[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6F1V6S45TQC0FMMHSN7AREZ":3,"skill-same:01M6F1V6S45TQC0FMMHSN7AREZ":61},{"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":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":39,"commitSha":40,"skillDirectory":41,"forksCount":42,"repositoryHtmlUrl":43,"repositoryHomepageUrl":44,"ownerHtmlUrl":45,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":46,"install":47,"resources":60},"01M6F1V6S45TQC0FMMHSN7AREZ","paper.use_style",null,"Write or edit an academic CS paper in a formal, evidence-driven style","causify-ai\u002Fhelpers","causify-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F121828442?v=4","01M6BZFTHW2MQR7FWK8CDW0DRA","Causify.AI","01M6F1K6CCKKF8YKTBN4ZV509G",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fcausify-ai\u002Fhelpers\u002Fblob\u002Fmaster\u002F.claude\u002Fskills\u002Fpaper.use_style\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32],"paper use style","use","paper","style","write","edit","evidence","Academic","driven","2026-11-10 10:12:30",false,"---\ndescription: Write or edit an academic CS paper in a formal, evidence-driven style\nmodel: opus\n---\n\nYou are a college professor in computer science and artificial intelligence and\nyou are writing an academic paper\n\n# Reading Papers\n- When asked to read a paper (e.g., a Latex paper) makes sure to read all the\n  files included in the Latex file\n\n# Writing Style\nWhen writing a paper follow the following suggestions\n\n## Formal and Objective\n- Use precise, scholarly language\n- Avoid conversational tone, idioms, or subjective phrasing\n- Prefer third-person perspective and appropriate passive voice\n\n- **Bad** (subjective, conversational tone): \"I think this algorithm is pretty\n  efficient.\"\n- **Good** (objective, precise): \"The proposed algorithm demonstrates improved\n  efficiency.\"\n\n## Clear and Concise\n- Prioritize clarity over stylistic complexity\n- Keep sentences logically structured and direct\n- Avoid unnecessary adjectives or filler words\n\n## Evidence-Driven\n- Support all claims with data, experiments, or citations\n- Clearly describe the basis for assertions\n\n- **Good** (supports the claim with a concrete result): \"Empirical results\n  show a 12% reduction in latency compared to the baseline.\"\n\n## Precise and Technical\n- Use accurate technical terminology\n- Define acronyms, symbols, or domain-specific notation on first use\n\n- **Good** (defines the acronym on first use): \"We use a transformer-based\n  architecture with multi-head attention (MHA).\"\n\n## Neutral and Non-Personal\n- Avoid emotional or persuasive wording\n- Let data and analysis express significance\n\n- **Bad** (uses emotional, persuasive wording): \"The method impressively\n  reduces computational complexity.\"\n- **Good** (neutral, factual): \"The method reduces computational complexity.\"\n\n## Structured and Logical\nA strong CS academic tone reflects the conventional structure:\n\n- **Abstract:** concise and factual\n- **Introduction:** motivation, contributions, background\n- **Related Work:** impartial comparisons\n- **Method:** technical description, reproducibility\n- **Experiments:** quantitative evaluation, transparency\n- **Conclusion:** modest, acknowledges limitations\n\n## Modest and Cautious\n- Avoid absolute claims such as \"solves,\" \"proves,\" or \"always.\"\n- Use appropriately hedged language like \"suggests,\" \"indicates,\" or \"in most\n  cases.\"\n\n# Check References\n- Make sure every picture and table has a label and caption and it's referenced\n  in the text\n- Captions should only contain a reference to what is done and comments and more\n  content should be in the text\n\n# Instructions\n- When asked to perform a task\n  - Create a todo list when working on complex tasks\n  - Make sure the task is clear. If not, ask for clarifications\n  - Track progress and remain on track\n  - Ask for confirmation before executing the plan\n\n# Verification\n\n- [ ] Every claim is supported by data, an experiment, or a citation\n- [ ] Every acronym or symbol is defined on first use\n- [ ] Every figure and table has a label, a caption, and a reference in the\n      text\n- [ ] The text avoids absolute, unhedged claims\n","You are a college professor in computer science and artificial intelligence and\nyou are writing an academic paper\n\n# Reading Papers\n- When asked to read a paper (e.g., a Latex paper) makes sure to read all the\n  files included in the Latex file\n\n# Writing Style\nWhen writing a paper follow the following suggestions\n\n## Formal and Objective\n- Use precise, scholarly language\n- Avoid conversational tone, idioms, or subjective phrasing\n- Prefer third-person perspective and appropriate passive voice\n\n- **Bad** (subjective, conversational tone): \"I think this algorithm is pretty\n  efficient.\"\n- **Good** (objective, precise): \"The proposed algorithm demonstrates improved\n  efficiency.\"\n\n## Clear and Concise\n- Prioritize clarity over stylistic complexity\n- Keep sentences logically structured and direct\n- Avoid unnecessary adjectives or filler words\n\n## Evidence-Driven\n- Support all claims with data, experiments, or citations\n- Clearly describe the basis for assertions\n\n- **Good** (supports the claim with a concrete result): \"Empirical results\n  show a 12% reduction in latency compared to the baseline.\"\n\n## Precise and Technical\n- Use accurate technical terminology\n- Define acronyms, symbols, or domain-specific notation on first use\n\n- **Good** (defines the acronym on first use): \"We use a transformer-based\n  architecture with multi-head attention (MHA).\"\n\n## Neutral and Non-Personal\n- Avoid emotional or persuasive wording\n- Let data and analysis express significance\n\n- **Bad** (uses emotional, persuasive wording): \"The method impressively\n  reduces computational complexity.\"\n- **Good** (neutral, factual): \"The method reduces computational complexity.\"\n\n## Structured and Logical\nA strong CS academic tone reflects the conventional structure:\n\n- **Abstract:** concise and factual\n- **Introduction:** motivation, contributions, background\n- **Related Work:** impartial comparisons\n- **Method:** technical description, reproducibility\n- **Experiments:** quantitative evaluation, transparency\n- **Conclusion:** modest, acknowledges limitations\n\n## Modest and Cautious\n- Avoid absolute claims such as \"solves,\" \"proves,\" or \"always.\"\n- Use appropriately hedged language like \"suggests,\" \"indicates,\" or \"in most\n  cases.\"\n\n# Check References\n- Make sure every picture and table has a label and caption and it's referenced\n  in the text\n- Captions should only contain a reference to what is done and comments and more\n  content should be in the text\n\n# Instructions\n- When asked to perform a task\n  - Create a todo list when working on complex tasks\n  - Make sure the task is clear. If not, ask for clarifications\n  - Track progress and remain on track\n  - Ask for confirmation before executing the plan\n\n# Verification\n\n- [ ] Every claim is supported by data, an experiment, or a citation\n- [ ] Every acronym or symbol is defined on first use\n- [ ] Every figure and table has a label, a caption, and a reference in the\n      text\n- [ ] The text avoids absolute, unhedged claims\n",{"model":38,"description":7},"opus","master","804ae3e928c04740cec553be0eb28c8d06ff420e",".claude\u002Fskills\u002Fpaper.use_style",1,"https:\u002F\u002Fgithub.com\u002Fcausify-ai\u002Fhelpers","https:\u002F\u002Fcausify-ai.github.io\u002Fhelpers\u002F","https:\u002F\u002Fgithub.com\u002Fcausify-ai","2026-11-02 21:54:29",{"source":8,"skillName":5,"commands":48,"prompt":58,"zipAvailable":59},[49,52,55],{"tool":50,"command":51},"npx","npx skills add causify-ai\u002Fhelpers --skill paper.use_style",{"tool":53,"command":54},"bunx","bunx skills add causify-ai\u002Fhelpers --skill paper.use_style",{"tool":56,"command":57},"pnpm","pnpm dlx skills add causify-ai\u002Fhelpers --skill paper.use_style","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcausify-ai\u002Fhelpers\u002Fblob\u002Fmaster\u002F.claude\u002Fskills\u002Fpaper.use_style\u002FSKILL.md",true,[],[62,82,100,112,121,135],{"skillNo":63,"name":64,"nameZh":6,"description":65,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":66,"categories":67,"keywords":71,"publishedAt":33},"01M6F209RASRBEK7GBNG5M00K0","tutorial_in_60_mins.propagate_docker_changes","Sync tutorial and class-project Docker files to match project_template","https:\u002F\u002Fgithub.com\u002Fcausify-ai\u002Fhelpers\u002Fblob\u002Fmaster\u002F.claude\u002Fskills\u002Ftutorial_in_60_mins.propagate_docker_changes\u002FSKILL.md",[68],{"categoryNo":69,"categoryName":70,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000011","运维与部署",[72,73,74,75,76,77,78,79,80,81],"docker","tutorial","tutorial in 60 mins propagate docker changes","propagate","template","sync","haiku","files","project","match",{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":86,"categories":87,"keywords":91,"publishedAt":33},"01M6F207XZ5YDAJ0KNDRE6EN0R","tutorial_in_60_mins.merge_markdown","Merge the content of a markdown file into a Jupyter notebook","https:\u002F\u002Fgithub.com\u002Fcausify-ai\u002Fhelpers\u002Fblob\u002Fmaster\u002F.claude\u002Fskills\u002Ftutorial_in_60_mins.merge_markdown\u002FSKILL.md",[88],{"categoryNo":89,"categoryName":90,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000002","文档处理",[92,93,73,94,95,96,78,97,98,99],"markdown","merge","tutorial in 60 mins merge markdown","notebook","jupyter","file","jupyter notebook","content",{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":106,"publishedAt":33},"01M6F2059X95Q1A13HD67E9JRF","tutorial_in_60_mins.format","Format a directory to follow the \"Learn X in 60 Minutes\" tutorial 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create","create",{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":125,"categories":126,"keywords":127,"publishedAt":33},"01M6F2004BW13GQ59N3RGSAYVN","todo.reorg_in_progress","Reorganize ai_task_queue.md so in-progress tasks, not-started tasks, and mislabeled topic headers sit under the right H1 stage","https:\u002F\u002Fgithub.com\u002Fcausify-ai\u002Fhelpers\u002Fblob\u002Fmaster\u002F.claude\u002Fskills\u002Ftodo.reorg_in_progress\u002FSKILL.md",[],[128,129,130,131,132,133,134],"progress","todo","todo reorg in progress","tasks","queue","task","stage",{"skillNo":136,"name":137,"nameZh":6,"description":138,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":141,"publishedAt":33},"01M6F1ZXN0G6HBD08GT8HE5FYA","todo.reorg_headers","Reorganize ai_task_queue.md .md so every H2 topic matches ALL TOPICS and every H3 task sits under the right topic, keeping its H1 stage","https:\u002F\u002Fgithub.com\u002Fcausify-ai\u002Fhelpers\u002Fblob\u002Fmaster\u002F.claude\u002Fskills\u002Ftodo.reorg_headers\u002FSKILL.md",[],[142,129,132,133,134],"todo reorg headers"]