[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7BZVSW15YVT88ASZ3PDQTRF":3,"skill-same:01M7BZVSW15YVT88ASZ3PDQTRF":83},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":29,"commitSha":30,"skillDirectory":31,"forksCount":14,"repositoryHtmlUrl":32,"repositoryHomepageUrl":6,"ownerHtmlUrl":33,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":34,"install":35,"resources":48},"01M7BZVSW15YVT88ASZ3PDQTRF","x-twitter-growth",null,"X\u002FTwitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X\u002FTwitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.","azhri1990\u002Fproject-genesis","azhri1990","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F281207543?v=4","01M7BMC0WHXB2ZA9SH1PFJDYNS","Nashriq Mokhtar","01M7BMC0XAE6SV0VTKWP3EMFGZ",0,"MIT","https:\u002F\u002Fgithub.com\u002Fazhri1990\u002Fproject-genesis\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fmarketing-skill\u002Fskills\u002Fx-twitter-growth\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: \"x-twitter-growth\"\ndescription: \"X\u002FTwitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X\u002FTwitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.\"\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: Alireza Rezvani\n  category: marketing\n  updated: 2026-03-10\n---\n\n# X\u002FTwitter Growth Engine\n\nX-specific growth skill. For general social media content across platforms, see `social-content`. For social strategy and calendar planning, see `social-media-manager`. This skill goes deep on X.\n\n## When to Use This vs Other Skills\n\n| Need | Use |\n|------|-----|\n| Write a tweet or thread | **This skill** |\n| Plan content across LinkedIn + X + Instagram | social-content |\n| Analyze engagement metrics across platforms | social-media-analyzer |\n| Build overall social strategy | social-media-manager |\n| X-specific growth, algorithm, competitive intel | **This skill** |\n\n---\n\n## Step 1 — Profile Audit\n\nBefore any growth work, audit the current X presence. Run `scripts\u002Fprofile_auditor.py` with the handle, or manually assess:\n\n### Bio Checklist\n- [ ] Clear value proposition in first line (who you help + how)\n- [ ] Specific niche — not \"entrepreneur | thinker | builder\"\n- [ ] Social proof element (followers, title, metric, brand)\n- [ ] CTA or link (newsletter, product, site)\n- [ ] No hashtags in bio (signals amateur)\n\n### Pinned Tweet\n- [ ] Exists and is less than 30 days old\n- [ ] Showcases best work or strongest hook\n- [ ] Has clear CTA (follow, subscribe, read)\n\n### Recent Activity (last 30 posts)\n- [ ] Posting frequency: minimum 1x\u002Fday, ideal 3-5x\u002Fday\n- [ ] Mix of formats: tweets, threads, replies, quotes\n- [ ] Reply ratio: >30% of activity should be replies\n- [ ] Engagement trend: improving, flat, or declining\n\nRun: `python3 scripts\u002Fprofile_auditor.py --handle @username`\n\n---\n\n## Step 2 — Competitive Intelligence\n\nResearch competitors and successful accounts in your niche using web search.\n\n### Process\n1. Search `site:x.com \"topic\" min_faves:100` via Brave to find high-performing content\n2. Identify 5-10 accounts in your niche with strong engagement\n3. For each, analyze: posting frequency, content types, hook patterns, engagement rates\n4. Run: `python3 scripts\u002Fcompetitor_analyzer.py --handles @acc1 @acc2 @acc3`\n\n### What to Extract\n- **Hook patterns** — How do top posts start? Question? Bold claim? Statistic?\n- **Content themes** — What 3-5 topics get the most engagement?\n- **Format mix** — Ratio of tweets vs threads vs replies vs quotes\n- **Posting times** — When do their best posts go out?\n- **Engagement triggers** — What makes people reply vs like vs retweet?\n\n---\n\n## Step 3 — Content Creation\n\n### Tweet Types (ordered by growth impact)\n\n#### 1. Threads (highest reach, highest follow conversion)\n```\nStructure:\n- Tweet 1: Hook — must stop the scroll in \u003C7 words\n- Tweet 2: Context or promise (\"Here's what I learned:\")\n- Tweets 3-N: One idea per tweet, each standalone-worthy\n- Final tweet: Summary + explicit CTA (\"Follow @handle for more\")\n- Reply to tweet 1: Restate hook + \"Follow for more [topic]\"\n\nRules:\n- 5-12 tweets optimal (under 5 feels thin, over 12 loses people)\n- Each tweet should make sense if read alone\n- Use line breaks for readability\n- No tweet should be a wall of text (3-4 lines max)\n- Number the tweets or use \"↓\" in tweet 1\n```\n\n#### 2. Atomic Tweets (breadth, impression farming)\n```\nFormats that work:\n- Observation: \"[Thing] is underrated. Here's why:\"\n- Listicle: \"10 tools I use daily:\\n\\n1. X — for Y\"\n- Contrarian: \"Unpopular opinion: [statement]\"\n- Lesson: \"I [did X] for [time]. Biggest lesson:\"\n- Framework: \"[Concept] explained in 30 seconds:\"\n\nRules:\n- Under 200 characters gets more engagement\n- One idea per tweet\n- No links in tweet body (kills reach — put link in reply)\n- Question tweets drive replies (algorithm loves replies)\n```\n\n#### 3. Quote Tweets (authority building)\n```\nFormula: Original tweet + your unique take\n- Add data the original missed\n- Provide counterpoint or nuance\n- Share personal experience that validates\u002Fcontradicts\n- Never just say \"This\" or \"So true\"\n```\n\n#### 4. Replies (network growth, fastest path to visibility)\n```\nStrategy:\n- Reply to accounts 2-10x your size\n- Add genuine value, not \"great post!\"\n- Be first to reply on accounts with large audiences\n- Your reply IS your content — make it tweet-worthy\n- Controversial\u002Finsightful replies get quote-tweeted (free reach)\n```\n\nRun: `python3 scripts\u002Ftweet_composer.py --type thread --topic \"your topic\" --audience \"your audience\"`\n\n---\n\n## Step 4 — Algorithm Mechanics\n\n### What X rewards (2025-2026)\n| Signal | Weight | Action |\n|--------|--------|--------|\n| Replies received | Very high | Write reply-worthy content (questions, debates) |\n| Time spent reading | High | Threads, longer tweets with line breaks |\n| Profile visits from tweet | High | Curiosity gaps, tease expertise |\n| Bookmarks | High | Tactical, save-worthy content (lists, frameworks) |\n| Retweets\u002FQuotes | Medium | Shareable insights, bold takes |\n| Likes | Low-medium | Easy agreement, relatable content |\n| Link clicks | Low (penalized) | Never put links in tweet body — use reply |\n\n### What kills reach\n- Links in tweet body (put in first reply instead)\n- Editing tweets within 30 min of posting\n- Posting and immediately going offline (no early engagement)\n- More than 2 hashtags\n- Tagging people who don't engage back\n- Threads with inconsistent quality (one weak tweet tanks the whole thread)\n\n### Optimal Posting Cadence\n| Account size | Tweets\u002Fday | Threads\u002Fweek | Replies\u002Fday |\n|-------------|------------|--------------|-------------|\n| \u003C 1K followers | 2-3 | 1-2 | 10-20 |\n| 1K-10K | 3-5 | 2-3 | 5-15 |\n| 10K-50K | 3-7 | 2-4 | 5-10 |\n| 50K+ | 2-5 | 1-3 | 5-10 |\n\n---\n\n## Step 5 — Growth Playbook\n\n### Week 1-2: Foundation\n1. Optimize bio and pinned tweet (Step 1)\n2. Identify 20 accounts in your niche to engage with daily\n3. Reply 10-20 times per day to larger accounts (genuine value only)\n4. Post 2-3 atomic tweets per day testing different formats\n5. Publish 1 thread\n\n### Week 3-4: Pattern Recognition\n1. Review what formats got most engagement\n2. Double down on top 2 content formats\n3. Increase to 3-5 posts per day\n4. Publish 2-3 threads per week\n5. Start quote-tweeting relevant content daily\n\n### Month 2+: Scale\n1. Develop 3-5 recurring content series (e.g., \"Friday Framework\")\n2. Cross-pollinate: repurpose threads as LinkedIn posts, newsletter content\n3. Build reply relationships with 5-10 accounts your size (mutual engagement)\n4. Experiment with spaces\u002Faudio if relevant to niche\n5. Run: `python3 scripts\u002Fgrowth_tracker.py --handle @username --period 30d`\n\n---\n\n## Step 6 — Content Calendar Generation\n\nRun: `python3 scripts\u002Fcontent_planner.py --niche \"your niche\" --frequency 5 --weeks 2`\n\nGenerates a 2-week posting plan with:\n- Daily tweet topics with hook suggestions\n- Thread outlines (2-3 per week)\n- Reply targets (accounts to engage with)\n- Optimal posting times based on niche\n\n---\n\n## Scripts\n\n| Script | Purpose |\n|--------|---------|\n| `scripts\u002Fprofile_auditor.py` | Audit X profile: bio, pinned, activity patterns |\n| `scripts\u002Ftweet_composer.py` | Generate tweets\u002Fthreads with hook patterns |\n| `scripts\u002Fcompetitor_analyzer.py` | Analyze competitor accounts via web search |\n| `scripts\u002Fcontent_planner.py` | Generate weekly\u002Fmonthly content calendars |\n| `scripts\u002Fgrowth_tracker.py` | Track follower growth and engagement trends |\n\n## Common Pitfalls\n\n1. **Posting links directly** — Always put links in the first reply, never in the tweet body\n2. **Thread tweet 1 is weak** — If the hook doesn't stop scrolling, nothing else matters\n3. **Inconsistent posting** — Algorithm rewards daily consistency over occasional bangers\n4. **Only broadcasting** — Replies and engagement are 50%+ of growth, not just posting\n5. **Generic bio** — \"Helping people do things\" tells nobody anything\n6. **Copying formats without adapting** — What works for tech Twitter doesn't work for marketing Twitter\n\n## Related Skills\n\n- `social-content` — Multi-platform content creation\n- `social-media-manager` — Overall social strategy\n- `social-media-analyzer` — Cross-platform analytics\n- `content-production` — Long-form content that feeds X threads\n- `copywriting` — Headline and hook writing techniques\n","# X\u002FTwitter Growth Engine\n\nX-specific growth skill. For general social media content across platforms, see `social-content`. For social strategy and calendar planning, see `social-media-manager`. This skill goes deep on X.\n\n## When to Use This vs Other Skills\n\n| Need | Use |\n|------|-----|\n| Write a tweet or thread | **This skill** |\n| Plan content across LinkedIn + X + Instagram | social-content |\n| Analyze engagement metrics across platforms | social-media-analyzer |\n| Build overall social strategy | social-media-manager |\n| X-specific growth, algorithm, competitive intel | **This skill** |\n\n---\n\n## Step 1 — Profile Audit\n\nBefore any growth work, audit the current X presence. Run `scripts\u002Fprofile_auditor.py` with the handle, or manually assess:\n\n### Bio Checklist\n- [ ] Clear value proposition in first line (who you help + how)\n- [ ] Specific niche — not \"entrepreneur | thinker | builder\"\n- [ ] Social proof element (followers, title, metric, brand)\n- [ ] CTA or link (newsletter, product, site)\n- [ ] No hashtags in bio (signals amateur)\n\n### Pinned Tweet\n- [ ] Exists and is less than 30 days old\n- [ ] Showcases best work or strongest hook\n- [ ] Has clear CTA (follow, subscribe, read)\n\n### Recent Activity (last 30 posts)\n- [ ] Posting frequency: minimum 1x\u002Fday, ideal 3-5x\u002Fday\n- [ ] Mix of formats: tweets, threads, replies, quotes\n- [ ] Reply ratio: >30% of activity should be replies\n- [ ] Engagement trend: improving, flat, or declining\n\nRun: `python3 scripts\u002Fprofile_auditor.py --handle @username`\n\n---\n\n## Step 2 — Competitive Intelligence\n\nResearch competitors and successful accounts in your niche using web search.\n\n### Process\n1. Search `site:x.com \"topic\" min_faves:100` via Brave to find high-performing content\n2. Identify 5-10 accounts in your niche with strong engagement\n3. For each, analyze: posting frequency, content types, hook patterns, engagement rates\n4. Run: `python3 scripts\u002Fcompetitor_analyzer.py --handles @acc1 @acc2 @acc3`\n\n### What to Extract\n- **Hook patterns** — How do top posts start? Question? Bold claim? Statistic?\n- **Content themes** — What 3-5 topics get the most engagement?\n- **Format mix** — Ratio of tweets vs threads vs replies vs quotes\n- **Posting times** — When do their best posts go out?\n- **Engagement triggers** — What makes people reply vs like vs retweet?\n\n---\n\n## Step 3 — Content Creation\n\n### Tweet Types (ordered by growth impact)\n\n#### 1. Threads (highest reach, highest follow conversion)\n```\nStructure:\n- Tweet 1: Hook — must stop the scroll in \u003C7 words\n- Tweet 2: Context or promise (\"Here's what I learned:\")\n- Tweets 3-N: One idea per tweet, each standalone-worthy\n- Final tweet: Summary + explicit CTA (\"Follow @handle for more\")\n- Reply to tweet 1: Restate hook + \"Follow for more [topic]\"\n\nRules:\n- 5-12 tweets optimal (under 5 feels thin, over 12 loses people)\n- Each tweet should make sense if read alone\n- Use line breaks for readability\n- No tweet should be a wall of text (3-4 lines max)\n- Number the tweets or use \"↓\" in tweet 1\n```\n\n#### 2. Atomic Tweets (breadth, impression farming)\n```\nFormats that work:\n- Observation: \"[Thing] is underrated. Here's why:\"\n- Listicle: \"10 tools I use daily:\\n\\n1. X — for Y\"\n- Contrarian: \"Unpopular opinion: [statement]\"\n- Lesson: \"I [did X] for [time]. Biggest lesson:\"\n- Framework: \"[Concept] explained in 30 seconds:\"\n\nRules:\n- Under 200 characters gets more engagement\n- One idea per tweet\n- No links in tweet body (kills reach — put link in reply)\n- Question tweets drive replies (algorithm loves replies)\n```\n\n#### 3. Quote Tweets (authority building)\n```\nFormula: Original tweet + your unique take\n- Add data the original missed\n- Provide counterpoint or nuance\n- Share personal experience that validates\u002Fcontradicts\n- Never just say \"This\" or \"So true\"\n```\n\n#### 4. Replies (network growth, fastest path to visibility)\n```\nStrategy:\n- Reply to accounts 2-10x your size\n- Add genuine value, not \"great post!\"\n- Be first to reply on accounts with large audiences\n- Your reply IS your content — make it tweet-worthy\n- Controversial\u002Finsightful replies get quote-tweeted (free reach)\n```\n\nRun: `python3 scripts\u002Ftweet_composer.py --type thread --topic \"your topic\" --audience \"your audience\"`\n\n---\n\n## Step 4 — Algorithm Mechanics\n\n### What X rewards (2025-2026)\n| Signal | Weight | Action |\n|--------|--------|--------|\n| Replies received | Very high | Write reply-worthy content (questions, debates) |\n| Time spent reading | High | Threads, longer tweets with line breaks |\n| Profile visits from tweet | High | Curiosity gaps, tease expertise |\n| Bookmarks | High | Tactical, save-worthy content (lists, frameworks) |\n| Retweets\u002FQuotes | Medium | Shareable insights, bold takes |\n| Likes | Low-medium | Easy agreement, relatable content |\n| Link clicks | Low (penalized) | Never put links in tweet body — use reply |\n\n### What kills reach\n- Links in tweet body (put in first reply instead)\n- Editing tweets within 30 min of posting\n- Posting and immediately going offline (no early engagement)\n- More than 2 hashtags\n- Tagging people who don't engage back\n- Threads with inconsistent quality (one weak tweet tanks the whole thread)\n\n### Optimal Posting Cadence\n| Account size | Tweets\u002Fday | Threads\u002Fweek | Replies\u002Fday |\n|-------------|------------|--------------|-------------|\n| \u003C 1K followers | 2-3 | 1-2 | 10-20 |\n| 1K-10K | 3-5 | 2-3 | 5-15 |\n| 10K-50K | 3-7 | 2-4 | 5-10 |\n| 50K+ | 2-5 | 1-3 | 5-10 |\n\n---\n\n## Step 5 — Growth Playbook\n\n### Week 1-2: Foundation\n1. Optimize bio and pinned tweet (Step 1)\n2. Identify 20 accounts in your niche to engage with daily\n3. Reply 10-20 times per day to larger accounts (genuine value only)\n4. Post 2-3 atomic tweets per day testing different formats\n5. Publish 1 thread\n\n### Week 3-4: Pattern Recognition\n1. Review what formats got most engagement\n2. Double down on top 2 content formats\n3. Increase to 3-5 posts per day\n4. Publish 2-3 threads per week\n5. Start quote-tweeting relevant content daily\n\n### Month 2+: Scale\n1. Develop 3-5 recurring content series (e.g., \"Friday Framework\")\n2. Cross-pollinate: repurpose threads as LinkedIn posts, newsletter content\n3. Build reply relationships with 5-10 accounts your size (mutual engagement)\n4. Experiment with spaces\u002Faudio if relevant to niche\n5. Run: `python3 scripts\u002Fgrowth_tracker.py --handle @username --period 30d`\n\n---\n\n## Step 6 — Content Calendar Generation\n\nRun: `python3 scripts\u002Fcontent_planner.py --niche \"your niche\" --frequency 5 --weeks 2`\n\nGenerates a 2-week posting plan with:\n- Daily tweet topics with hook suggestions\n- Thread outlines (2-3 per week)\n- Reply targets (accounts to engage with)\n- Optimal posting times based on niche\n\n---\n\n## Scripts\n\n| Script | Purpose |\n|--------|---------|\n| `scripts\u002Fprofile_auditor.py` | Audit X profile: bio, pinned, activity patterns |\n| `scripts\u002Ftweet_composer.py` | Generate tweets\u002Fthreads with hook patterns |\n| `scripts\u002Fcompetitor_analyzer.py` | Analyze competitor accounts via web search |\n| `scripts\u002Fcontent_planner.py` | Generate weekly\u002Fmonthly content calendars |\n| `scripts\u002Fgrowth_tracker.py` | Track follower growth and engagement trends |\n\n## Common Pitfalls\n\n1. **Posting links directly** — Always put links in the first reply, never in the tweet body\n2. **Thread tweet 1 is weak** — If the hook doesn't stop scrolling, nothing else matters\n3. **Inconsistent posting** — Algorithm rewards daily consistency over occasional bangers\n4. **Only broadcasting** — Replies and engagement are 50%+ of growth, not just posting\n5. **Generic bio** — \"Helping people do things\" tells nobody anything\n6. **Copying formats without adapting** — What works for tech Twitter doesn't work for marketing Twitter\n\n## Related Skills\n\n- `social-content` — Multi-platform content creation\n- `social-media-manager` — Overall social strategy\n- `social-media-analyzer` — Cross-platform analytics\n- `content-production` — Long-form content that feeds X threads\n- `copywriting` — Headline and hook writing techniques\n",{"name":5,"license":15,"metadata":24,"description":7},{"author":25,"updated":26,"version":27,"category":28},"Alireza 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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\u002Fazhri1990\u002Fproject-genesis\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fsyllabus\u002Fskills\u002Fsyllabus\u002FSKILL.md",[],[],{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":19},"01M7C0EA12FWRZTMG0N23HV68M","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\u002Fazhri1990\u002Fproject-genesis\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpulse\u002Fskills\u002Fpulse\u002FSKILL.md",[],[],{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":104,"publishedAt":19},"01M7C0DXEHJKMKTB4N6B7MS4BT","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\u002Fazhri1990\u002Fproject-genesis\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fpatent\u002Fskills\u002Fpatent\u002FSKILL.md",[],[],{"skillNo":106,"name":107,"nameZh":6,"description":108,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":111,"publishedAt":19},"01M7C0DJM5ECEKZXTQA9G6YHQZ","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\u002Fazhri1990\u002Fproject-genesis\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fnotebooklm\u002Fskills\u002Fnotebooklm\u002FSKILL.md",[],[],{"skillNo":113,"name":114,"nameZh":6,"description":115,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":116,"categories":117,"keywords":118,"publishedAt":19},"01M7C0D304Z7YX7J25R42N6W2T","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\u002Fazhri1990\u002Fproject-genesis\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Flitreview\u002Fskills\u002Flitreview\u002FSKILL.md",[],[],{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":123,"categories":124,"keywords":125,"publishedAt":19},"01M7C0CP1419VDF6SGCDY6ZRZV","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\u002Fazhri1990\u002Fproject-genesis\u002Fblob\u002Fmain\u002Fclaude-skills\u002Fresearch\u002Fgrants\u002Fskills\u002Fgrants\u002FSKILL.md",[],[]]