[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7BGFQCEEQTYPYGCRAZ3CV0F":3,"skill-same:01M7BGFQCEEQTYPYGCRAZ3CV0F":49},{"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":26,"commitSha":27,"skillDirectory":28,"forksCount":29,"repositoryHtmlUrl":30,"repositoryHomepageUrl":31,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":33,"updatedAt":34,"install":35,"resources":48},"01M7BGFQCEEQTYPYGCRAZ3CV0F","understand-chat",null,"Use when you need to ask questions about a codebase or understand code using a knowledge graph","YYC-Cube\u002FYYC3-Knowledge-Base","YYC-Cube","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F235006543?v=4","01M79J2PH4SWD2X0825X6PN748","yyc3","01M79J2PHVK3F6ZBYT8K2SCZCW",1,"MIT","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-AI-应用工具\u002FYYC3-AI-应用工具-Understand-Anything\u002Funderstand-anything-plugin\u002Fskills\u002Funderstand-chat\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: understand-chat\ndescription: Use when you need to ask questions about a codebase or understand code using a knowledge graph\nargument-hint: [query]\n---\n\n# \u002Funderstand-chat\n\nAnswer questions about this codebase using the knowledge graph at `.understand-anything\u002Fknowledge-graph.json`.\n\n## Graph Structure Reference\n\nThe knowledge graph JSON has this structure:\n- `project` — {name, description, languages, frameworks, analyzedAt, gitCommitHash}\n- `nodes[]` — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}\n  - Code node types: file, function, class, module, concept\n  - Non-code node types: config, document, service, table, endpoint, pipeline, schema, resource\n  - Domain\u002Fknowledge node types: domain, flow, step, article, entity, topic, claim, source\n  - IDs use the node type as prefix, e.g. `file:path`, `function:path:name`, `config:path`, `article:path`\n- `edges[]` — each has {source, target, type, direction, weight}\n  - Key types: imports, contains, calls, depends_on, configures, documents, deploys, triggers, contains_flow, flow_step, related, cites\n- `layers[]` — each has {id, name, description, nodeIds[]}\n- `tour[]` — each has {order, title, description, nodeIds[]}\n\n## How to Read Efficiently\n\n1. Use Grep to search within the JSON for relevant entries BEFORE reading the full file\n2. Only read sections you need — don't dump the entire graph into context\n3. Node names and summaries are the most useful fields for understanding\n4. Edges tell you how components connect — follow imports and calls for dependency chains\n\n## Instructions\n\n1. Check that `.understand-anything\u002Fknowledge-graph.json` exists in the current project root. If not, tell the user to run `\u002Funderstand` first.\n\n2. **Read project metadata only** — use Grep or Read with a line limit to extract just the `\"project\"` section from the top of the file for context (name, description, languages, frameworks).\n\n3. **Search for relevant nodes** — use Grep to search the knowledge graph file for the user's query keywords: \"$ARGUMENTS\"\n   - Search `\"name\"` fields: `grep -i \"query_keyword\"` in the graph file\n   - Search `\"summary\"` fields for semantic matches\n   - Search `\"tags\"` arrays for topic matches\n   - Note the `id` values of all matching nodes\n\n4. **Find connected edges** — for each matched node ID, Grep for that ID in the `edges` section to find:\n   - What it imports or depends on (downstream)\n   - What calls or imports it (upstream)\n   - This gives you the 1-hop subgraph around the query\n\n5. **Read layer context** — Grep for `\"layers\"` to understand which architectural layers the matched nodes belong to.\n\n6. **Answer the query** using only the relevant subgraph:\n   - Reference specific files, functions, and relationships from the graph\n   - Explain which layer(s) are relevant and why\n   - Be concise but thorough — link concepts to actual code locations\n   - If the query doesn't match any nodes, say so and suggest related terms from the graph\n","# \u002Funderstand-chat\n\nAnswer questions about this codebase using the knowledge graph at `.understand-anything\u002Fknowledge-graph.json`.\n\n## Graph Structure Reference\n\nThe knowledge graph JSON has this structure:\n- `project` — {name, description, languages, frameworks, analyzedAt, gitCommitHash}\n- `nodes[]` — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}\n  - Code node types: file, function, class, module, concept\n  - Non-code node types: config, document, service, table, endpoint, pipeline, schema, resource\n  - Domain\u002Fknowledge node types: domain, flow, step, article, entity, topic, claim, source\n  - IDs use the node type as prefix, e.g. `file:path`, `function:path:name`, `config:path`, `article:path`\n- `edges[]` — each has {source, target, type, direction, weight}\n  - Key types: imports, contains, calls, depends_on, configures, documents, deploys, triggers, contains_flow, flow_step, related, cites\n- `layers[]` — each has {id, name, description, nodeIds[]}\n- `tour[]` — each has {order, title, description, nodeIds[]}\n\n## How to Read Efficiently\n\n1. Use Grep to search within the JSON for relevant entries BEFORE reading the full file\n2. Only read sections you need — don't dump the entire graph into context\n3. Node names and summaries are the most useful fields for understanding\n4. Edges tell you how components connect — follow imports and calls for dependency chains\n\n## Instructions\n\n1. Check that `.understand-anything\u002Fknowledge-graph.json` exists in the current project root. If not, tell the user to run `\u002Funderstand` first.\n\n2. **Read project metadata only** — use Grep or Read with a line limit to extract just the `\"project\"` section from the top of the file for context (name, description, languages, frameworks).\n\n3. **Search for relevant nodes** — use Grep to search the knowledge graph file for the user's query keywords: \"$ARGUMENTS\"\n   - Search `\"name\"` fields: `grep -i \"query_keyword\"` in the graph file\n   - Search `\"summary\"` fields for semantic matches\n   - Search `\"tags\"` arrays for topic matches\n   - Note the `id` values of all matching nodes\n\n4. **Find connected edges** — for each matched node ID, Grep for that ID in the `edges` section to find:\n   - What it imports or depends on (downstream)\n   - What calls or imports it (upstream)\n   - This gives you the 1-hop subgraph around the query\n\n5. **Read layer context** — Grep for `\"layers\"` to understand which architectural layers the matched nodes belong to.\n\n6. **Answer the query** using only the relevant subgraph:\n   - Reference specific files, functions, and relationships from the graph\n   - Explain which layer(s) are relevant and why\n   - Be concise but thorough — link concepts to actual code locations\n   - If the query doesn't match any nodes, say so and suggest related terms from the graph\n",{"name":5,"description":7,"argument-hint":24},[25],"query","main","87afe6ce96220accf50a345dea46784c8c9f210e","YYC3-AI-应用工具\u002FYYC3-AI-应用工具-Understand-Anything\u002Funderstand-anything-plugin\u002Fskills\u002Funderstand-chat",0,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base","https:\u002F\u002Fkb.yyc3.top\u002F","https:\u002F\u002Fgithub.com\u002FYYC-Cube","万象归元于云枢 | 深栈智启新纪元","2026-11-10 10:37:32",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill understand-chat",{"tool":41,"command":42},"bunx","bunx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill understand-chat",{"tool":44,"command":45},"pnpm","pnpm dlx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill understand-chat","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-AI-应用工具\u002FYYC3-AI-应用工具-Understand-Anything\u002Funderstand-anything-plugin\u002Fskills\u002Funderstand-chat\u002FSKILL.md",true,[],[50,57,64,71,78,85],{"skillNo":51,"name":52,"nameZh":6,"description":53,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":54,"categories":55,"keywords":56,"publishedAt":19},"01M7CTDWHERCXPQCP0K03A86AS","vercel-sandbox","Run agent-browser + Chrome inside Vercel Sandbox microVMs for browser automation from any Vercel-deployed app. Use when the user needs browser automation in a Vercel app (Next.js, SvelteKit, Nuxt, Remix, Astro, etc.), wants to run headless Chrome without binary size limits, needs persistent browser sessions across commands, or wants ephemeral isolated browser environments. Triggers include \"Vercel Sandbox browser\", \"microVM Chrome\", \"agent-browser in sandbox\", \"browser automation on Vercel\", or any task requiring Chrome in a Vercel Sandbox.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fvercel-sandbox\u002FSKILL.md",[],[],{"skillNo":58,"name":59,"nameZh":6,"description":60,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":61,"categories":62,"keywords":63,"publishedAt":19},"01M7CTD8D2BNJY54S65M47HEJA","slack","Interact with Slack workspaces using browser automation. Use when the user needs to check unread channels, navigate Slack, send messages, extract data, find information, search conversations, or automate any Slack task. Triggers include \"check my Slack\", \"what channels have unreads\", \"send a message to\", \"search Slack for\", \"extract from Slack\", \"find who said\", or any task requiring programmatic Slack interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fslack\u002FSKILL.md",[],[],{"skillNo":65,"name":66,"nameZh":6,"description":67,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":70,"publishedAt":19},"01M7CTCSSB8ZP3Q58C3YZDZK1W","electron","Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include \"automate Slack app\", \"control VS Code\", \"interact with Discord app\", \"test this Electron app\", \"connect to desktop app\", or any task requiring automation of a native Electron application.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Felectron\u002FSKILL.md",[],[],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":77,"publishedAt":19},"01M7CTCBJY76688V4DCZGWFHGQ","dogfood","Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to \"dogfood\", \"QA\", \"exploratory test\", \"find issues\", \"bug hunt\", \"test this app\u002Fsite\u002Fplatform\", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fdogfood\u002FSKILL.md",[],[],{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":84,"publishedAt":19},"01M7CTC4H0FFGVEAQR9PA4GA1A","agent-browser","Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to \"open a website\", \"fill out a form\", \"click a button\", \"take a screenshot\", \"scrape data from a page\", \"test this web app\", \"login to a site\", \"automate browser actions\", or any task requiring programmatic web interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fagent-browser\u002FSKILL.md",[],[],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":91,"publishedAt":19},"01M7CTBKVFYBG78FDSABSDJTTQ","shadcn","Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn\u002Fui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for \"shadcn init\", \"create an app with --preset\", \"switch to --preset\", and for building a design system or applying a DESIGN.md or brand spec to shadcn\u002Fui.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-UI-界面组件\u002FYYC3-UI-界面组件-ui\u002Fskills\u002Fshadcn\u002FSKILL.md",[],[]]