[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C14HT7M6WZ967TF2P33A2A":3,"skill-same:01M6C14HT7M6WZ967TF2P33A2A":79},{"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":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":59,"commitSha":60,"skillDirectory":61,"forksCount":13,"repositoryHtmlUrl":62,"repositoryHomepageUrl":6,"ownerHtmlUrl":63,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":64,"install":65,"resources":78},"01M6C14HT7M6WZ967TF2P33A2A","business-operations-skills",null,"Use when running, diagnosing, or designing internal business operations — process documentation, vendor SLAs, capacity planning, internal comms, SOP\u002Frunbook authoring, procurement spend. Triggers on \"BizOps review\", \"where's the bottleneck\", \"vendor health\", \"internal SOP\", \"all-hands deck\", \"spend categorization\", \"capacity for Q3\", \"process mapping\". Forks context to route to one of six BizOps sub-skills (process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizer) and returns a digest. Distinct from business-growth (external sales motion) and c-level-advisor (strategic, not operational).","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\u002Fbusiness-operations\u002Fskills\u002Fbusiness-operations-skills\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"business","business operations skills","runbook","bizops","growth","sales","planner","knowledge","health","procurement","internal comms","planning","code","documentation","capacity","codex","antigravity","gemini","cli","review","2026-11-10 10:12:30",false,"---\nname: business-operations-skills\ndescription: Use when running, diagnosing, or designing internal business operations — process documentation, vendor SLAs, capacity planning, internal comms, SOP\u002Frunbook authoring, procurement spend. Triggers on \"BizOps review\", \"where's the bottleneck\", \"vendor health\", \"internal SOP\", \"all-hands deck\", \"spend categorization\", \"capacity for Q3\", \"process mapping\". Forks context to route to one of six BizOps sub-skills (process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizer) and returns a digest. Distinct from business-growth (external sales motion) and c-level-advisor (strategic, not operational).\ncontext: fork\nversion: 2.8.0\nauthor: claude-code-skills\nlicense: MIT\ntags: [bizops, operations, process, vendor, capacity, sop, procurement, coo, orchestrator]\ncompatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]\n---\n\n# Business Operations — Domain Orchestrator\n\nThe BizOps surface is **internal**: how the company actually runs. This orchestrator forks its conversation context, routes your inquiry to one of six sub-skills, then returns a tight digest to the parent thread. The heavy ingestion (vendor catalogs, process interviews, multi-doc SOP intake) stays in the forked context.\n\n## When to invoke\n\n| Symptom | Sub-skill to route to |\n|---|---|\n| \"Where does the work spend most of its time waiting?\" | `process-mapper` |\n| \"Is this vendor delivering against the SLA?\" | `vendor-management` |\n| \"Do we have enough people to ship in Q3?\" | `capacity-planner` |\n| \"I need to brief the company on a re-org\" | `internal-comms` |\n| \"Write me a runbook for the incident response process\" | `knowledge-ops` |\n| \"Why is our software spend up 40% YoY?\" | `procurement-optimizer` |\n\n## Routing logic (deterministic)\n\nThe orchestrator classifies the inquiry by **signals** detected in the prompt. Two-signal threshold for confident routing; one-signal triggers a clarifying question.\n\n### Signal table\n\n| Signal class | Keywords | Sub-skill |\n|---|---|---|\n| **PROCESS** | bottleneck, cycle time, waiting, handoff, BPMN, process map, workflow | `process-mapper` |\n| **VENDOR** | vendor, supplier, SLA, contract, third-party, MSA, SaaS subscription, renewal | `vendor-management` |\n| **CAPACITY** | headcount, capacity, utilization, planning, hiring sequence, FTE | `capacity-planner` |\n| **COMMS** | all-hands, internal newsletter, announcement, change management, FAQ, town hall | `internal-comms` |\n| **KNOWLEDGE** | SOP, runbook, knowledge base, wiki, playbook, documentation, onboarding doc | `knowledge-ops` |\n| **PROCUREMENT** | spend, procurement, purchase, supplier rationalization, software audit, SaaS sprawl | `procurement-optimizer` |\n\nIf signals are mixed (e.g., \"vendor SLA + spend audit\"), run the **highest-confidence sub-skill first**, then chain into the second one in a follow-up forked turn.\n\n### Fallback\n\nIf no signal class scores ≥ 2, ask **one** clarifying question naming the two most likely candidates. Do NOT guess silently.\n\n## Workflow (Matt Pocock grill discipline)\n\nDerived from Matt Pocock's `grill-with-docs` pattern: **explore-then-ask, one question per turn with a recommended answer, walk the decision tree depth-first, track dependencies, anchor every challenge in the documented canon** (`references\u002F`).\n\n### Step 1 — Explore before asking\n\nBefore any clarifying question, check:\n- Does the user's working directory already contain a process map, vendor catalog, SOP, or org chart we can grep?\n- Does the inquiry already disambiguate the lane (e.g., \"vendor SLA review\" — that's `vendor-management`, no question needed)?\n- Is the lane unambiguous from filenames mentioned (`procurement-Q3.csv` → procurement)?\n\nIf the codebase resolves the lane, **route silently**. Don't ask.\n\n### Step 2 — If still ambiguous, ONE forcing question with a recommended answer\n\nMatt's rule: never bundle questions. Never default to \"what do you think?\". Always offer your recommendation.\n\nPattern:\n```\nQ1\u002F1: [precise question naming the two candidate lanes]\nRecommended: [Lane X, because \u003Cone-sentence rationale from the signal table>]\n\n(Confirm, or override?)\n```\n\nWait for the user's response. **Then** route. Never guess silently after a turn that asked a question.\n\n### Step 3 — Forking decision-tree walk (only if the inquiry crosses lanes)\n\nIf the user's inquiry legitimately crosses two lanes (e.g., \"vendor SLA + spend audit\" = VENDOR + PROCUREMENT), walk the tree **depth-first**:\n\n1. Resolve the higher-confidence lane first → run that sub-skill in forked context → return digest\n2. Ask: \"Should we now run [second lane]? My recommendation: yes, because [dependency reason].\"\n3. Only after explicit user confirmation, run the second sub-skill\n\nDo NOT chain silently. Each fork is an explicit user-confirmed step.\n\n### Step 4 — Invoke sub-skill in forked context\n\nEach sub-skill is invoked with the original prompt + a digest of any structured inputs (file paths, JSON inputs). The fork keeps heavy ingestion (vendor catalog, process transcripts, SOP source documents) out of the parent context.\n\n### Step 5 — Return digest with cited canon challenge\n\nWhen the sub-skill completes, return a **≤ 200-word digest** to the parent thread:\n\n- What was analyzed\n- Top 3 findings (each anchored in a reference doc citation — e.g., \"Goldratt's Theory of Constraints: optimize the bottleneck, not the non-constraint\")\n- Top 3 next actions (named owners if possible)\n- Path to the artifact(s) produced\n- **One grill challenge** for the user, cited: \"Your value-add ratio is 12%. Lean canon (Womack & Jones 1996) classifies \u003C15% as waste-heavy. What's blocking process redesign — political, technical, or budget?\"\n\nThe parent agent can then ask follow-ups (each triggering new forked invocations).\n\n## Forcing-question library (grill-with-docs pattern)\n\nWhen the user has provided enough context to enter a lane, the orchestrator may grill them on the **decisions inside that lane** before invoking the sub-skill. One question per turn, each with a recommended answer + canon citation. Examples:\n\n- **PROCESS lane**: \"Before mapping: do you have measured cycle times per stage, or only estimates? Recommended: insist on measured data for the top-3 longest stages. Anti-pattern (Goldratt 1984): map estimates, optimize the wrong constraint.\"\n- **VENDOR lane**: \"Before scoring: what's your tier-1 criticality threshold — by spend ($X\u002Fyear), or by operational dependency (revenue-blocking if vendor fails)? Recommended: operational dependency. Anti-pattern (Gartner TPRM): spend-only tiering misses critical low-spend vendors like the HVAC vendor in the Target breach.\"\n- **CAPACITY lane**: \"Before modeling: are you planning for utilization or throughput? Recommended: throughput (Little's Law). Anti-pattern (DORA): planning for utilization > 80% destroys throughput via queueing.\"\n\nNever run a sub-skill until the lane-defining decision is locked.\n\n## Assumptions\n\n1. The user is acting on behalf of an organization with ≥ 10 employees (smaller orgs don't need this surface).\n2. The user has access to the data the sub-skill needs (process docs, vendor list, spend export, etc.) — or accepts the skill's templated dummy data.\n3. The user wants **deterministic, repeatable analysis** over LLM-flavored prose. Every sub-skill ships stdlib-only Python tools.\n\n## Non-goals\n\n- Not a substitute for an ERP, vendor management platform (Vendr, Tropic), or capacity-planning SaaS (Float, Runn).\n- Does not store state across sessions — every invocation is self-contained.\n- Does not call external APIs from Python tools (stdlib only, by design).\n\n## Distinct from\n\n- **`business-growth\u002F*`** — that's the **external sales motion** (CSM, sales engineering, RevOps). BizOps is **internal**.\n- **`c-level-advisor\u002Fcoo-advisor`** — that's strategic COO judgment (\"should we restructure?\"). BizOps is tactical (\"here's the process map with bottlenecks\").\n- **`engineering\u002Fslo-architect`** — that's system reliability with SLO\u002FSLI\u002Ferror budgets. `process-mapper` is **business process** reliability, not system reliability.\n- **`engineering\u002Fllm-wiki`** — that's a **personal** PKM (Karpathy's pattern). `knowledge-ops` is **company-wide** SOP authoring.\n\n## Output artifacts\n\nEvery sub-skill produces at least one artifact (markdown, CSV, or JSON) saved to the user's working directory. The orchestrator surfaces the file path in the digest.\n\n## Anti-patterns (do not)\n\n- ❌ Run all 6 sub-skills \"to be thorough\" — pick one based on signal, return digest, let user chain\n- ❌ Auto-approve a vendor or process change — surface findings; the human decides\n- ❌ Edit production process docs without asking — write to a new file, propose the diff\n- ❌ Skip the digest step — parent context needs ≤ 200-word digest, not the full sub-skill output\n\n## References\n\n- See `c-level-advisor\u002Fcoo-advisor` for strategic COO framing\n- Path-B build pattern: `documentation\u002Fimplementation\u002Fbizops-commercial-expansion-plan.md`\n","# Business Operations — Domain Orchestrator\n\nThe BizOps surface is **internal**: how the company actually runs. This orchestrator forks its conversation context, routes your inquiry to one of six sub-skills, then returns a tight digest to the parent thread. The heavy ingestion (vendor catalogs, process interviews, multi-doc SOP intake) stays in the forked context.\n\n## When to invoke\n\n| Symptom | Sub-skill to route to |\n|---|---|\n| \"Where does the work spend most of its time waiting?\" | `process-mapper` |\n| \"Is this vendor delivering against the SLA?\" | `vendor-management` |\n| \"Do we have enough people to ship in Q3?\" | `capacity-planner` |\n| \"I need to brief the company on a re-org\" | `internal-comms` |\n| \"Write me a runbook for the incident response process\" | `knowledge-ops` |\n| \"Why is our software spend up 40% YoY?\" | `procurement-optimizer` |\n\n## Routing logic (deterministic)\n\nThe orchestrator classifies the inquiry by **signals** detected in the prompt. Two-signal threshold for confident routing; one-signal triggers a clarifying question.\n\n### Signal table\n\n| Signal class | Keywords | Sub-skill |\n|---|---|---|\n| **PROCESS** | bottleneck, cycle time, waiting, handoff, BPMN, process map, workflow | `process-mapper` |\n| **VENDOR** | vendor, supplier, SLA, contract, third-party, MSA, SaaS subscription, renewal | `vendor-management` |\n| **CAPACITY** | headcount, capacity, utilization, planning, hiring sequence, FTE | `capacity-planner` |\n| **COMMS** | all-hands, internal newsletter, announcement, change management, FAQ, town hall | `internal-comms` |\n| **KNOWLEDGE** | SOP, runbook, knowledge base, wiki, playbook, documentation, onboarding doc | `knowledge-ops` |\n| **PROCUREMENT** | spend, procurement, purchase, supplier rationalization, software audit, SaaS sprawl | `procurement-optimizer` |\n\nIf signals are mixed (e.g., \"vendor SLA + spend audit\"), run the **highest-confidence sub-skill first**, then chain into the second one in a follow-up forked turn.\n\n### Fallback\n\nIf no signal class scores ≥ 2, ask **one** clarifying question naming the two most likely candidates. Do NOT guess silently.\n\n## Workflow (Matt Pocock grill discipline)\n\nDerived from Matt Pocock's `grill-with-docs` pattern: **explore-then-ask, one question per turn with a recommended answer, walk the decision tree depth-first, track dependencies, anchor every challenge in the documented canon** (`references\u002F`).\n\n### Step 1 — Explore before asking\n\nBefore any clarifying question, check:\n- Does the user's working directory already contain a process map, vendor catalog, SOP, or org chart we can grep?\n- Does the inquiry already disambiguate the lane (e.g., \"vendor SLA review\" — that's `vendor-management`, no question needed)?\n- Is the lane unambiguous from filenames mentioned (`procurement-Q3.csv` → procurement)?\n\nIf the codebase resolves the lane, **route silently**. Don't ask.\n\n### Step 2 — If still ambiguous, ONE forcing question with a recommended answer\n\nMatt's rule: never bundle questions. Never default to \"what do you think?\". Always offer your recommendation.\n\nPattern:\n```\nQ1\u002F1: [precise question naming the two candidate lanes]\nRecommended: [Lane X, because \u003Cone-sentence rationale from the signal table>]\n\n(Confirm, or override?)\n```\n\nWait for the user's response. **Then** route. Never guess silently after a turn that asked a question.\n\n### Step 3 — Forking decision-tree walk (only if the inquiry crosses lanes)\n\nIf the user's inquiry legitimately crosses two lanes (e.g., \"vendor SLA + spend audit\" = VENDOR + PROCUREMENT), walk the tree **depth-first**:\n\n1. Resolve the higher-confidence lane first → run that sub-skill in forked context → return digest\n2. Ask: \"Should we now run [second lane]? My recommendation: yes, because [dependency reason].\"\n3. Only after explicit user confirmation, run the second sub-skill\n\nDo NOT chain silently. Each fork is an explicit user-confirmed step.\n\n### Step 4 — Invoke sub-skill in forked context\n\nEach sub-skill is invoked with the original prompt + a digest of any structured inputs (file paths, JSON inputs). The fork keeps heavy ingestion (vendor catalog, process transcripts, SOP source documents) out of the parent context.\n\n### Step 5 — Return digest with cited canon challenge\n\nWhen the sub-skill completes, return a **≤ 200-word digest** to the parent thread:\n\n- What was analyzed\n- Top 3 findings (each anchored in a reference doc citation — e.g., \"Goldratt's Theory of Constraints: optimize the bottleneck, not the non-constraint\")\n- Top 3 next actions (named owners if possible)\n- Path to the artifact(s) produced\n- **One grill challenge** for the user, cited: \"Your value-add ratio is 12%. Lean canon (Womack & Jones 1996) classifies \u003C15% as waste-heavy. What's blocking process redesign — political, technical, or budget?\"\n\nThe parent agent can then ask follow-ups (each triggering new forked invocations).\n\n## Forcing-question library (grill-with-docs pattern)\n\nWhen the user has provided enough context to enter a lane, the orchestrator may grill them on the **decisions inside that lane** before invoking the sub-skill. One question per turn, each with a recommended answer + canon citation. Examples:\n\n- **PROCESS lane**: \"Before mapping: do you have measured cycle times per stage, or only estimates? Recommended: insist on measured data for the top-3 longest stages. Anti-pattern (Goldratt 1984): map estimates, optimize the wrong constraint.\"\n- **VENDOR lane**: \"Before scoring: what's your tier-1 criticality threshold — by spend ($X\u002Fyear), or by operational dependency (revenue-blocking if vendor fails)? Recommended: operational dependency. Anti-pattern (Gartner TPRM): spend-only tiering misses critical low-spend vendors like the HVAC vendor in the Target breach.\"\n- **CAPACITY lane**: \"Before modeling: are you planning for utilization or throughput? Recommended: throughput (Little's Law). Anti-pattern (DORA): planning for utilization > 80% destroys throughput via queueing.\"\n\nNever run a sub-skill until the lane-defining decision is locked.\n\n## Assumptions\n\n1. The user is acting on behalf of an organization with ≥ 10 employees (smaller orgs don't need this surface).\n2. The user has access to the data the sub-skill needs (process docs, vendor list, spend export, etc.) — or accepts the skill's templated dummy data.\n3. The user wants **deterministic, repeatable analysis** over LLM-flavored prose. Every sub-skill ships stdlib-only Python tools.\n\n## Non-goals\n\n- Not a substitute for an ERP, vendor management platform (Vendr, Tropic), or capacity-planning SaaS (Float, Runn).\n- Does not store state across sessions — every invocation is self-contained.\n- Does not call external APIs from Python tools (stdlib only, by design).\n\n## Distinct from\n\n- **`business-growth\u002F*`** — that's the **external sales motion** (CSM, sales engineering, RevOps). BizOps is **internal**.\n- **`c-level-advisor\u002Fcoo-advisor`** — that's strategic COO judgment (\"should we restructure?\"). BizOps is tactical (\"here's the process map with bottlenecks\").\n- **`engineering\u002Fslo-architect`** — that's system reliability with SLO\u002FSLI\u002Ferror budgets. `process-mapper` is **business process** reliability, not system reliability.\n- **`engineering\u002Fllm-wiki`** — that's a **personal** PKM (Karpathy's pattern). `knowledge-ops` is **company-wide** SOP authoring.\n\n## Output artifacts\n\nEvery sub-skill produces at least one artifact (markdown, CSV, or JSON) saved to the user's working directory. The orchestrator surfaces the file path in the digest.\n\n## Anti-patterns (do not)\n\n- ❌ Run all 6 sub-skills \"to be thorough\" — pick one based on signal, return digest, let user chain\n- ❌ Auto-approve a vendor or process change — surface findings; the human decides\n- ❌ Edit production process docs without asking — write to a new file, propose the diff\n- ❌ Skip the digest step — parent context needs ≤ 200-word digest, not the full sub-skill output\n\n## References\n\n- See `c-level-advisor\u002Fcoo-advisor` for strategic COO framing\n- Path-B build pattern: `documentation\u002Fimplementation\u002Fbizops-commercial-expansion-plan.md`\n",{"name":5,"tags":43,"author":50,"context":51,"license":14,"version":52,"description":7,"compatible_tools":53},[21,44,45,46,32,47,27,48,49],"operations","process","vendor","sop","coo","orchestrator","claude-code-skills","fork","2.8.0",[54,55,56,34,57,58],"claude-code","codex-cli","cursor","opencode","gemini-cli","main","510dd2917e051cc953dc55f56fd6ef442aa01b38","claude-skills\u002Fbusiness-operations\u002Fskills\u002Fbusiness-operations-skills","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi","https:\u002F\u002Fgithub.com\u002Fmne20114-hash","2026-10-28 07:50:31",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add mne20114-hash\u002Fgest35bi --skill business-operations-skills",{"tool":71,"command":72},"bunx","bunx skills add mne20114-hash\u002Fgest35bi --skill business-operations-skills",{"tool":74,"command":75},"pnpm","pnpm dlx skills add mne20114-hash\u002Fgest35bi --skill business-operations-skills","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fbusiness-operations\u002Fskills\u002Fbusiness-operations-skills\u002FSKILL.md",true,[],[80,119,141,164,189,208],{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":84,"categories":85,"keywords":99,"publishedAt":38},"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",[86,91,94],{"categoryNo":87,"categoryName":88,"taxonomyType":89,"taxonomyTypeDesc":90},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",{"categoryNo":92,"categoryName":93,"taxonomyType":89,"taxonomyTypeDesc":90},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":95,"categoryName":96,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[82,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118],"docx","pr","create","intake","search","audit","integrity","checkpoint","learning","js","format","direct","Rules","find","consensus","list","extract","use","outcomes",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":123,"categories":124,"keywords":129,"publishedAt":38},"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",[125,128],{"categoryNo":126,"categoryName":127,"taxonomyType":89,"taxonomyTypeDesc":90},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":92,"categoryName":93,"taxonomyType":89,"taxonomyTypeDesc":90},[121,130,131,101,132,103,105,133,134,106,135,136,137,138,111,112,139,113,140,117],"research","web","sentiment analysis","sentiment","Citations","analysis","discovery","open","tool","twitter","user",{"skillNo":142,"name":143,"nameZh":6,"description":144,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":145,"categories":146,"keywords":152,"publishedAt":38},"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",[147,148,149],{"categoryNo":87,"categoryName":88,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":92,"categoryName":93,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":150,"categoryName":151,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000037","律师与法务",[143,100,101,153,154,155,103,104,105,135,156,157,158,112,159,160,161,162,117,163],"competitive landscape","routing","product","commits","Word","text","acquisition","decisions","strategy","coverage","advice",{"skillNo":165,"name":166,"nameZh":6,"description":167,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":168,"categories":169,"keywords":174,"publishedAt":38},"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",[170,173],{"categoryNo":171,"categoryName":172,"taxonomyType":89,"taxonomyTypeDesc":90},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":92,"categoryName":93,"taxonomyType":89,"taxonomyTypeDesc":90},[166,175,176,130,177,178,179,180,181,182,183,184,137,158,111,185,186,187,188,117],"google","browser automation","automation","generate","browser","fast","SET","doc","Video","Audio","check","ask","environment","overview",{"skillNo":190,"name":191,"nameZh":6,"description":192,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":193,"categories":194,"keywords":199,"publishedAt":38},"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",[195,196,197,198],{"categoryNo":87,"categoryName":88,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":126,"categoryName":127,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":92,"categoryName":93,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":95,"categoryName":96,"taxonomyType":97,"taxonomyTypeDesc":98},[191,100,200,201,37,101,103,104,202,203,204,107,205,157,206,112,114,207,162,117],"MCP","writing","lane","keyless","literature review","plan","researcher","question",{"skillNo":209,"name":210,"nameZh":6,"description":211,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":212,"categories":213,"keywords":218,"publishedAt":38},"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",[214,215,216,217],{"categoryNo":87,"categoryName":88,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":126,"categoryName":127,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":92,"categoryName":93,"taxonomyType":89,"taxonomyTypeDesc":90},{"categoryNo":95,"categoryName":96,"taxonomyType":97,"taxonomyTypeDesc":98},[210,100,130,101,219,103,104,105,220,221,106,135,157,112,113,114,161,187,117,222],"help","data","Budget","innovation"]