[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6EB3JXCJCJ2K7HM7AEV8GYS":3,"skill-same:01M6EB3JXCJCJ2K7HM7AEV8GYS":93},{"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":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M6EB3JXCJCJ2K7HM7AEV8GYS","board-meeting",null,"Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite contributions (isolated, no cross-pollination), critic analysis, synthesis, founder review, and decision extraction. Use when the user invokes \u002Fcs:board, calls a board meeting, or wants structured multi-perspective executive deliberation on a strategic question.","levalencia\u002Fagent-god-mode","levalencia","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6962857?v=4","01M6EB0FZZ4BPQPC4HET4QY6NM","Luis Valencia ","01M6EB0G4HWHPWW0H9X7QKSAHP",3,"MIT","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002F.gemini-board-meeting\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"board meeting","board","multi","review","founder","deliberation","structured","Synthesis","use","user","context","question","decisions","decision","multi-agent","critic","analysis","extraction","protocol","memory","2026-11-10 10:12:30",false,"---\nname: \"board-meeting\"\ndescription: \"Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite contributions (isolated, no cross-pollination), critic analysis, synthesis, founder review, and decision extraction. Use when the user invokes \u002Fcs:board, calls a board meeting, or wants structured multi-perspective executive deliberation on a strategic question.\"\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: Alireza Rezvani\n  category: c-level\n  domain: board-protocol\n  updated: 2026-03-05\n  frameworks: 6-phase-board, two-layer-memory, independent-contributions\n---\n\n# Board Meeting Protocol\n\nStructured multi-agent deliberation that prevents groupthink, captures minority views, and produces clean, actionable decisions.\n\n## Keywords\nboard meeting, executive deliberation, strategic decision, C-suite, multi-agent, \u002Fcs:board, founder review, decision extraction, independent perspectives\n\n## Invoke\n`\u002Fcs:board [topic]` — e.g. `\u002Fcs:board Should we expand to Spain in Q3?`\n\n---\n\n## The 6-Phase Protocol\n\n### PHASE 1: Context Gathering\n1. Load `memory\u002Fcompany-context.md`\n2. Load `memory\u002Fboard-meetings\u002Fdecisions.md` **(Layer 2 ONLY — never raw transcripts)**\n3. Reset session state — no bleed from previous conversations\n4. Present agenda + activated roles → wait for founder confirmation\n\n**Chief of Staff selects relevant roles** based on topic (not all 9 every time):\n| Topic | Activate |\n|-------|----------|\n| Market expansion | CEO, CMO, CFO, CRO, COO |\n| Product direction | CEO, CPO, CTO, CMO |\n| Hiring\u002Forg | CEO, CHRO, CFO, COO |\n| Pricing | CMO, CFO, CRO, CPO |\n| Technology | CTO, CPO, CFO, CISO |\n\n---\n\n### PHASE 2: Independent Contributions (ISOLATED)\n\n**No cross-pollination. Each agent runs before seeing others' outputs.**\n\nOrder: Research (if needed) → CMO → CFO → CEO → CTO → COO → CHRO → CRO → CISO → CPO\n\n**Reasoning techniques:** CEO: Tree of Thought (3 futures) | CFO: Chain of Thought (show the math) | CMO: Recursion of Thought (draft→critique→refine) | CPO: First Principles | CRO: Chain of Thought (pipeline math) | COO: Step by Step (process map) | CTO: ReAct (research→analyze→act) | CISO: Risk-Based (P×I) | CHRO: Empathy + Data\n\n**Contribution format (max 5 key points, self-verified):**\n```\n## [ROLE] — [DATE]\n\nKey points (max 5):\n• [Finding] — [VERIFIED\u002FASSUMED] — ?\u002F?\u002F?\n• [Finding] — [VERIFIED\u002FASSUMED] — ?\u002F?\u002F?\n\nRecommendation: [clear position]\nConfidence: High \u002F Medium \u002F Low\nSource: [where the data came from]\nWhat would change my mind: [specific condition]\n```\n\nEach agent self-verifies before contributing: source attribution, assumption audit, confidence scoring. No untagged claims.\n\n---\n\n### PHASE 3: Critic Analysis\nExecutive Mentor receives ALL Phase 2 outputs simultaneously. Role: adversarial reviewer, not synthesizer.\n\nChecklist:\n- Where did agents agree too easily? (suspicious consensus = red flag)\n- What assumptions are shared but unvalidated?\n- Who is missing from the room? (customer voice? front-line ops?)\n- What risk has nobody mentioned?\n- Which agent operated outside their domain?\n\n---\n\n### PHASE 4: Synthesis\nChief of Staff delivers using the **Board Meeting Output** format (defined in `agent-protocol\u002FSKILL.md`):\n- Decision Required (one sentence)\n- Perspectives (one line per contributing role)\n- Where They Agree \u002F Where They Disagree\n- Critic's View (the uncomfortable truth)\n- Recommended Decision + Action Items (owners, deadlines)\n- Your Call (options if founder disagrees)\n\n---\n\n### PHASE 5: Human in the Loop ⏸️\n\n**Full stop. Wait for the founder.**\n\n```\n⏸️ FOUNDER REVIEW — [Paste synthesis]\n\nOptions: ✅ Approve | ✏️ Modify | ❌ Reject | ❓ Ask follow-up\n```\n\n**Rules:**\n- User corrections OVERRIDE agent proposals. No pushback. No \"but the CFO said...\"\n- 30-min inactivity → auto-close as \"pending review\"\n- Reopen any time with `\u002Fcs:board resume`\n\n---\n\n### PHASE 6: Decision Extraction\nAfter founder approval:\n- **Layer 1:** Write full transcript → `memory\u002Fboard-meetings\u002FYYYY-MM-DD-raw.md`\n- **Layer 2:** Append approved decisions → `memory\u002Fboard-meetings\u002Fdecisions.md`\n- Mark rejected proposals `[DO_NOT_RESURFACE]`\n- Confirm to founder with count of decisions logged, actions tracked, flags added\n\n---\n\n## Memory Structure\n```\nmemory\u002Fboard-meetings\u002F\n├── decisions.md          # Layer 2 — founder-approved only (Phase 1 loads this)\n├── YYYY-MM-DD-raw.md     # Layer 1 — full transcripts (never auto-loaded)\n└── archive\u002FYYYY\u002F         # Raw transcripts after 90 days\n```\n\n**Future meetings load Layer 2 only.** Never Layer 1. This prevents hallucinated consensus.\n\n---\n\n## Failure Mode Quick Reference\n| Failure | Fix |\n|---------|-----|\n| Groupthink (all agree) | Re-run Phase 2 isolated; force \"strongest argument against\" |\n| Analysis paralysis | Cap at 5 points; force recommendation even with Low confidence |\n| Bikeshedding | Log as async action item; return to main agenda |\n| Role bleed (CFO making product calls) | Critic flags; exclude from synthesis |\n| Layer contamination | Phase 1 loads decisions.md only — hard rule |\n\n---\n\n## References\n- `templates\u002Fmeeting-agenda.md` — agenda format\n- `templates\u002Fmeeting-minutes.md` — final output format\n- `references\u002Fmeeting-facilitation.md` — conflict handling, timing, failure modes\n","# Board Meeting Protocol\n\nStructured multi-agent deliberation that prevents groupthink, captures minority views, and produces clean, actionable decisions.\n\n## Keywords\nboard meeting, executive deliberation, strategic decision, C-suite, multi-agent, \u002Fcs:board, founder review, decision extraction, independent perspectives\n\n## Invoke\n`\u002Fcs:board [topic]` — e.g. `\u002Fcs:board Should we expand to Spain in Q3?`\n\n---\n\n## The 6-Phase Protocol\n\n### PHASE 1: Context Gathering\n1. Load `memory\u002Fcompany-context.md`\n2. Load `memory\u002Fboard-meetings\u002Fdecisions.md` **(Layer 2 ONLY — never raw transcripts)**\n3. Reset session state — no bleed from previous conversations\n4. Present agenda + activated roles → wait for founder confirmation\n\n**Chief of Staff selects relevant roles** based on topic (not all 9 every time):\n| Topic | Activate |\n|-------|----------|\n| Market expansion | CEO, CMO, CFO, CRO, COO |\n| Product direction | CEO, CPO, CTO, CMO |\n| Hiring\u002Forg | CEO, CHRO, CFO, COO |\n| Pricing | CMO, CFO, CRO, CPO |\n| Technology | CTO, CPO, CFO, CISO |\n\n---\n\n### PHASE 2: Independent Contributions (ISOLATED)\n\n**No cross-pollination. Each agent runs before seeing others' outputs.**\n\nOrder: Research (if needed) → CMO → CFO → CEO → CTO → COO → CHRO → CRO → CISO → CPO\n\n**Reasoning techniques:** CEO: Tree of Thought (3 futures) | CFO: Chain of Thought (show the math) | CMO: Recursion of Thought (draft→critique→refine) | CPO: First Principles | CRO: Chain of Thought (pipeline math) | COO: Step by Step (process map) | CTO: ReAct (research→analyze→act) | CISO: Risk-Based (P×I) | CHRO: Empathy + Data\n\n**Contribution format (max 5 key points, self-verified):**\n```\n## [ROLE] — [DATE]\n\nKey points (max 5):\n• [Finding] — [VERIFIED\u002FASSUMED] — ?\u002F?\u002F?\n• [Finding] — [VERIFIED\u002FASSUMED] — ?\u002F?\u002F?\n\nRecommendation: [clear position]\nConfidence: High \u002F Medium \u002F Low\nSource: [where the data came from]\nWhat would change my mind: [specific condition]\n```\n\nEach agent self-verifies before contributing: source attribution, assumption audit, confidence scoring. No untagged claims.\n\n---\n\n### PHASE 3: Critic Analysis\nExecutive Mentor receives ALL Phase 2 outputs simultaneously. Role: adversarial reviewer, not synthesizer.\n\nChecklist:\n- Where did agents agree too easily? (suspicious consensus = red flag)\n- What assumptions are shared but unvalidated?\n- Who is missing from the room? (customer voice? front-line ops?)\n- What risk has nobody mentioned?\n- Which agent operated outside their domain?\n\n---\n\n### PHASE 4: Synthesis\nChief of Staff delivers using the **Board Meeting Output** format (defined in `agent-protocol\u002FSKILL.md`):\n- Decision Required (one sentence)\n- Perspectives (one line per contributing role)\n- Where They Agree \u002F Where They Disagree\n- Critic's View (the uncomfortable truth)\n- Recommended Decision + Action Items (owners, deadlines)\n- Your Call (options if founder disagrees)\n\n---\n\n### PHASE 5: Human in the Loop ⏸️\n\n**Full stop. Wait for the founder.**\n\n```\n⏸️ FOUNDER REVIEW — [Paste synthesis]\n\nOptions: ✅ Approve | ✏️ Modify | ❌ Reject | ❓ Ask follow-up\n```\n\n**Rules:**\n- User corrections OVERRIDE agent proposals. No pushback. No \"but the CFO said...\"\n- 30-min inactivity → auto-close as \"pending review\"\n- Reopen any time with `\u002Fcs:board resume`\n\n---\n\n### PHASE 6: Decision Extraction\nAfter founder approval:\n- **Layer 1:** Write full transcript → `memory\u002Fboard-meetings\u002FYYYY-MM-DD-raw.md`\n- **Layer 2:** Append approved decisions → `memory\u002Fboard-meetings\u002Fdecisions.md`\n- Mark rejected proposals `[DO_NOT_RESURFACE]`\n- Confirm to founder with count of decisions logged, actions tracked, flags added\n\n---\n\n## Memory Structure\n```\nmemory\u002Fboard-meetings\u002F\n├── decisions.md          # Layer 2 — founder-approved only (Phase 1 loads this)\n├── YYYY-MM-DD-raw.md     # Layer 1 — full transcripts (never auto-loaded)\n└── archive\u002FYYYY\u002F         # Raw transcripts after 90 days\n```\n\n**Future meetings load Layer 2 only.** Never Layer 1. This prevents hallucinated consensus.\n\n---\n\n## Failure Mode Quick Reference\n| Failure | Fix |\n|---------|-----|\n| Groupthink (all agree) | Re-run Phase 2 isolated; force \"strongest argument against\" |\n| Analysis paralysis | Cap at 5 points; force recommendation even with Low confidence |\n| Bikeshedding | Log as async action item; return to main agenda |\n| Role bleed (CFO making product calls) | Critic flags; exclude from synthesis |\n| Layer contamination | Phase 1 loads decisions.md only — hard rule |\n\n---\n\n## References\n- `templates\u002Fmeeting-agenda.md` — agenda format\n- `templates\u002Fmeeting-minutes.md` — final output format\n- `references\u002Fmeeting-facilitation.md` — conflict handling, timing, failure modes\n",{"name":5,"license":15,"metadata":49,"description":7},{"author":50,"domain":51,"updated":52,"version":53,"category":54,"frameworks":55},"Alireza Rezvani","board-protocol",1772668800000,"1.0.0","c-level","6-phase-board, two-layer-memory, independent-contributions","main","fa638b97a18ff6d9f26cf0eaf3dfa123531bcc87","organized-skills\u002F.gemini-board-meeting",1,"https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode","https:\u002F\u002Fgithub.com\u002Flevalencia","https:\u002F\u002Fmedium.com\u002F@luisevalencia","Microsoft MVP - Artificial Intelligence\r\nMachine Learning Enthusiast\r\n","2026-05-02 06:55:36",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add levalencia\u002Fagent-god-mode --skill board-meeting",{"tool":71,"command":72},"bunx","bunx skills add levalencia\u002Fagent-god-mode --skill board-meeting",{"tool":74,"command":75},"pnpm","pnpm dlx skills add levalencia\u002Fagent-god-mode --skill board-meeting","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002F.gemini-board-meeting\u002FSKILL.md",true,[79,85,89],{"path":80,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"references\u002Fmeeting-facilitation.md","REFERENCE","参考文档",8212,"https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002F.gemini-board-meeting\u002Freferences\u002Fmeeting-facilitation.md",{"path":86,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":87,"sourceHtmlUrl":88},"templates\u002Fmeeting-agenda.md",1976,"https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002F.gemini-board-meeting\u002Ftemplates\u002Fmeeting-agenda.md",{"path":90,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":91,"sourceHtmlUrl":92},"templates\u002Fmeeting-minutes.md",2465,"https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002F.gemini-board-meeting\u002Ftemplates\u002Fmeeting-minutes.md",[94,116,151,178,200,228],{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":100,"publishedAt":44},"01M6EM8ES5M9J4S8N78NJST0YC","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fzarr-python\u002FSKILL.md",[],[101,102,103,104,105,106,107,108,109,110,111,112,113,114,115],"python","zarr python","storage","integration","s3","gcs","cloud","dask","parallel","pipelines","arrays","numpy","scientific computing","scale","scientific",{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":133,"publishedAt":44},"01M6EM8AR6ZFKZ9YVW8TTG850Z","zabbix","Zabbix monitoring system automation via API and Python. Use when: (1) Managing hosts, templates, items, triggers, or host groups, (2) Automating monitoring configuration, (3) Sending data via Zabbix trapper\u002Fsender, (4) Querying historical data or events, (5) Bulk operations on Zabbix objects, (6) Maintenance window management, (7) User\u002Fpermission management","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fzabbix-api-skill\u002FSKILL.md",[122,127,130],{"categoryNo":123,"categoryName":124,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":128,"categoryName":129,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":131,"categoryName":132,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师",[118,101,134,135,136,137,138,139,140,141,32,142,143,144,145,146,147,148,149,150],"automation","window management","monitoring","data","templates","api","system","operations","maintenance","objects","permission","bulk operations","triggers","host","events","via","bulk",{"skillNo":152,"name":153,"nameZh":6,"description":154,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":155,"categories":156,"keywords":157,"publishedAt":44},"01M6EM6Q9JG846ECQY9A210A26","x-twitter-growth","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.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fx-twitter-growth\u002FSKILL.md",[],[158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177],"twitter","x twitter growth","growth","competitive intelligence","search","analyzing","plan","marketing","web search","competitors","analyze","write","optimize","social","intelligence","viral","growth engine","mechanics","grow","competitive",{"skillNo":179,"name":180,"nameZh":6,"description":181,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":182,"categories":183,"keywords":184,"publishedAt":44},"01M6EM3FQNPYNKPC4CV9TCVNGD","what-if-oracle","Run structured What-If scenario analysis with multi-branch possibility exploration. Use this skill when the user asks speculative questions like \"what if...\", \"what would happen if...\", \"what are the possibilities\", \"explore scenarios\", \"scenario analysis\", \"possibility space\", \"what could go wrong\", \"best case \u002F worst case\", \"risk analysis\", \"contingency planning\", \"strategic options\", or any question about uncertain futures. Also trigger when the user faces a fork-in-the-road decision, wants to stress-test an idea, or needs to think through consequences before committing.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fwhat-if-oracle\u002FSKILL.md",[],[185,186,187,188,189,190,191,40,192,37,193,35,32,194,195,196,197,198,199,26],"oracle","what if oracle","test","planning","ux","futures","risk","explore","branch","exploration","options","stress-test","strategies","trigger","case",{"skillNo":201,"name":202,"nameZh":6,"description":203,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":204,"categories":205,"keywords":209,"publishedAt":44},"01M6EM08C06RGDYCJ86HAPK0FF","vercel-react-best-practices","React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React\u002FNext.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fvercel-react-best-practices\u002FSKILL.md",[206],{"categoryNo":207,"categoryName":208,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000009","前端开发",[210,211,212,213,214,215,216,217,218,219,220,221,222,137,223,224,225,226,227,146],"react","vercel react best practices","best practices","react best practices","vercel","writing","performance","components","react components","guidelines","tasks","code","Optimization","Next.js","refactoring","performance optimization","next","pages",{"skillNo":229,"name":230,"nameZh":6,"description":231,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":232,"categories":233,"keywords":244,"publishedAt":44},"01M6EM00S13326QM08DTM94J6Z","venue-templates","Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.","https:\u002F\u002Fgithub.com\u002Flevalencia\u002Fagent-god-mode\u002Fblob\u002Fmain\u002Forganized-skills\u002Fvenue-templates\u002FSKILL.md",[234,237,240,241],{"categoryNo":235,"categoryName":236,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":238,"categoryName":239,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":128,"categoryName":129,"taxonomyType":125,"taxonomyTypeDesc":126},{"categoryNo":242,"categoryName":243,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000036","内容创作者",[138,245,246,219,247,248,249,250,251,252,253,169,254,255,256,257,258,259,115,260],"venue templates","research","NeurIPS","ICML","LaTeX","science","Bash","access","read","edit","proposals","Academic","requirements","formatting","journal","chi"]