[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CXNDJKVASH8EP74YPR108B":3,"skill-same:01M6CXNDJKVASH8EP74YPR108B":112},{"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":31,"publishedAt":52,"linkOnly":53,"markdownContent":54,"markdownBody":55,"frontMatter":56,"refName":66,"commitSha":67,"skillDirectory":68,"forksCount":69,"repositoryHtmlUrl":70,"repositoryHomepageUrl":71,"ownerHtmlUrl":72,"ownerBlogUrl":73,"ownerDescription":74,"updatedAt":75,"install":76,"resources":89},"01M6CXNDJKVASH8EP74YPR108B","database-optimizer",null,"Optimizes database queries and improves performance across PostgreSQL and MySQL systems. Use when investigating slow queries, analyzing execution plans, or optimizing database performance. Invoke for index design, query rewrites, configuration tuning, partitioning strategies, lock contention resolution.","eric861129\u002FSKILLS_All-in-one","eric861129","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F74950944?v=4","01M6CXHDYEYRPFGGV4EFXCSYCF","ChiYu-Huang","01M6CXHE2J5CN1EBTY0FKV3ZKW",52,"MIT","https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer\u002FSKILL.md",[18,23,26],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"optimizer","database","database optimizer","strategies","design","across","query","engineer","analyze","plan","analysis","tuning","postgresql optimization","analyzing","postgresql","mysql","code","execution plan","database performance","performance","2026-11-10 10:12:30",false,"---\nname: database-optimizer\ndescription: Optimizes database queries and improves performance across PostgreSQL and MySQL systems. Use when investigating slow queries, analyzing execution plans, or optimizing database performance. Invoke for index design, query rewrites, configuration tuning, partitioning strategies, lock contention resolution.\nlicense: MIT\nmetadata:\n  author: https:\u002F\u002Fgithub.com\u002FJeffallan\n  version: \"1.1.0\"\n  domain: infrastructure\n  triggers: database optimization, slow query, query performance, database tuning, index optimization, execution plan, EXPLAIN ANALYZE, database performance, PostgreSQL optimization, MySQL optimization\n  role: specialist\n  scope: optimization\n  output-format: analysis-and-code\n  related-skills: devops-engineer\n---\n\n# Database Optimizer\n\nSenior database optimizer with expertise in performance tuning, query optimization, and scalability across multiple database systems.\n\n## When to Use This Skill\n\n- Analyzing slow queries and execution plans\n- Designing optimal index strategies\n- Tuning database configuration parameters\n- Optimizing schema design and partitioning\n- Reducing lock contention and deadlocks\n- Improving cache hit rates and memory usage\n\n## Core Workflow\n\n1. **Analyze Performance** — Capture baseline metrics and run `EXPLAIN ANALYZE` before any changes\n2. **Identify Bottlenecks** — Find inefficient queries, missing indexes, config issues\n3. **Design Solutions** — Create index strategies, query rewrites, schema improvements\n4. **Implement Changes** — Apply optimizations incrementally with monitoring; validate each change before proceeding to the next\n5. **Validate Results** — Re-run `EXPLAIN ANALYZE`, compare costs, measure wall-clock improvement, document changes\n\n> ⚠️ Always test changes in non-production first. Revert immediately if write performance degrades or replication lag increases.\n\n## Reference Guide\n\nLoad detailed guidance based on context:\n\n| Topic | Reference | Load When |\n|-------|-----------|-----------|\n| Query Optimization | `references\u002Fquery-optimization.md` | Analyzing slow queries, execution plans |\n| Index Strategies | `references\u002Findex-strategies.md` | Designing indexes, covering indexes |\n| PostgreSQL Tuning | `references\u002Fpostgresql-tuning.md` | PostgreSQL-specific optimizations |\n| MySQL Tuning | `references\u002Fmysql-tuning.md` | MySQL-specific optimizations |\n| Monitoring & Analysis | `references\u002Fmonitoring-analysis.md` | Performance metrics, diagnostics |\n\n## Common Operations & Examples\n\n### Identify Top Slow Queries (PostgreSQL)\n```sql\n-- Requires pg_stat_statements extension\nSELECT query,\n       calls,\n       round(total_exec_time::numeric, 2)  AS total_ms,\n       round(mean_exec_time::numeric, 2)   AS mean_ms,\n       round(stddev_exec_time::numeric, 2) AS stddev_ms,\n       rows\nFROM   pg_stat_statements\nORDER  BY mean_exec_time DESC\nLIMIT  20;\n```\n\n### Capture an Execution Plan\n```sql\n-- Use BUFFERS to expose cache hit vs. disk read ratio\nEXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)\nSELECT o.id, c.name\nFROM   orders o\nJOIN   customers c ON c.id = o.customer_id\nWHERE  o.status = 'pending'\n  AND  o.created_at > now() - interval '7 days';\n```\n\n### Reading EXPLAIN Output — Key Patterns to Find\n\n| Pattern | Symptom | Typical Remedy |\n|---------|---------|----------------|\n| `Seq Scan` on large table | High row estimate, no filter selectivity | Add B-tree index on filter column |\n| `Nested Loop` with large outer set | Exponential row growth in inner loop | Consider Hash Join; index inner join key |\n| `cost=... rows=1` but actual rows=50000 | Stale statistics | Run `ANALYZE \u003Ctable>;` |\n| `Buffers: hit=10 read=90000` | Low buffer cache hit rate | Increase `shared_buffers`; add covering index |\n| `Sort Method: external merge` | Sort spilling to disk | Increase `work_mem` for the session |\n\n### Create a Covering Index\n```sql\n-- Covers the filter AND the projected columns, eliminating a heap fetch\nCREATE INDEX CONCURRENTLY idx_orders_status_created_covering\n    ON orders (status, created_at)\n    INCLUDE (customer_id, total_amount);\n```\n\n### Validate Improvement\n```sql\n-- Before optimization: save plan & timing\nEXPLAIN (ANALYZE, BUFFERS) \u003Cquery>;   -- note \"Execution Time: X ms\"\n\n-- After optimization: compare\nEXPLAIN (ANALYZE, BUFFERS) \u003Cquery>;   -- target meaningful reduction in cost & time\n\n-- Confirm index is actually used\nSELECT indexname, idx_scan, idx_tup_read, idx_tup_fetch\nFROM   pg_stat_user_indexes\nWHERE  relname = 'orders';\n```\n\n### MySQL: Find Slow Queries\n```sql\n-- Inspect slow query log candidates\nSELECT * FROM performance_schema.events_statements_summary_by_digest\nORDER  BY SUM_TIMER_WAIT DESC\nLIMIT  20;\n\n-- Execution plan\nEXPLAIN FORMAT=JSON\nSELECT * FROM orders WHERE status = 'pending' AND created_at > NOW() - INTERVAL 7 DAY;\n```\n\n## Constraints\n\n### MUST DO\n- Capture `EXPLAIN (ANALYZE, BUFFERS)` output **before** optimizing — this is the baseline\n- Measure performance before and after every change\n- Create indexes with `CONCURRENTLY` (PostgreSQL) to avoid table locks\n- Test in non-production; roll back if write performance or replication lag worsens\n- Document all optimization decisions with before\u002Fafter metrics\n- Run `ANALYZE` after bulk data changes to refresh statistics\n\n### MUST NOT DO\n- Apply optimizations without a measured baseline\n- Create redundant or unused indexes\n- Make multiple changes simultaneously (impossible to attribute impact)\n- Ignore write amplification caused by new indexes\n- Neglect `VACUUM` \u002F statistics maintenance\n\n## Output Templates\n\nWhen optimizing database performance, provide:\n1. Performance analysis with baseline metrics (query time, cost, buffer hit ratio)\n2. Identified bottlenecks and root causes (with EXPLAIN evidence)\n3. Optimization strategy with specific changes\n4. Implementation SQL \u002F config changes\n5. Validation queries to measure improvement\n6. Monitoring recommendations\n","# Database Optimizer\n\nSenior database optimizer with expertise in performance tuning, query optimization, and scalability across multiple database systems.\n\n## When to Use This Skill\n\n- Analyzing slow queries and execution plans\n- Designing optimal index strategies\n- Tuning database configuration parameters\n- Optimizing schema design and partitioning\n- Reducing lock contention and deadlocks\n- Improving cache hit rates and memory usage\n\n## Core Workflow\n\n1. **Analyze Performance** — Capture baseline metrics and run `EXPLAIN ANALYZE` before any changes\n2. **Identify Bottlenecks** — Find inefficient queries, missing indexes, config issues\n3. **Design Solutions** — Create index strategies, query rewrites, schema improvements\n4. **Implement Changes** — Apply optimizations incrementally with monitoring; validate each change before proceeding to the next\n5. **Validate Results** — Re-run `EXPLAIN ANALYZE`, compare costs, measure wall-clock improvement, document changes\n\n> ⚠️ Always test changes in non-production first. Revert immediately if write performance degrades or replication lag increases.\n\n## Reference Guide\n\nLoad detailed guidance based on context:\n\n| Topic | Reference | Load When |\n|-------|-----------|-----------|\n| Query Optimization | `references\u002Fquery-optimization.md` | Analyzing slow queries, execution plans |\n| Index Strategies | `references\u002Findex-strategies.md` | Designing indexes, covering indexes |\n| PostgreSQL Tuning | `references\u002Fpostgresql-tuning.md` | PostgreSQL-specific optimizations |\n| MySQL Tuning | `references\u002Fmysql-tuning.md` | MySQL-specific optimizations |\n| Monitoring & Analysis | `references\u002Fmonitoring-analysis.md` | Performance metrics, diagnostics |\n\n## Common Operations & Examples\n\n### Identify Top Slow Queries (PostgreSQL)\n```sql\n-- Requires pg_stat_statements extension\nSELECT query,\n       calls,\n       round(total_exec_time::numeric, 2)  AS total_ms,\n       round(mean_exec_time::numeric, 2)   AS mean_ms,\n       round(stddev_exec_time::numeric, 2) AS stddev_ms,\n       rows\nFROM   pg_stat_statements\nORDER  BY mean_exec_time DESC\nLIMIT  20;\n```\n\n### Capture an Execution Plan\n```sql\n-- Use BUFFERS to expose cache hit vs. disk read ratio\nEXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)\nSELECT o.id, c.name\nFROM   orders o\nJOIN   customers c ON c.id = o.customer_id\nWHERE  o.status = 'pending'\n  AND  o.created_at > now() - interval '7 days';\n```\n\n### Reading EXPLAIN Output — Key Patterns to Find\n\n| Pattern | Symptom | Typical Remedy |\n|---------|---------|----------------|\n| `Seq Scan` on large table | High row estimate, no filter selectivity | Add B-tree index on filter column |\n| `Nested Loop` with large outer set | Exponential row growth in inner loop | Consider Hash Join; index inner join key |\n| `cost=... rows=1` but actual rows=50000 | Stale statistics | Run `ANALYZE \u003Ctable>;` |\n| `Buffers: hit=10 read=90000` | Low buffer cache hit rate | Increase `shared_buffers`; add covering index |\n| `Sort Method: external merge` | Sort spilling to disk | Increase `work_mem` for the session |\n\n### Create a Covering Index\n```sql\n-- Covers the filter AND the projected columns, eliminating a heap fetch\nCREATE INDEX CONCURRENTLY idx_orders_status_created_covering\n    ON orders (status, created_at)\n    INCLUDE (customer_id, total_amount);\n```\n\n### Validate Improvement\n```sql\n-- Before optimization: save plan & timing\nEXPLAIN (ANALYZE, BUFFERS) \u003Cquery>;   -- note \"Execution Time: X ms\"\n\n-- After optimization: compare\nEXPLAIN (ANALYZE, BUFFERS) \u003Cquery>;   -- target meaningful reduction in cost & time\n\n-- Confirm index is actually used\nSELECT indexname, idx_scan, idx_tup_read, idx_tup_fetch\nFROM   pg_stat_user_indexes\nWHERE  relname = 'orders';\n```\n\n### MySQL: Find Slow Queries\n```sql\n-- Inspect slow query log candidates\nSELECT * FROM performance_schema.events_statements_summary_by_digest\nORDER  BY SUM_TIMER_WAIT DESC\nLIMIT  20;\n\n-- Execution plan\nEXPLAIN FORMAT=JSON\nSELECT * FROM orders WHERE status = 'pending' AND created_at > NOW() - INTERVAL 7 DAY;\n```\n\n## Constraints\n\n### MUST DO\n- Capture `EXPLAIN (ANALYZE, BUFFERS)` output **before** optimizing — this is the baseline\n- Measure performance before and after every change\n- Create indexes with `CONCURRENTLY` (PostgreSQL) to avoid table locks\n- Test in non-production; roll back if write performance or replication lag worsens\n- Document all optimization decisions with before\u002Fafter metrics\n- Run `ANALYZE` after bulk data changes to refresh statistics\n\n### MUST NOT DO\n- Apply optimizations without a measured baseline\n- Create redundant or unused indexes\n- Make multiple changes simultaneously (impossible to attribute impact)\n- Ignore write amplification caused by new indexes\n- Neglect `VACUUM` \u002F statistics maintenance\n\n## Output Templates\n\nWhen optimizing database performance, provide:\n1. Performance analysis with baseline metrics (query time, cost, buffer hit ratio)\n2. Identified bottlenecks and root causes (with EXPLAIN evidence)\n3. Optimization strategy with specific changes\n4. Implementation SQL \u002F config changes\n5. Validation queries to measure improvement\n6. Monitoring recommendations\n",{"name":5,"license":15,"metadata":57,"description":7},{"role":58,"scope":59,"author":60,"domain":61,"version":62,"triggers":63,"output-format":64,"related-skills":65},"specialist","optimization","https:\u002F\u002Fgithub.com\u002FJeffallan","infrastructure","1.1.0","database optimization, slow query, query performance, database tuning, index optimization, execution plan, EXPLAIN ANALYZE, database performance, PostgreSQL optimization, MySQL optimization","analysis-and-code","devops-engineer","main","cbdd44aae21131521c09e42762e36178c790eacf","public\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer",13,"https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one","http:\u002F\u002Fhuangchiyu.com\u002FSKILLS_All-in-one\u002F","https:\u002F\u002Fgithub.com\u002Feric861129","https:\u002F\u002Fhuangchiyu.com\u002FChiYu-Blog\u002F","開發工程師，專注於 C#／.NET 系統現代化、AI-assisted engineering、開源工具與技術寫作。","2026-04-16 14:28:14",{"source":8,"skillName":5,"commands":77,"prompt":87,"zipAvailable":88},[78,81,84],{"tool":79,"command":80},"npx","npx skills add eric861129\u002FSKILLS_All-in-one --skill database-optimizer",{"tool":82,"command":83},"bunx","bunx skills add eric861129\u002FSKILLS_All-in-one --skill database-optimizer",{"tool":85,"command":86},"pnpm","pnpm dlx skills add eric861129\u002FSKILLS_All-in-one --skill database-optimizer","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer\u002FSKILL.md",true,[90,96,100,104,108],{"path":91,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":94,"sourceHtmlUrl":95},"references\u002Findex-strategies.md","REFERENCE","参考文档",8131,"https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer\u002Freferences\u002Findex-strategies.md",{"path":97,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":98,"sourceHtmlUrl":99},"references\u002Fmonitoring-analysis.md",14596,"https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer\u002Freferences\u002Fmonitoring-analysis.md",{"path":101,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":102,"sourceHtmlUrl":103},"references\u002Fmysql-tuning.md",11021,"https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer\u002Freferences\u002Fmysql-tuning.md",{"path":105,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":106,"sourceHtmlUrl":107},"references\u002Fpostgresql-tuning.md",10284,"https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer\u002Freferences\u002Fpostgresql-tuning.md",{"path":109,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":110,"sourceHtmlUrl":111},"references\u002Fquery-optimization.md",5793,"https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FData & Analysis\u002Fdatabase-optimizer\u002Freferences\u002Fquery-optimization.md",[113,139,170,195,220,240],{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":120,"publishedAt":52},"01M6CZ1WR3KNVTKSWH4GNWT646","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\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FWriting & Research\u002Fwhat-if-oracle\u002FSKILL.md",[119],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[121,122,123,124,125,126,127,128,42,129,130,131,132,133,134,135,136,137,138,35],"oracle","what if oracle","go","run","planning","ux","futures","risk","explore","decision","branch","question","read","write","idea","exploration","options","stress-test",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":155,"publishedAt":52},"01M6CZ1QHGJE91A95MSN5EK5Q9","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\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FWriting & Research\u002Fvenue-templates\u002FSKILL.md",[145,148,151,152],{"categoryNo":146,"categoryName":147,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":149,"categoryName":150,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":153,"categoryName":154,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000036","内容创作者",[156,157,158,159,160,161,162,163,164,165,133,134,166,167,168,169],"templates","venue templates","research","guidelines","NeurIPS","ICML","LaTeX","science","Bash","access","edit","proposals","Academic","requirements",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":174,"categories":175,"keywords":178,"publishedAt":52},"01M6CZ1KBQD2E5RTFB3BGVX7CD","the-fool","Use when challenging ideas, plans, decisions, or proposals using structured critical reasoning. Invoke to play devil's advocate, run a pre-mortem, red team, or audit evidence and assumptions.","https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FWriting & Research\u002Fthe-fool\u002FSKILL.md",[176,177],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},[179,180,123,181,182,124,48,183,184,185,186,187,188,189,167,190,191,192,193,194],"the fool","review","workflow","architecture","audit","forge","devil","team","designer","reviewer","challenge","stress test","evidence","expert","poke","ideas",{"skillNo":196,"name":197,"nameZh":6,"description":198,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":199,"categories":200,"keywords":204,"publishedAt":52},"01M6CZ1ES826S7P1X3333E40TA","scientific-writing","Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA\u002FAMA\u002FVancouver), figures\u002Ftables, reporting guidelines (CONSORT\u002FSTROBE\u002FPRISMA), for research papers and journal submissions.","https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FWriting & Research\u002Fscientific-writing\u002FSKILL.md",[201,202,203],{"categoryNo":146,"categoryName":147,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":153,"categoryName":154,"taxonomyType":29,"taxonomyTypeDesc":30},[205,206,159,207,208,209,210,211,164,212,133,134,166,213,214,215,216,217,218,219],"writing","scientific writing","core","reporting","deep research","Citations","Outlines","tool","use","never","structure","deep","full","stage","prisma",{"skillNo":221,"name":222,"nameZh":6,"description":223,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":224,"categories":225,"keywords":227,"publishedAt":52},"01M6CZ1B2JGJTB9FRD0TW4RXXE","scientific-brainstorming","Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.","https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FWriting & Research\u002Fscientific-brainstorming\u002FSKILL.md",[226],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[228,229,158,230,125,231,232,233,213,234,235,236,136,237,238,218,239],"brainstorming","scientific brainstorming","sessions","data","hypothesis","open","ideation","creative","do","connections","research ideation","generation",{"skillNo":241,"name":242,"nameZh":6,"description":243,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":244,"categories":245,"keywords":250,"publishedAt":52},"01M6CZ16JG8N7A2ZX04BGE8J2Y","research-lookup","Look up current research information using the Parallel Chat API (primary) or Perplexity sonar-pro-search (academic paper searches). Automatically routes queries to the best backend. Use for finding papers, gathering research data, and verifying scientific information.","https:\u002F\u002Fgithub.com\u002Feric861129\u002FSKILLS_All-in-one\u002Fblob\u002Fmain\u002Fpublic\u002FSKILLS\u002FWriting & Research\u002Fresearch-lookup\u002FSKILL.md",[246,247,248,249],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":149,"categoryName":150,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},[158,251,252,253,231,254,255,164,256,257,133,134,166,213,258,259,260,261,262,168],"lookup","research lookup","search","perplexity","api","parallel","openrouter","backend","up","look","queries","chat"]