[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7EHKPW39MGDZHA95BKXK5NJ":3,"skill-same:01M7EHKPW39MGDZHA95BKXK5NJ":56},{"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":14,"repositoryHtmlUrl":29,"repositoryHomepageUrl":6,"ownerHtmlUrl":30,"ownerBlogUrl":6,"ownerDescription":31,"updatedAt":32,"install":33,"resources":45},"01M7EHKPW39MGDZHA95BKXK5NJ","how",null,"Use for \"how does X work\", code walkthroughs before changing something, and placement \u002F ownership \u002F layering questions (\"where should this live\", \"which package owns this\", \"is this the right layer\"). Explains subsystem architecture, runtime flow, onboarding mental models. Use why for motivation.","renefatuaki\u002Fskills","renefatuaki","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F43519979?v=4","01M7EHD24GFMFZRH3Z04WSYC9A","René","01M7EHD25408DH8QKN61CSDXX4",0,"MIT","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Fhow\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: how\ndescription: \"Use for \\\"how does X work\\\", code walkthroughs before changing something, and placement \u002F ownership \u002F layering questions (\\\"where should this live\\\", \\\"which package owns this\\\", \\\"is this the right layer\\\"). Explains subsystem architecture, runtime flow, onboarding mental models. Use why for motivation.\"\ndisable-model-invocation: true\nargument-hint: \"[question]\"\n---\n\n# How\n\nExplore the codebase to answer \"how does X work?\" questions. Produce architectural explanations at the level of a senior engineer onboarding onto a subsystem, enough to build a working mental model, not so much that it reads like annotated source code.\n\nEvery spawn is a subagent with `subagent_type: \"general-purpose\"`. Read-only: the prompt says not to edit, write, or commit anything. Explorers use the `how explorer` line in `~\u002F.claude\u002Frules\u002Fmodels.md` (default `sonnet\u002Fhigh`), and every explainer uses the `how explainer` line (default `opus\u002Fxhigh`). Set `model` and `effort` from that line's value per `${CLAUDE_PLUGIN_ROOT}\u002Fskills\u002Fworkflow\u002Fengineering\u002Freferences\u002Fmodel-roles.md`, or from the default if the rule or the line is missing.\n\n## 1. Assess complexity\n\nIf the scope is ambiguous, state your interpretation and explore. The user can redirect.\n\n- **Simple** (a single module, a small utility, a narrow question such as \"how does function X work\"): no explorers. Spawn one explainer that explores and explains in one pass, built from `references\u002Fexplainer-prompt.md` without the explorer-findings section. Go to step 4.\n- **Complex** (a subsystem spanning multiple files or services, a cross-cutting feature, a full architectural overview): go to step 2.\n\nWhen in doubt, take the simple path.\n\n## 2. Explore (complex only)\n\nDecompose the question into 2 to 4 angles, each a distinct slice of the subsystem. Spawn all explorers in a single message, each with `references\u002Fexplorer-prompt.md` and its angle filled in.\n\n## 3. Synthesize (complex only)\n\nOnce all explorers have returned, spawn one explainer with `references\u002Fexplainer-prompt.md` and every explorer's findings filled in.\n\n## 4. Present\n\nPresent the explainer's output. Light edits for clarity or context from the conversation are fine. Do not substantially rewrite it.\n\n## Output format\n\nThe explanation uses the sections defined in `references\u002Fexplainer-prompt.md`, dropping any that do not apply: Overview, Key Concepts, How It Works, Where Things Live, Gotchas.\n","# How\n\nExplore the codebase to answer \"how does X work?\" questions. Produce architectural explanations at the level of a senior engineer onboarding onto a subsystem, enough to build a working mental model, not so much that it reads like annotated source code.\n\nEvery spawn is a subagent with `subagent_type: \"general-purpose\"`. Read-only: the prompt says not to edit, write, or commit anything. Explorers use the `how explorer` line in `~\u002F.claude\u002Frules\u002Fmodels.md` (default `sonnet\u002Fhigh`), and every explainer uses the `how explainer` line (default `opus\u002Fxhigh`). Set `model` and `effort` from that line's value per `${CLAUDE_PLUGIN_ROOT}\u002Fskills\u002Fworkflow\u002Fengineering\u002Freferences\u002Fmodel-roles.md`, or from the default if the rule or the line is missing.\n\n## 1. Assess complexity\n\nIf the scope is ambiguous, state your interpretation and explore. The user can redirect.\n\n- **Simple** (a single module, a small utility, a narrow question such as \"how does function X work\"): no explorers. Spawn one explainer that explores and explains in one pass, built from `references\u002Fexplainer-prompt.md` without the explorer-findings section. Go to step 4.\n- **Complex** (a subsystem spanning multiple files or services, a cross-cutting feature, a full architectural overview): go to step 2.\n\nWhen in doubt, take the simple path.\n\n## 2. Explore (complex only)\n\nDecompose the question into 2 to 4 angles, each a distinct slice of the subsystem. Spawn all explorers in a single message, each with `references\u002Fexplorer-prompt.md` and its angle filled in.\n\n## 3. Synthesize (complex only)\n\nOnce all explorers have returned, spawn one explainer with `references\u002Fexplainer-prompt.md` and every explorer's findings filled in.\n\n## 4. Present\n\nPresent the explainer's output. Light edits for clarity or context from the conversation are fine. Do not substantially rewrite it.\n\n## Output format\n\nThe explanation uses the sections defined in `references\u002Fexplainer-prompt.md`, dropping any that do not apply: Overview, Key Concepts, How It Works, Where Things Live, Gotchas.\n",{"name":5,"description":7,"argument-hint":24,"disable-model-invocation":25},"[question]",true,"main","95608c3222b36a55dba667cf51a92a2efdf5e65c","skills\u002Fworkflow\u002Fhow","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills","https:\u002F\u002Fgithub.com\u002Frenefatuaki","Senior Software Engineer","2026-11-11 02:18:10",{"source":8,"skillName":5,"commands":34,"prompt":44,"zipAvailable":25},[35,38,41],{"tool":36,"command":37},"npx","npx skills add renefatuaki\u002Fskills --skill how",{"tool":39,"command":40},"bunx","bunx skills add renefatuaki\u002Fskills --skill how",{"tool":42,"command":43},"pnpm","pnpm dlx skills add renefatuaki\u002Fskills --skill how","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Fhow\u002FSKILL.md",[46,52],{"path":47,"resourceType":48,"resourceTypeDesc":49,"sizeBytes":50,"sourceHtmlUrl":51},"references\u002Fexplainer-prompt.md","REFERENCE","参考文档",3085,"https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Fhow\u002Freferences\u002Fexplainer-prompt.md",{"path":53,"resourceType":48,"resourceTypeDesc":49,"sizeBytes":54,"sourceHtmlUrl":55},"references\u002Fexplorer-prompt.md",1135,"https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Fhow\u002Freferences\u002Fexplorer-prompt.md",[57,64,71,78,85,92],{"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},"01M7EHM6WHPXSSEDBK04TSGYW3","why","Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Fwhy\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},"01M7EHM3Z7JM36BCPJAQBVAMJ1","tdd","Use only when the user explicitly asks for TDD, a failing test, or a regression test, OR when the bug has an obvious cheap local test target. Skip when the test path is unclear, expensive, integration-heavy, or not requested.","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Ftdd\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},"01M7EHM0WJND99F23YC24X0PXS","swarm","Fan out N parallel workers, drain them, and return one report. Use for \u002Fswarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Fswarm\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},"01M7EHKXJPJHD57W7S0V2FYAAM","show-me-your-work","Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for \u002Fshow-me-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Fshow-me-your-work\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},"01M7EHKSX411XWSR4GYZ9VKP42","interrogate","Use for \"interrogate\", \"adversarial review\", \"multi-model review\", \"challenge this\", \"stress test this code\", \"find blind spots\", or \"tear this apart\". Multiple LLM reviewers challenge changes from independent angles.","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Finterrogate\u002FSKILL.md",[],[],{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":19},"01M7EHKM1V0FKQEMQ4ZEZEC4G3","figure-it-out","Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions. Use for \u002Ffigure-it-out or 'figure it out'.","https:\u002F\u002Fgithub.com\u002Frenefatuaki\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fworkflow\u002Ffigure-it-out\u002FSKILL.md",[],[]]