[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C13M8SJS9TAPAMMSJF7PPF":3,"skill-same:01M6C13M8SJS9TAPAMMSJF7PPF":124},{"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":27,"publishedAt":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":64,"commitSha":65,"skillDirectory":66,"forksCount":13,"repositoryHtmlUrl":67,"repositoryHomepageUrl":6,"ownerHtmlUrl":68,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":69,"install":70,"resources":83},"01M6C13M8SJS9TAPAMMSJF7PPF","interview",null,"Phase 1 of building a Claude Managed Agent — interview the founder about the one job the agent should do, then produce a build sheet (CMA primitives table + v1\u002Fv2 deferrals + eval plan) WITHOUT needing their API key yet. Use when the user says \"help me scope an agent\", \"I have an idea for an agent\", \"what should this agent be\", or when the orchestrator routes phase=interview. Drives the six intake slots (job, trigger, inputs, actions, definition-of-done, recurrence) via AskUserQuestion, maps them to primitives with interview_planner.py, assembles build-sheet.json with build_sheet_builder.py, and validates limits with primitives_validator.py. Connectors are mockable in v0 (schema-true custom tools); real MCP servers become v1 deferrals. Distinct from stage-launch (which turns the sheet into payloads).","mne20114-hash\u002Fgest35bi","mne20114-hash","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F224168109?v=4","01M6C0JCR7334CZ39YWTZXX2NG","01M6C0JCWN0NBWMQTW1CPG2Z4G",0,"MIT","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fagent-launcher\u002Fskills\u002Finterview\u002FSKILL.md",[17,22],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000038","人力资源","PROFESSION","适用职业",[5,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"actions","eval-plan","orchestrator","cma","cursor","eval","planner","plan","api","MCP","produce","intake","help","code","connectors","codex","antigravity","gemini","cli","2026-11-10 10:12:30",false,"---\nname: interview\ndescription: Phase 1 of building a Claude Managed Agent — interview the founder about the one job the agent should do, then produce a build sheet (CMA primitives table + v1\u002Fv2 deferrals + eval plan) WITHOUT needing their API key yet. Use when the user says \"help me scope an agent\", \"I have an idea for an agent\", \"what should this agent be\", or when the orchestrator routes phase=interview. Drives the six intake slots (job, trigger, inputs, actions, definition-of-done, recurrence) via AskUserQuestion, maps them to primitives with interview_planner.py, assembles build-sheet.json with build_sheet_builder.py, and validates limits with primitives_validator.py. Connectors are mockable in v0 (schema-true custom tools); real MCP servers become v1 deferrals. Distinct from stage-launch (which turns the sheet into payloads).\nversion: 2.11.2\nauthor: Alireza Rezvani\nlicense: MIT\ntags: [cma, interview, scoping, build-sheet, primitives, deferrals, eval-plan]\ncompatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]\n---\n\n# Phase 1 — Interview → Plan\n\nOpen warmly with one or two examples from\n[`..\u002F..\u002Freferences\u002Fexamples-bank.md`](..\u002F..\u002Freferences\u002Fexamples-bank.md), then interview\nthe founder into a **build sheet**. No API key needed in this phase — the output\nis a plan.\n\n## The six intake slots (ask one at a time; use AskUserQuestion for choices)\n\n| Slot | Question | Maps to |\n|---|---|---|\n| **Job** | \"What one job should this agent do end-to-end?\" | `agent.system` + outcome `description` |\n| **Trigger** | \"What kicks it off — you ask it, an event, or a schedule?\" | on-demand \u002F event \u002F cron |\n| **Inputs** | \"What does it read?\" (files, repo, memory, gmail\u002Fslack\u002Fgithub, web) | resources \u002F MCP servers \u002F memory |\n| **Actions** | \"What does it do?\" (draft, write, call APIs, run code) | agent toolset \u002F custom tools \u002F MCP |\n| **Done** | \"How would you grade a good run?\" | outcome `rubric` (required) |\n| **Recurrence** | \"Once, on request, or on a cadence?\" | single-pass \u002F grade-loop \u002F cron-loop |\n\nSee [`..\u002F..\u002Freferences\u002Finterview-to-config.md`](..\u002F..\u002Freferences\u002Finterview-to-config.md)\nfor the full mapping.\n\n## Workflow\n\n1. **Interview.** Walk the six slots. Capture the founder's own words — never\n   invent specifics they didn't claim.\n2. **Map to primitives.**\n   ```bash\n   python3 scripts\u002Finterview_planner.py \\\n     --job \"Triage overnight support email\" --trigger schedule \\\n     --inputs \"gmail,memory\" --actions \"label,reply\" \\\n     --dod \"one label per email, grounded reason, no invented facts\" \\\n     --recurrence daily --out .\u002Fmy-agent\u002Fplan.json\n   ```\n   MCP inputs become **schema-true mock custom tools** in v0 and a **v1 deferral**\n   to wire the real server. Irreversible actions (send\u002Fpublish) become **v2\n   deferrals** behind `always_ask`.\n3. **Assemble the sheet.**\n   ```bash\n   python3 scripts\u002Fbuild_sheet_builder.py --plan .\u002Fmy-agent\u002Fplan.json --out-dir .\u002Fmy-agent\n   ```\n4. **Validate limits.**\n   ```bash\n   python3 scripts\u002Fprimitives_validator.py --sheet .\u002Fmy-agent\u002Fbuild-sheet.json\n   ```\n   FAIL blocks progress; fix and re-run. WARN is advisory (surface it).\n5. **Record the plan in the goal.** `goal_state.py set --phase stage-launch\n   --artifact build_sheet=.\u002Fmy-agent\u002Fbuild-sheet.json`, then advance.\n\n## Hard rules\n\n- **v0 is the core job only.** Everything else is a versioned deferral with a\n  reason and an exact mechanism.\n- **Their problem, their words.**\n- **No key yet.** The interview produces a plan; the key is a Phase-2 concern.\n\n## Forcing-question library (recommend + cite)\n\n1. \"What one job — singular?\" *Recommend:* the most-repeated task. *Cite:*\n   interview-to-config.md. Two jobs → two agents.\n2. \"Real integration or v0 mock?\" *Recommend:* mock; wire MCP as v1. *Cite:*\n   interview-to-config.md rule 1.\n3. \"How do you grade it?\" *Recommend:* 3–5 grounded rubric lines. *Cite:*\n   cma-primitives.md (rubric required).\n4. \"Smarter over time?\" *Recommend:* attach memory only if yes. *Cite:*\n   cma-primitives.md (memory limits + injection).\n5. \"Once, or on a cadence?\" *Recommend:* on-demand v0, schedule as Phase-4.\n   *Cite:* loops-and-workflows.md.\n\n## Tools\n\n- `scripts\u002Finterview_planner.py` — answers → primitives skeleton + deferrals.\n- `scripts\u002Fbuild_sheet_builder.py` — assemble\u002Fnormalize build-sheet.json.\n- `scripts\u002Fprimitives_validator.py` — validate vs CMA limits (PASS\u002FWARN\u002FFAIL).\n","# Phase 1 — Interview → Plan\n\nOpen warmly with one or two examples from\n[`..\u002F..\u002Freferences\u002Fexamples-bank.md`](..\u002F..\u002Freferences\u002Fexamples-bank.md), then interview\nthe founder into a **build sheet**. No API key needed in this phase — the output\nis a plan.\n\n## The six intake slots (ask one at a time; use AskUserQuestion for choices)\n\n| Slot | Question | Maps to |\n|---|---|---|\n| **Job** | \"What one job should this agent do end-to-end?\" | `agent.system` + outcome `description` |\n| **Trigger** | \"What kicks it off — you ask it, an event, or a schedule?\" | on-demand \u002F event \u002F cron |\n| **Inputs** | \"What does it read?\" (files, repo, memory, gmail\u002Fslack\u002Fgithub, web) | resources \u002F MCP servers \u002F memory |\n| **Actions** | \"What does it do?\" (draft, write, call APIs, run code) | agent toolset \u002F custom tools \u002F MCP |\n| **Done** | \"How would you grade a good run?\" | outcome `rubric` (required) |\n| **Recurrence** | \"Once, on request, or on a cadence?\" | single-pass \u002F grade-loop \u002F cron-loop |\n\nSee [`..\u002F..\u002Freferences\u002Finterview-to-config.md`](..\u002F..\u002Freferences\u002Finterview-to-config.md)\nfor the full mapping.\n\n## Workflow\n\n1. **Interview.** Walk the six slots. Capture the founder's own words — never\n   invent specifics they didn't claim.\n2. **Map to primitives.**\n   ```bash\n   python3 scripts\u002Finterview_planner.py \\\n     --job \"Triage overnight support email\" --trigger schedule \\\n     --inputs \"gmail,memory\" --actions \"label,reply\" \\\n     --dod \"one label per email, grounded reason, no invented facts\" \\\n     --recurrence daily --out .\u002Fmy-agent\u002Fplan.json\n   ```\n   MCP inputs become **schema-true mock custom tools** in v0 and a **v1 deferral**\n   to wire the real server. Irreversible actions (send\u002Fpublish) become **v2\n   deferrals** behind `always_ask`.\n3. **Assemble the sheet.**\n   ```bash\n   python3 scripts\u002Fbuild_sheet_builder.py --plan .\u002Fmy-agent\u002Fplan.json --out-dir .\u002Fmy-agent\n   ```\n4. **Validate limits.**\n   ```bash\n   python3 scripts\u002Fprimitives_validator.py --sheet .\u002Fmy-agent\u002Fbuild-sheet.json\n   ```\n   FAIL blocks progress; fix and re-run. WARN is advisory (surface it).\n5. **Record the plan in the goal.** `goal_state.py set --phase stage-launch\n   --artifact build_sheet=.\u002Fmy-agent\u002Fbuild-sheet.json`, then advance.\n\n## Hard rules\n\n- **v0 is the core job only.** Everything else is a versioned deferral with a\n  reason and an exact mechanism.\n- **Their problem, their words.**\n- **No key yet.** The interview produces a plan; the key is a Phase-2 concern.\n\n## Forcing-question library (recommend + cite)\n\n1. \"What one job — singular?\" *Recommend:* the most-repeated task. *Cite:*\n   interview-to-config.md. Two jobs → two agents.\n2. \"Real integration or v0 mock?\" *Recommend:* mock; wire MCP as v1. *Cite:*\n   interview-to-config.md rule 1.\n3. \"How do you grade it?\" *Recommend:* 3–5 grounded rubric lines. *Cite:*\n   cma-primitives.md (rubric required).\n4. \"Smarter over time?\" *Recommend:* attach memory only if yes. *Cite:*\n   cma-primitives.md (memory limits + injection).\n5. \"Once, or on a cadence?\" *Recommend:* on-demand v0, schedule as Phase-4.\n   *Cite:* loops-and-workflows.md.\n\n## Tools\n\n- `scripts\u002Finterview_planner.py` — answers → primitives skeleton + deferrals.\n- `scripts\u002Fbuild_sheet_builder.py` — assemble\u002Fnormalize build-sheet.json.\n- `scripts\u002Fprimitives_validator.py` — validate vs CMA limits (PASS\u002FWARN\u002FFAIL).\n",{"name":5,"tags":52,"author":57,"license":14,"version":58,"description":7,"compatible_tools":59},[31,5,53,54,55,56,29],"scoping","build-sheet","primitives","deferrals","Alireza Rezvani","2.11.2",[60,61,32,44,62,63],"claude-code","codex-cli","opencode","gemini-cli","main","510dd2917e051cc953dc55f56fd6ef442aa01b38","claude-skills\u002Fagent-launcher\u002Fskills\u002Finterview","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi","https:\u002F\u002Fgithub.com\u002Fmne20114-hash","2026-10-28 07:50:31",{"source":8,"skillName":5,"commands":71,"prompt":81,"zipAvailable":82},[72,75,78],{"tool":73,"command":74},"npx","npx skills add mne20114-hash\u002Fgest35bi --skill interview",{"tool":76,"command":77},"bunx","bunx skills add mne20114-hash\u002Fgest35bi --skill interview",{"tool":79,"command":80},"pnpm","pnpm dlx skills add mne20114-hash\u002Fgest35bi --skill interview","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fagent-launcher\u002Fskills\u002Finterview\u002FSKILL.md",true,[84,90,94,98,102,106,110,116,120],{"path":85,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":88,"sourceHtmlUrl":89},"README.md","REFERENCE","参考文档",1107,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fagent-launcher\u002Fskills\u002Finterview\u002FREADME.md",{"path":91,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fcontent-filter-implementation.md",4478,"https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fklingai-pack\u002Fskills\u002Fklingai-content-policy\u002Freferences\u002Fcontent-filter-implementation.md",{"path":95,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":96,"sourceHtmlUrl":97},"references\u002Fcontent-moderation-service.md",5249,"https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fklingai-pack\u002Fskills\u002Fklingai-content-policy\u002Freferences\u002Fcontent-moderation-service.md",{"path":99,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":100,"sourceHtmlUrl":101},"references\u002Ferrors.md",192,"https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fklingai-pack\u002Fskills\u002Fklingai-content-policy\u002Freferences\u002Ferrors.md",{"path":103,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":104,"sourceHtmlUrl":105},"references\u002Fexamples.md",75,"https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fklingai-pack\u002Fskills\u002Fklingai-content-policy\u002Freferences\u002Fexamples.md",{"path":107,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":108,"sourceHtmlUrl":109},"references\u002Fpolicy-violation-logger.md",2049,"https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Fklingai-pack\u002Fskills\u002Fklingai-content-policy\u002Freferences\u002Fpolicy-violation-logger.md",{"path":111,"resourceType":112,"resourceTypeDesc":113,"sizeBytes":114,"sourceHtmlUrl":115},"scripts\u002Fbuild_sheet_builder.py","SCRIPT","脚本",3700,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fagent-launcher\u002Fskills\u002Finterview\u002Fscripts\u002Fbuild_sheet_builder.py",{"path":117,"resourceType":112,"resourceTypeDesc":113,"sizeBytes":118,"sourceHtmlUrl":119},"scripts\u002Finterview_planner.py",8382,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fagent-launcher\u002Fskills\u002Finterview\u002Fscripts\u002Finterview_planner.py",{"path":121,"resourceType":112,"resourceTypeDesc":113,"sizeBytes":122,"sourceHtmlUrl":123},"scripts\u002Fprimitives_validator.py",6791,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fagent-launcher\u002Fskills\u002Finterview\u002Fscripts\u002Fprimitives_validator.py",[125,157,179,202,227,245],{"skillNo":126,"name":127,"nameZh":6,"description":128,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":129,"categories":130,"keywords":138,"publishedAt":47},"01M6C27N3H0F9RGG2KASPASH04","syllabus","Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fsyllabus\u002Fskills\u002Fsyllabus\u002FSKILL.md",[131,134,135],{"categoryNo":132,"categoryName":133,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000002","文档处理",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":136,"categoryName":137,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000034","行政与办公人员",[127,139,140,141,39,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156],"docx","pr","create","search","audit","integrity","checkpoint","learning","js","format","direct","Rules","find","consensus","list","extract","use","outcomes",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":167,"publishedAt":47},"01M6C27DMGZ4D6ERNHSVA8H8RJ","pulse","Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X\u002FTwitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend\u002Fsentiment\u002Fproblems\u002Fopportunities\u002Fcomparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpulse\u002Fskills\u002Fpulse\u002FSKILL.md",[163,166],{"categoryNo":164,"categoryName":165,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[159,168,169,140,170,39,143,171,172,144,173,174,175,176,149,150,177,151,178,155],"research","web","sentiment analysis","sentiment","Citations","analysis","discovery","open","tool","twitter","user",{"skillNo":180,"name":181,"nameZh":6,"description":182,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":183,"categories":184,"keywords":190,"publishedAt":47},"01M6C279M59X635VPD6Y9R616J","patent","Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search \u002F freedom-to-operate \u002F competitive landscape \u002F acquisition diligence \u002F litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",[185,186,187],{"categoryNo":132,"categoryName":133,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":188,"categoryName":189,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000037","律师与法务",[181,139,140,191,192,193,39,142,143,173,194,195,196,150,197,198,199,200,155,201],"competitive landscape","routing","product","commits","Word","text","acquisition","decisions","strategy","coverage","advice",{"skillNo":203,"name":204,"nameZh":6,"description":205,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":206,"categories":207,"keywords":212,"publishedAt":47},"01M6C275RZWNRB3CCB14QQM7ES","notebooklm","Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio\u002FVideo Overviews, Mind Maps, Reports incl. Briefing Doc\u002FStudy Guide\u002FFAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fnotebooklm\u002Fskills\u002Fnotebooklm\u002FSKILL.md",[208,211],{"categoryNo":209,"categoryName":210,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[204,213,214,168,215,216,217,218,219,220,221,222,175,196,149,223,224,225,226,155],"google","browser automation","automation","generate","browser","fast","SET","doc","Video","Audio","check","ask","environment","overview",{"skillNo":228,"name":229,"nameZh":6,"description":230,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":231,"categories":232,"keywords":237,"publishedAt":47},"01M6C2717B0QDJ3Y4PJP77BMW5","litreview","Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER \u002F Decomposition \u002F hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5\u002F10\u002F20 queries) controls coverage vs. speed. Output is a 'launching pad' — an orientation guide that lets a researcher dive in confidently, not a finished review. Use when the user starts literature-oriented research (e.g., 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'). Do NOT use for single one-off paper searches wanting a quick list — that's a plain PubMed\u002FOpenAlex (or Consensus) query.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Flitreview\u002Fskills\u002Flitreview\u002FSKILL.md",[233,234,235,236],{"categoryNo":132,"categoryName":133,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":164,"categoryName":165,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":136,"categoryName":137,"taxonomyType":25,"taxonomyTypeDesc":26},[229,139,37,238,239,140,39,142,240,241,242,145,35,195,243,150,152,244,200,155],"writing","review","lane","keyless","literature review","researcher","question",{"skillNo":246,"name":247,"nameZh":6,"description":248,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":249,"categories":250,"keywords":255,"publishedAt":47},"01M6C26X5G3WDVWQ40Y16ZS19F","grants","NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance\u002FInnovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget\u002Fscope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fgrants\u002Fskills\u002Fgrants\u002FSKILL.md",[251,252,253,254],{"categoryNo":132,"categoryName":133,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":164,"categoryName":165,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":136,"categoryName":137,"taxonomyType":25,"taxonomyTypeDesc":26},[247,139,168,140,40,39,142,143,256,257,144,173,195,150,151,152,199,225,155,258],"data","Budget","innovation"]