[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C279M59X635VPD6Y9R616J":3,"skill-same:01M6C279M59X635VPD6Y9R616J":112},{"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":30,"publishedAt":50,"linkOnly":51,"markdownContent":52,"markdownBody":53,"frontMatter":54,"refName":60,"commitSha":61,"skillDirectory":62,"forksCount":13,"repositoryHtmlUrl":63,"repositoryHomepageUrl":6,"ownerHtmlUrl":64,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":65,"install":66,"resources":79},"01M6C279M59X635VPD6Y9R616J","patent",null,"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.","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\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",[17,22,25],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":26,"categoryName":27,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[5,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49],"Word","advice","use","coverage","strategy","decisions","acquisition","Rules","text","docx","commits","analysis","audit","search","intake","product","routing","competitive landscape","pr","2026-11-10 10:12:30",false,"---\nname: patent\ndescription: \"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.\"\nlicense: MIT\nmetadata:\n  source_spec: \"megaprompts\u002F11-patent-megaprompt.md\"\n  build_pattern: \"Path B (direct conversion)\"\n  research_pack_convention: \"Agent Integrity Rules verbatim per PR #657 audit; sub-use-case routing variant\"\n  version: 1.0.0\n---\n\n# Patent — Prior-Art + Landscape Intelligence\n\n> **Portability:** Requires `web_fetch` (Google Patents, Espacenet, USPTO), `WebSearch` (adjacent academic art), Node.js with `docx` package, and optionally Lens.org API key for citation-graph signals. Works in Claude Code CLI natively. In Claude.ai with web tools + Code Execution + BYOK Lens.org, the workflow is supported.\n\n> **Out of scope:** trademark, copyright, trade-secret. These are flagged at intake. Use a different skill or qualified counsel.\n\n> **Legal disclaimer:** This skill produces search signal, not legal advice. Verdicts are technical assessments. **Always consult a patent attorney before filing or licensing decisions.**\n\n## Non-Generic Framing — The Differentiator\n\nThis skill is **prior-art + landscape intelligence**. It **refuses to be a bucket**. Every invocation commits to one of five sub-use-cases via the grill-me intake before any search runs. The chosen sub-use-case dictates the entire search strategy, ranking heuristics, and DOCX emphasis.\n\n| Sub-use-case | Search strategy | DOCX emphasis |\n|---|---|---|\n| **Novelty search** | Narrow + claims-text focused; pre-filing date irrelevant | Closest art + claim-differentiation |\n| **Freedom-to-operate** | Broad + active patents only; jurisdiction-filtered | FTO flags + claim-by-claim risk |\n| **Competitive landscape** | Breadth + filer tally + CPC trends | Filer map + investment hotspots |\n| **Acquisition diligence** | Specific assignee + portfolio scope + assignment chain | Portfolio table + ownership verification |\n| **Litigation prior-art** | Specific target patent + adjacent art before priority date | Knock-out candidates ranked by relevance |\n\nSee [`references\u002Fsub_use_case_routing.md`](references\u002Fsub_use_case_routing.md) for the canon.\n\n## Agent Integrity Rules (Research-Pack Convention)\n\nLocked verbatim per PR #657 audit.\n\n- **Execution discipline.** Sequential search calls only. **1 query\u002Fsec rate limit.** Confirm response received before next call.\n- **Source discipline.** Cite only patents returned by THIS session's tool calls. Training knowledge labeled `[Not from search — reference information]` and excluded from counts.\n- **Three-count tracking.** Queries sent \u002F patents received (shown) \u002F patents cited. Surfaced in audit log.\n- **Retry policy.** On failure → wait 3s → retry once → log. After 3 consecutive failures across tools: stop, alert user, explain what's missing.\n- **Plan-tier detection.** Lens.org free tier = 1000 queries\u002Fmonth. Google Patents has no auth but rate-limits per IP. Detect and surface caps.\n\n## Phase 1: Grill-Me Intake (6 forcing questions, one at a time)\n\n### Q1 (root) — Invention description\n\n> **Describe the invention in 2–3 sentences. What does it do, and what's new about it?**\n>\n> *Why I'm asking:* Concept and keyword extraction depends entirely on a precise description. Vague descriptions (\"AI for healthcare\", \"a better widget\") will be rejected — push back and ask the user to specify what the invention does and what differentiates it from existing approaches.\n\n**Refuse mush.** If answer is generic, ask once more: \"What does it do that existing systems don't?\" Then commit (with caveat in DOCX).\n\n### Q2 (depends on Q1) — Sub-use-case commitment\n\n> **What's the purpose of this search? Pick one:**\n>\n> 1. Novelty search (am I novel enough to file)\n> 2. Freedom-to-operate (will I get sued if I ship)\n> 3. Competitive landscape (who else plays here)\n> 4. Acquisition diligence (does target really own X)\n> 5. Litigation prior-art hunting (kill a specific patent)\n>\n> *Why I'm asking:* Each path uses a fundamentally different search strategy. I'll **refuse to start without you picking one**.\n\nForcing format. If user says \"all of them\", push for the primary purpose — secondary purposes can run as follow-up searches.\n\n### Q3 (asked only if Q2 ∈ {FTO, landscape, diligence}) — Jurisdictions\n\n> **Which jurisdictions matter? Pick all that apply: US \u002F EP \u002F CN \u002F JP \u002F KR \u002F PCT \u002F worldwide.**\n>\n> *Why I'm asking:* FTO only matters where you'll sell. Landscape changes radically by region. Diligence requires checking all jurisdictions where the target operates.\n\nSkip for novelty (priority date is jurisdictionally portable) and litigation (jurisdiction is set by the target patent).\n\n### Q4 (depends on Q1) — Known prior art\n\n> **Have you already seen prior art close to this? Cite a patent number or paper.**\n>\n> *Why I'm asking:* If you know one piece of art, I can search adjacent to it — much more precise than starting cold. If you don't, that's fine — just confirm.\n\nAnchoring. Accept \"none\" but ask if the user has seen *any* related work even informally.\n\n### Q5 (depends on Q2) — Risk tolerance\n\n> **Risk tolerance for this search: strict (one close hit means abandon the path) or signal-gathering (you want the lay of the land regardless)?**\n>\n> *Why I'm asking:* Strict mode ranks aggressively and surfaces verdict-grade hits; signal mode prioritizes breadth and visualizations.\n\nAsked for novelty and FTO; skipped for pure landscape (always signal-gathering by definition).\n\n### Q6 (asked only if Q2 ∈ {novelty, FTO}) — Attorney status\n\n> **Have you spoken to a patent attorney? This skill produces search signal, not legal advice. Confirm you understand this is for technical assessment only.**\n>\n> *Why I'm asking:* Novelty and FTO have legal consequences. The skill's verdict is signal-grade; legal positions require qualified counsel.\n\n**Triggers the legal-disclaimer footer in the DOCX.** Skipped for landscape and diligence (lower legal exposure).\n\n**Stop condition:** After Q6 (or earlier if dependency skips applied), commit and start Phase 2. Never re-open intake after Phase 2 begins.\n\n## Phase 2: Search Strategy Selection\n\nDeterministic from intake answers. Use `scripts\u002Fsub_use_case_router.py`:\n\n```bash\npython scripts\u002Fsub_use_case_router.py \\\n  --sub-use-case novelty \\\n  --jurisdictions \"\" \\\n  --risk strict \\\n  --known-art \"US10000000B2\"\n```\n\nReturns: query plan (5-8 queries) + ranking heuristic + DOCX emphasis flags.\n\n## Phase 3: Multi-Source Search (Sequential)\n\n### Source priority\n\n1. **Google Patents** (https:\u002F\u002Fpatents.google.com) — workhorse, no auth required, broad coverage\n2. **Espacenet** (https:\u002F\u002Fworldwide.espacenet.com) — global coverage, good for non-US art\n3. **USPTO PPS** (https:\u002F\u002Fppubs.uspto.gov) — US deep dive\n4. **Lens.org** (https:\u002F\u002Fwww.lens.org) — citation graph, BYOK API key required\n\n### Per-sub-use-case query patterns\n\n**Novelty:**\n- 3 narrow queries on invention-specific terminology (Google Patents)\n- 2 broad concept queries with synonyms (Google Patents + Espacenet)\n- 1 CPC-class-restricted query if class identified from initial hits\n\n**FTO:**\n- Jurisdiction-filtered: only active patents (not expired, not abandoned)\n- Date filter: priority \u003C today\n- Active-claim text extraction for each hit\n\n**Competitive landscape:**\n- Broader queries on the technology space\n- CPC class identification → tally top filers in that class\n- 10-year filing trend by year per top-5 filer\n\n**Acquisition diligence:**\n- Specific assignee searches (target company + subsidiaries + named inventors)\n- Assignment chain check (USPTO assignment recordation)\n- Family resolution for deduplication\n\n**Litigation prior-art:**\n- Target patent input required (number)\n- Priority date extraction\n- Search for art before priority date in same CPC classes\n- Adjacent-claim-language search\n\n### Sequential discipline\n\n1 q\u002Fsec across ALL sources combined. Tracked via `scripts\u002Fcitation_tracker.py` with timestamp-enforced gap.\n\n## Phase 4: Claim Extraction + Relevance Scoring\n\nFor each closest-art hit:\n- Pull **independent claim 1** (the broadest claim — primary anticipation\u002Fobviousness vehicle)\n- Pull **key dependent claims** (claims that add the inventive step)\n- Score relevance against invention description (overlap of claim language with Q1 terminology)\n\nRank by score. Verdict per sub-use-case (NOVEL \u002F POTENTIALLY NOVEL \u002F NOT NOVEL for novelty; CLEAR \u002F FLAGGED \u002F HIGH RISK per jurisdiction for FTO).\n\n## Phase 5: Citation Graph + Family Resolution\n\n### Citation graph (Lens.org BYOK)\n\nIf user provides Lens.org API key:\n- Foundational-patent identification (cited-by count > threshold, typically 50+)\n- Recent high-cite signals (citations in last 24 months as proxy for current activity)\n- Forward citations from target patent (litigation prior-art) or from closest art (novelty)\n\nIf no Lens.org key: skip; note in audit log; recommend manual citation review on Google Patents.\n\n### Family resolution\n\nSame invention often filed in multiple jurisdictions (US + EP + JP + CN). Group by family ID or priority number to avoid double-counting. Use `scripts\u002Ffamily_resolver.py`:\n\n```bash\npython scripts\u002Ffamily_resolver.py --hits-file hits.json\n# Returns: deduplicated family list + family-member jurisdictions\n```\n\n## CPC\u002FIPC Classification Awareness\n\n**Critical:** keyword search alone misses adjacent art. After initial search, extract the CPC\u002FIPC classes from top 5 hits and run **one class-restricted query**. This consistently surfaces art that keyword search misses.\n\nSee [`references\u002Fcpc_classification_canon.md`](references\u002Fcpc_classification_canon.md) for the canon.\n\n## Phase 6: DOCX Generation (8 Sections)\n\nSub-use-case-dependent emphasis. Via Node.js + `docx` library.\n\n1. **Executive Summary + Verdict** — Sub-use-case banner + one-line verdict (NOVEL \u002F FLAGGED \u002F etc.) + 3-4 key findings + legal disclaimer footer\n2. **Closest Prior Art** — 5-10 patents in ranked order. Per hit: hyperlinked title + assignee + filing\u002Fpriority dates + independent claim 1 text (italicized) + relevance score + relevance rationale (1-2 sentences)\n3. **Patent Landscape** — Top filers table (top 10 by count) + 10-year filing trend description + CPC class distribution table. Only for landscape and diligence; abbreviated otherwise.\n4. **Citation Graph Signals** — Foundational patents (if Lens-enabled) + recent high-cite activity. If Lens unavailable, note \"manual review recommended\" and skip table.\n5. **Geographic Coverage** — Filings by jurisdiction for top 10 hits. Only for FTO, landscape, diligence; skipped for novelty and litigation.\n6. **FTO Flags** (FTO only) — Active patents posing infringement risk. Per flag: hyperlinked patent + jurisdiction + relevant claims + risk level (HIGH\u002FMEDIUM\u002FLOW) + mitigation note.\n7. **Strategy + Recommendations** — Sub-use-case-specific:\n   - Novelty → claim differentiation suggestions\n   - FTO → design-around hints + jurisdiction strategy\n   - Landscape → who-to-watch list\n   - Diligence → red flags in portfolio\n   - Litigation → ranked knock-out candidates\n   - **Mandatory disclaimer to consult patent attorney** for any filing\u002Flicensing decision.\n8. **Audit Log** — Searches table (#, query, source, results, status), counts (sent\u002Fshown\u002Fcited), tool constraints (plan-tier notes), failed steps, attorney-consultation reminder\n\n### Styling\n\nArial 12pt body, navy headings (#1a3a5c), light blue table headers (#e8f0f8), red FTO-flag callout. `ExternalHyperlink` patterns:\n- Google Patents: `https:\u002F\u002Fpatents.google.com\u002Fpatent\u002F[number]`\n- Espacenet: `https:\u002F\u002Fworldwide.espacenet.com\u002Fpatent\u002F...`\n- USPTO: `https:\u002F\u002Fpatents.uspto.gov\u002Fpatent\u002F...`\n\n## Date Discipline\n\nDistinguish at every hit:\n- **Filing date** — when the application was first submitted\n- **Priority date** — earliest claim of priority (often earlier than filing)\n- **Publication date** — when the application became public (typically 18 months after priority)\n- **Grant date** — when the patent was granted (later than publication)\n\nSurface the **legally-relevant date** per sub-use-case:\n- Novelty → priority date (vs invention's anticipated filing date)\n- FTO → grant date + status (active vs expired)\n- Landscape → publication date (when public knowledge began)\n- Diligence → grant date + assignment date\n- Litigation → priority date of target patent (sets the prior-art cutoff)\n\n## Phase 7: Deliver\n\n- Save: `\u003Coutput-dir>\u002Fpatent_\u003Cinvention-slug>_\u003Csub-use-case>_\u003CYYYY-MM-DD>.docx`\n- Chat summary: file path + sub-use-case + verdict + audit counts + plan-tier\n- Validate: check zip integrity with `python3 -c \"import zipfile,sys; zipfile.ZipFile(sys.argv[1]).testzip()\" \u003Cdocx>` (no output = intact), then confirm the required sections are present\n- Reminder: \"Consult patent attorney before filing\u002Flicensing\"\n\n## Tooling\n\n| Script | Role |\n|---|---|\n| `scripts\u002Fcitation_tracker.py` | Multi-source three-count audit (Google Patents + Espacenet + USPTO + Lens.org) at `~\u002F.patent_sessions\u002F\u003Csession>.json` |\n| `scripts\u002Ffamily_resolver.py` | Group same-invention filings across jurisdictions by family ID \u002F priority number |\n| `scripts\u002Fsub_use_case_router.py` | Deterministic search-strategy selection from intake answers |\n\n## References\n\n- [`references\u002Fsub_use_case_routing.md`](references\u002Fsub_use_case_routing.md) — 5-sub-use-case canon (7+ sources)\n- [`references\u002Fcpc_classification_canon.md`](references\u002Fcpc_classification_canon.md) — CPC\u002FIPC class follow-up rationale (7+ sources)\n- [`references\u002Flegal_disclaimer_discipline.md`](references\u002Flegal_disclaimer_discipline.md) — when + why disclaimer mandatory (7+ sources)\n\n## Error Handling\n\n| Failure | Behavior |\n|---|---|\n| User refuses to commit to sub-use-case | Refuse to proceed. Re-ask Q2 with examples. |\n| Invention description is generic | Reject answer. Re-ask Q1 with \"what does it do that existing systems don't?\" |\n| Google Patents rate-limits | Wait 3s, retry once. Fall back to Espacenet for that query. Log in audit. |\n| Lens.org key missing | Skip citation graph section, note \"manual review recommended\" in DOCX. |\n| Claim text extraction fails | Fall back to abstract; flag as \"abstract-only\" in relevance rationale. |\n| Family resolution incomplete | Note in audit; same-invention duplicates may appear; suggest manual deduplication. |\n| All searches return \u003C3 hits | Surface explicitly as \"either niche art or genuine gap\"; never fabricate. |\n| 3 consecutive tool failures | Stop, alert user, explain what's missing. |\n| DOCX generation fails | Save raw data as JSON fallback so user doesn't lose work. |\n| Target patent number invalid (litigation) | Validate format before search; ask user to confirm. |\n\n## Anti-Patterns To Reject\n\n- Starting any search before user commits to a sub-use-case (refuses generic \"patent help\")\n- Batching all intake questions instead of one at a time\n- Accepting vague invention descriptions (\"AI for healthcare\")\n- Keyword-only search without CPC\u002FIPC class follow-up\n- Treating family members as separate hits (must be deduplicated)\n- Confusing filing date with priority date with publication date\n- Skipping the legal disclaimer when sub-use-case has legal consequences\n- Reporting a verdict without claim-text evidence\n- Fabricating Lens.org citation data when key is absent\n- Suggesting design-arounds without acknowledging attorney review is required\n- Skipping the audit log\n\n---\n\n**Version:** 1.0.0\n**Source spec:** `megaprompts\u002F11-patent-megaprompt.md` (maintainer-local draft spec — gitignored, not present in the public repository)\n**Build pattern:** Path B (direct conversion). Research-pack sibling, sub-use-case routing variant.\n","# Patent — Prior-Art + Landscape Intelligence\n\n> **Portability:** Requires `web_fetch` (Google Patents, Espacenet, USPTO), `WebSearch` (adjacent academic art), Node.js with `docx` package, and optionally Lens.org API key for citation-graph signals. Works in Claude Code CLI natively. In Claude.ai with web tools + Code Execution + BYOK Lens.org, the workflow is supported.\n\n> **Out of scope:** trademark, copyright, trade-secret. These are flagged at intake. Use a different skill or qualified counsel.\n\n> **Legal disclaimer:** This skill produces search signal, not legal advice. Verdicts are technical assessments. **Always consult a patent attorney before filing or licensing decisions.**\n\n## Non-Generic Framing — The Differentiator\n\nThis skill is **prior-art + landscape intelligence**. It **refuses to be a bucket**. Every invocation commits to one of five sub-use-cases via the grill-me intake before any search runs. The chosen sub-use-case dictates the entire search strategy, ranking heuristics, and DOCX emphasis.\n\n| Sub-use-case | Search strategy | DOCX emphasis |\n|---|---|---|\n| **Novelty search** | Narrow + claims-text focused; pre-filing date irrelevant | Closest art + claim-differentiation |\n| **Freedom-to-operate** | Broad + active patents only; jurisdiction-filtered | FTO flags + claim-by-claim risk |\n| **Competitive landscape** | Breadth + filer tally + CPC trends | Filer map + investment hotspots |\n| **Acquisition diligence** | Specific assignee + portfolio scope + assignment chain | Portfolio table + ownership verification |\n| **Litigation prior-art** | Specific target patent + adjacent art before priority date | Knock-out candidates ranked by relevance |\n\nSee [`references\u002Fsub_use_case_routing.md`](references\u002Fsub_use_case_routing.md) for the canon.\n\n## Agent Integrity Rules (Research-Pack Convention)\n\nLocked verbatim per PR #657 audit.\n\n- **Execution discipline.** Sequential search calls only. **1 query\u002Fsec rate limit.** Confirm response received before next call.\n- **Source discipline.** Cite only patents returned by THIS session's tool calls. Training knowledge labeled `[Not from search — reference information]` and excluded from counts.\n- **Three-count tracking.** Queries sent \u002F patents received (shown) \u002F patents cited. Surfaced in audit log.\n- **Retry policy.** On failure → wait 3s → retry once → log. After 3 consecutive failures across tools: stop, alert user, explain what's missing.\n- **Plan-tier detection.** Lens.org free tier = 1000 queries\u002Fmonth. Google Patents has no auth but rate-limits per IP. Detect and surface caps.\n\n## Phase 1: Grill-Me Intake (6 forcing questions, one at a time)\n\n### Q1 (root) — Invention description\n\n> **Describe the invention in 2–3 sentences. What does it do, and what's new about it?**\n>\n> *Why I'm asking:* Concept and keyword extraction depends entirely on a precise description. Vague descriptions (\"AI for healthcare\", \"a better widget\") will be rejected — push back and ask the user to specify what the invention does and what differentiates it from existing approaches.\n\n**Refuse mush.** If answer is generic, ask once more: \"What does it do that existing systems don't?\" Then commit (with caveat in DOCX).\n\n### Q2 (depends on Q1) — Sub-use-case commitment\n\n> **What's the purpose of this search? Pick one:**\n>\n> 1. Novelty search (am I novel enough to file)\n> 2. Freedom-to-operate (will I get sued if I ship)\n> 3. Competitive landscape (who else plays here)\n> 4. Acquisition diligence (does target really own X)\n> 5. Litigation prior-art hunting (kill a specific patent)\n>\n> *Why I'm asking:* Each path uses a fundamentally different search strategy. I'll **refuse to start without you picking one**.\n\nForcing format. If user says \"all of them\", push for the primary purpose — secondary purposes can run as follow-up searches.\n\n### Q3 (asked only if Q2 ∈ {FTO, landscape, diligence}) — Jurisdictions\n\n> **Which jurisdictions matter? Pick all that apply: US \u002F EP \u002F CN \u002F JP \u002F KR \u002F PCT \u002F worldwide.**\n>\n> *Why I'm asking:* FTO only matters where you'll sell. Landscape changes radically by region. Diligence requires checking all jurisdictions where the target operates.\n\nSkip for novelty (priority date is jurisdictionally portable) and litigation (jurisdiction is set by the target patent).\n\n### Q4 (depends on Q1) — Known prior art\n\n> **Have you already seen prior art close to this? Cite a patent number or paper.**\n>\n> *Why I'm asking:* If you know one piece of art, I can search adjacent to it — much more precise than starting cold. If you don't, that's fine — just confirm.\n\nAnchoring. Accept \"none\" but ask if the user has seen *any* related work even informally.\n\n### Q5 (depends on Q2) — Risk tolerance\n\n> **Risk tolerance for this search: strict (one close hit means abandon the path) or signal-gathering (you want the lay of the land regardless)?**\n>\n> *Why I'm asking:* Strict mode ranks aggressively and surfaces verdict-grade hits; signal mode prioritizes breadth and visualizations.\n\nAsked for novelty and FTO; skipped for pure landscape (always signal-gathering by definition).\n\n### Q6 (asked only if Q2 ∈ {novelty, FTO}) — Attorney status\n\n> **Have you spoken to a patent attorney? This skill produces search signal, not legal advice. Confirm you understand this is for technical assessment only.**\n>\n> *Why I'm asking:* Novelty and FTO have legal consequences. The skill's verdict is signal-grade; legal positions require qualified counsel.\n\n**Triggers the legal-disclaimer footer in the DOCX.** Skipped for landscape and diligence (lower legal exposure).\n\n**Stop condition:** After Q6 (or earlier if dependency skips applied), commit and start Phase 2. Never re-open intake after Phase 2 begins.\n\n## Phase 2: Search Strategy Selection\n\nDeterministic from intake answers. Use `scripts\u002Fsub_use_case_router.py`:\n\n```bash\npython scripts\u002Fsub_use_case_router.py \\\n  --sub-use-case novelty \\\n  --jurisdictions \"\" \\\n  --risk strict \\\n  --known-art \"US10000000B2\"\n```\n\nReturns: query plan (5-8 queries) + ranking heuristic + DOCX emphasis flags.\n\n## Phase 3: Multi-Source Search (Sequential)\n\n### Source priority\n\n1. **Google Patents** (https:\u002F\u002Fpatents.google.com) — workhorse, no auth required, broad coverage\n2. **Espacenet** (https:\u002F\u002Fworldwide.espacenet.com) — global coverage, good for non-US art\n3. **USPTO PPS** (https:\u002F\u002Fppubs.uspto.gov) — US deep dive\n4. **Lens.org** (https:\u002F\u002Fwww.lens.org) — citation graph, BYOK API key required\n\n### Per-sub-use-case query patterns\n\n**Novelty:**\n- 3 narrow queries on invention-specific terminology (Google Patents)\n- 2 broad concept queries with synonyms (Google Patents + Espacenet)\n- 1 CPC-class-restricted query if class identified from initial hits\n\n**FTO:**\n- Jurisdiction-filtered: only active patents (not expired, not abandoned)\n- Date filter: priority \u003C today\n- Active-claim text extraction for each hit\n\n**Competitive landscape:**\n- Broader queries on the technology space\n- CPC class identification → tally top filers in that class\n- 10-year filing trend by year per top-5 filer\n\n**Acquisition diligence:**\n- Specific assignee searches (target company + subsidiaries + named inventors)\n- Assignment chain check (USPTO assignment recordation)\n- Family resolution for deduplication\n\n**Litigation prior-art:**\n- Target patent input required (number)\n- Priority date extraction\n- Search for art before priority date in same CPC classes\n- Adjacent-claim-language search\n\n### Sequential discipline\n\n1 q\u002Fsec across ALL sources combined. Tracked via `scripts\u002Fcitation_tracker.py` with timestamp-enforced gap.\n\n## Phase 4: Claim Extraction + Relevance Scoring\n\nFor each closest-art hit:\n- Pull **independent claim 1** (the broadest claim — primary anticipation\u002Fobviousness vehicle)\n- Pull **key dependent claims** (claims that add the inventive step)\n- Score relevance against invention description (overlap of claim language with Q1 terminology)\n\nRank by score. Verdict per sub-use-case (NOVEL \u002F POTENTIALLY NOVEL \u002F NOT NOVEL for novelty; CLEAR \u002F FLAGGED \u002F HIGH RISK per jurisdiction for FTO).\n\n## Phase 5: Citation Graph + Family Resolution\n\n### Citation graph (Lens.org BYOK)\n\nIf user provides Lens.org API key:\n- Foundational-patent identification (cited-by count > threshold, typically 50+)\n- Recent high-cite signals (citations in last 24 months as proxy for current activity)\n- Forward citations from target patent (litigation prior-art) or from closest art (novelty)\n\nIf no Lens.org key: skip; note in audit log; recommend manual citation review on Google Patents.\n\n### Family resolution\n\nSame invention often filed in multiple jurisdictions (US + EP + JP + CN). Group by family ID or priority number to avoid double-counting. Use `scripts\u002Ffamily_resolver.py`:\n\n```bash\npython scripts\u002Ffamily_resolver.py --hits-file hits.json\n# Returns: deduplicated family list + family-member jurisdictions\n```\n\n## CPC\u002FIPC Classification Awareness\n\n**Critical:** keyword search alone misses adjacent art. After initial search, extract the CPC\u002FIPC classes from top 5 hits and run **one class-restricted query**. This consistently surfaces art that keyword search misses.\n\nSee [`references\u002Fcpc_classification_canon.md`](references\u002Fcpc_classification_canon.md) for the canon.\n\n## Phase 6: DOCX Generation (8 Sections)\n\nSub-use-case-dependent emphasis. Via Node.js + `docx` library.\n\n1. **Executive Summary + Verdict** — Sub-use-case banner + one-line verdict (NOVEL \u002F FLAGGED \u002F etc.) + 3-4 key findings + legal disclaimer footer\n2. **Closest Prior Art** — 5-10 patents in ranked order. Per hit: hyperlinked title + assignee + filing\u002Fpriority dates + independent claim 1 text (italicized) + relevance score + relevance rationale (1-2 sentences)\n3. **Patent Landscape** — Top filers table (top 10 by count) + 10-year filing trend description + CPC class distribution table. Only for landscape and diligence; abbreviated otherwise.\n4. **Citation Graph Signals** — Foundational patents (if Lens-enabled) + recent high-cite activity. If Lens unavailable, note \"manual review recommended\" and skip table.\n5. **Geographic Coverage** — Filings by jurisdiction for top 10 hits. Only for FTO, landscape, diligence; skipped for novelty and litigation.\n6. **FTO Flags** (FTO only) — Active patents posing infringement risk. Per flag: hyperlinked patent + jurisdiction + relevant claims + risk level (HIGH\u002FMEDIUM\u002FLOW) + mitigation note.\n7. **Strategy + Recommendations** — Sub-use-case-specific:\n   - Novelty → claim differentiation suggestions\n   - FTO → design-around hints + jurisdiction strategy\n   - Landscape → who-to-watch list\n   - Diligence → red flags in portfolio\n   - Litigation → ranked knock-out candidates\n   - **Mandatory disclaimer to consult patent attorney** for any filing\u002Flicensing decision.\n8. **Audit Log** — Searches table (#, query, source, results, status), counts (sent\u002Fshown\u002Fcited), tool constraints (plan-tier notes), failed steps, attorney-consultation reminder\n\n### Styling\n\nArial 12pt body, navy headings (#1a3a5c), light blue table headers (#e8f0f8), red FTO-flag callout. `ExternalHyperlink` patterns:\n- Google Patents: `https:\u002F\u002Fpatents.google.com\u002Fpatent\u002F[number]`\n- Espacenet: `https:\u002F\u002Fworldwide.espacenet.com\u002Fpatent\u002F...`\n- USPTO: `https:\u002F\u002Fpatents.uspto.gov\u002Fpatent\u002F...`\n\n## Date Discipline\n\nDistinguish at every hit:\n- **Filing date** — when the application was first submitted\n- **Priority date** — earliest claim of priority (often earlier than filing)\n- **Publication date** — when the application became public (typically 18 months after priority)\n- **Grant date** — when the patent was granted (later than publication)\n\nSurface the **legally-relevant date** per sub-use-case:\n- Novelty → priority date (vs invention's anticipated filing date)\n- FTO → grant date + status (active vs expired)\n- Landscape → publication date (when public knowledge began)\n- Diligence → grant date + assignment date\n- Litigation → priority date of target patent (sets the prior-art cutoff)\n\n## Phase 7: Deliver\n\n- Save: `\u003Coutput-dir>\u002Fpatent_\u003Cinvention-slug>_\u003Csub-use-case>_\u003CYYYY-MM-DD>.docx`\n- Chat summary: file path + sub-use-case + verdict + audit counts + plan-tier\n- Validate: check zip integrity with `python3 -c \"import zipfile,sys; zipfile.ZipFile(sys.argv[1]).testzip()\" \u003Cdocx>` (no output = intact), then confirm the required sections are present\n- Reminder: \"Consult patent attorney before filing\u002Flicensing\"\n\n## Tooling\n\n| Script | Role |\n|---|---|\n| `scripts\u002Fcitation_tracker.py` | Multi-source three-count audit (Google Patents + Espacenet + USPTO + Lens.org) at `~\u002F.patent_sessions\u002F\u003Csession>.json` |\n| `scripts\u002Ffamily_resolver.py` | Group same-invention filings across jurisdictions by family ID \u002F priority number |\n| `scripts\u002Fsub_use_case_router.py` | Deterministic search-strategy selection from intake answers |\n\n## References\n\n- [`references\u002Fsub_use_case_routing.md`](references\u002Fsub_use_case_routing.md) — 5-sub-use-case canon (7+ sources)\n- [`references\u002Fcpc_classification_canon.md`](references\u002Fcpc_classification_canon.md) — CPC\u002FIPC class follow-up rationale (7+ sources)\n- [`references\u002Flegal_disclaimer_discipline.md`](references\u002Flegal_disclaimer_discipline.md) — when + why disclaimer mandatory (7+ sources)\n\n## Error Handling\n\n| Failure | Behavior |\n|---|---|\n| User refuses to commit to sub-use-case | Refuse to proceed. Re-ask Q2 with examples. |\n| Invention description is generic | Reject answer. Re-ask Q1 with \"what does it do that existing systems don't?\" |\n| Google Patents rate-limits | Wait 3s, retry once. Fall back to Espacenet for that query. Log in audit. |\n| Lens.org key missing | Skip citation graph section, note \"manual review recommended\" in DOCX. |\n| Claim text extraction fails | Fall back to abstract; flag as \"abstract-only\" in relevance rationale. |\n| Family resolution incomplete | Note in audit; same-invention duplicates may appear; suggest manual deduplication. |\n| All searches return \u003C3 hits | Surface explicitly as \"either niche art or genuine gap\"; never fabricate. |\n| 3 consecutive tool failures | Stop, alert user, explain what's missing. |\n| DOCX generation fails | Save raw data as JSON fallback so user doesn't lose work. |\n| Target patent number invalid (litigation) | Validate format before search; ask user to confirm. |\n\n## Anti-Patterns To Reject\n\n- Starting any search before user commits to a sub-use-case (refuses generic \"patent help\")\n- Batching all intake questions instead of one at a time\n- Accepting vague invention descriptions (\"AI for healthcare\")\n- Keyword-only search without CPC\u002FIPC class follow-up\n- Treating family members as separate hits (must be deduplicated)\n- Confusing filing date with priority date with publication date\n- Skipping the legal disclaimer when sub-use-case has legal consequences\n- Reporting a verdict without claim-text evidence\n- Fabricating Lens.org citation data when key is absent\n- Suggesting design-arounds without acknowledging attorney review is required\n- Skipping the audit log\n\n---\n\n**Version:** 1.0.0\n**Source spec:** `megaprompts\u002F11-patent-megaprompt.md` (maintainer-local draft spec — gitignored, not present in the public repository)\n**Build pattern:** Path B (direct conversion). Research-pack sibling, sub-use-case routing variant.\n",{"name":5,"license":14,"metadata":55,"description":7},{"version":56,"source_spec":57,"build_pattern":58,"research_pack_convention":59},"1.0.0","megaprompts\u002F11-patent-megaprompt.md","Path B (direct conversion)","Agent Integrity Rules verbatim per PR #657 audit; sub-use-case routing variant","main","510dd2917e051cc953dc55f56fd6ef442aa01b38","claude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi","https:\u002F\u002Fgithub.com\u002Fmne20114-hash","2026-10-28 07:50:31",{"source":8,"skillName":5,"commands":67,"prompt":77,"zipAvailable":78},[68,71,74],{"tool":69,"command":70},"npx","npx skills add mne20114-hash\u002Fgest35bi --skill patent",{"tool":72,"command":73},"bunx","bunx skills add mne20114-hash\u002Fgest35bi --skill patent",{"tool":75,"command":76},"pnpm","pnpm dlx skills add mne20114-hash\u002Fgest35bi --skill patent","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",true,[80,86,90,94,100,104,108],{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fcpc_classification_canon.md","REFERENCE","参考文档",8666,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002Freferences\u002Fcpc_classification_canon.md",{"path":87,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Flegal_disclaimer_discipline.md",8022,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002Freferences\u002Flegal_disclaimer_discipline.md",{"path":91,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fsub_use_case_routing.md",11017,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002Freferences\u002Fsub_use_case_routing.md",{"path":95,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":98,"sourceHtmlUrl":99},"scripts\u002Fcitation_tracker.py","SCRIPT","脚本",9601,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002Fscripts\u002Fcitation_tracker.py",{"path":101,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":102,"sourceHtmlUrl":103},"scripts\u002Ffamily_resolver.py",9937,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002Fscripts\u002Ffamily_resolver.py",{"path":105,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":106,"sourceHtmlUrl":107},"scripts\u002Fsub_use_case_router.py",11405,"https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002Fscripts\u002Fsub_use_case_router.py",{"path":109,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":110,"sourceHtmlUrl":111},"skill.py",311,"https:\u002F\u002Fgithub.com\u002Fclovers-project\u002Fclovers-agent\u002Fblob\u002Fmaster\u002FAgentSkills\u002Fon-erotic\u002Fskill.py",[113,137,158,183,203,218],{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":124,"publishedAt":50},"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",[119,120,121],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":122,"categoryName":123,"taxonomyType":28,"taxonomyTypeDesc":29},"01JBSEEDCAT000000000000034","行政与办公人员",[115,40,49,125,45,44,43,126,127,128,129,130,131,38,132,133,134,135,33,136],"create","integrity","checkpoint","learning","js","format","direct","find","consensus","list","extract","outcomes",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":141,"categories":142,"keywords":147,"publishedAt":50},"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",[143,146],{"categoryNo":144,"categoryName":145,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},[139,148,149,49,150,45,43,151,152,126,42,153,154,155,131,38,156,132,157,33],"research","web","sentiment analysis","sentiment","Citations","discovery","open","tool","twitter","user",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":168,"publishedAt":50},"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",[164,167],{"categoryNo":165,"categoryName":166,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},[160,169,170,148,171,172,173,174,175,176,177,178,154,39,131,179,180,181,182,33],"google","browser automation","automation","generate","browser","fast","SET","doc","Video","Audio","check","ask","environment","overview",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":187,"categories":188,"keywords":193,"publishedAt":50},"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",[189,190,191,192],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":144,"categoryName":145,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":122,"categoryName":123,"taxonomyType":28,"taxonomyTypeDesc":29},[185,40,194,195,196,49,45,44,197,198,199,127,200,31,201,38,133,202,34,33],"MCP","writing","review","lane","keyless","literature review","plan","researcher","question",{"skillNo":204,"name":205,"nameZh":6,"description":206,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":207,"categories":208,"keywords":213,"publishedAt":50},"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",[209,210,211,212],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":144,"categoryName":145,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":122,"categoryName":123,"taxonomyType":28,"taxonomyTypeDesc":29},[205,40,148,49,214,45,44,43,215,216,126,42,31,38,132,133,35,181,33,217],"help","data","Budget","innovation",{"skillNo":219,"name":220,"nameZh":6,"description":221,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":222,"categories":223,"keywords":228,"publishedAt":50},"01M6C26SDXA3MT5XZEDVWZZDWR","dossier","Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica) as workhorses; optional BYOK MCPs enhance coverage. Use when the user asks for background research, diligence, or meeting prep on a specific entity (e.g., 'prep me for a meeting with [person\u002Fcompany]', 'due diligence on [company]'). Honors sensitivity exclusions for journalism + personal-vetting contexts.","https:\u002F\u002Fgithub.com\u002Fmne20114-hash\u002Fgest35bi\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fdossier\u002Fskills\u002Fdossier\u002FSKILL.md",[224,225,226,227],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":144,"categoryName":145,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":23,"categoryName":24,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":122,"categoryName":123,"taxonomyType":28,"taxonomyTypeDesc":29},[220,40,229,230,148,49,231,45,43,232,233,234,31,235,38,34,236,237,238,33],"testing","github","state","meeting prep","provenance","verify","decision","webfetch","reputation","byok"]