raised npm security.","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Fversion-bump\u002FSKILL.md",[],[],{"skillNo":75,"name":76,"nameZh":6,"description":77,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":78,"categories":79,"keywords":80,"publishedAt":19},"01M7535VQDD9MXAYXH6N2E8FFJ","understand","Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Funderstand\u002FSKILL.md",[],[],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":19},"01M7535T2XNDGZP1GD2AD8VHEW","understand-onboard","Use when you need to generate an onboarding guide for new team members joining a project","https:\u002F\u002Fgithub.com\u002Flonghang2004\u002FTenvyr\u002Fblob\u002Fmain\u002Fskills\u002Funderstand-onboard\u002FSKILL.md",[],[]]