[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M73GR5D0HD5VRB3NCE4NVRJY":3,"skill-same:01M73GR5D0HD5VRB3NCE4NVRJY":89},{"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":42,"commitSha":43,"skillDirectory":44,"forksCount":45,"repositoryHtmlUrl":46,"repositoryHomepageUrl":47,"ownerHtmlUrl":48,"ownerBlogUrl":49,"ownerDescription":50,"updatedAt":51,"install":52,"resources":65},"01M73GR5D0HD5VRB3NCE4NVRJY","competitive-teardown",null,"定位图 + 功能矩阵 + 价格对比 + 机会窗口, 把竞品资料转成产品决策报告","Horonomos-laps\u002FYana-AI","Horonomos-laps","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F355299122?v=4","01M76B3QPXE88ET2SQPDPVATZT"," Horonomos-laps","01M72ZQRJPCYPSSWT4D00VJR2A",13,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Ftools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: competitive-teardown\nzh_name: \"竞品拆解\"\nen_name: \"Competitive Teardown\"\nemoji: \"🧩\"\ndescription: \"定位图 + 功能矩阵 + 价格对比 + 机会窗口, 把竞品资料转成产品决策报告\"\ncategory: doc\nscenario: product\naspect_hint: \"战略长页面\"\nfeatured: 8\ntags: [\"competitive\", \"teardown\", \"strategy\", \"product\", \"竞品\", \"拆解\"]\nexample_id: sample-competitive-teardown\nexample_name: \"竞品拆解 · AI Meeting Assistants\"\nexample_format: markdown\nexample_tagline: \"比较矩阵 + 定位象限 + 我们的应对\"\nexample_desc: \"把三家竞品的定位、价格、功能、评价转成产品团队可行动的拆解报告。\"\n---\n\n【模板: 竞品拆解 \u002F Competitive Teardown】\n【意图】这不是文章、不是 PRD、不是 pitch deck。目标是把多个竞品的杂乱资料转成一份可决策的产品战略报告, 帮团队回答: \"我们和它们到底差在哪里, 下一步该怎么打?\"\n\n【适合输入】\n- 竞品官网 \u002F 定价页 \u002F changelog \u002F 用户评论 \u002F 销售反馈 \u002F 内部调研笔记\n- 2-6 个竞品最合适; 如果用户只给一个竞品, 输出单竞品 deep dive\n- 可以包含表格、bullet、链接摘录、访谈记录、截图说明\n\n【必须输出的结构】\n1. Header: 市场 \u002F 产品类别 \u002F 报告日期 \u002F 结论一句话。\n2. Executive takeaway: 3 条最重要判断, 每条必须包含 \"so what\"。\n3. Positioning map: 用 2×2 象限或坐标图表现竞品定位。坐标轴必须来自用户内容, 不要套模板词。\n4. Competitor cards: 每个竞品一张卡, 包含 target user、core promise、pricing signal、primary strength、visible weakness。\n5. Feature matrix: 行是关键能力, 列是竞品 + \"Us \u002F Opportunity\"; 用 ✓ \u002F △ \u002F — 表达覆盖度, 并用短注释说明。\n6. Pricing \u002F packaging read: 价格层级、免费试用、限制项、企业销售动作。\n7. UX \u002F messaging notes: 从用户材料中抽取 4-6 条可观察细节, 不要泛泛而谈。\n8. Opportunity windows: 3 个机会窗口, 每个包含 why now、target segment、first move、risk。\n9. Recommended moves: 近期 30 天 \u002F 90 天 \u002F 180 天行动建议。\n\n【设计要求】\n- 战略咨询 + 产品战情室风格: 信息密度高、扫描快、图表清楚。\n- 使用 restrained palette: ink \u002F paper \u002F muted blue \u002F signal amber 或类似专业色。\n- Feature matrix 必须横向可读; 小屏可变成 stacked cards。\n- 不要做成营销落地页, 不要做成普通文章。\n\n【可选风格模板 — 参考 assets\u002F】\n根据用户内容选择最贴合的一种, 不要三种混用:\n- `assets\u002Fwar-room-grid.html`: 默认风格。浅色战情室 \u002F 咨询报告, 适合产品团队、PM、普通商业读者。\n- `assets\u002Fradar-map.html`: 深色雷达图 \u002F market intelligence console, 适合安全、AI、开发者工具、平台型竞品。\n- `assets\u002Fanalyst-dossier.html`: 纸质分析档案 \u002F investment research dossier, 适合投研、行业分析、正式战略备忘。\n\n如果用户没有指定风格, 优先使用 `war-room-grid`; 如果输入强调市场格局、技术雷达、攻防态势, 使用 `radar-map`; 如果输入像研究笔记、投资备忘或行业报告, 使用 `analyst-dossier`。\n\n【内容真实性】\n- 只使用用户提供的竞品、价格、功能、评论。缺失信息用 \"not found in source\" 或 \"unknown\" 标注。\n- 不要发明市场份额、ARR、客户名、定价数字。\n- 如果用户资料明显不足, 仍然输出报告, 但在 \"Evidence gaps\" 中列出缺口。\n","【模板: 竞品拆解 \u002F Competitive Teardown】\n【意图】这不是文章、不是 PRD、不是 pitch deck。目标是把多个竞品的杂乱资料转成一份可决策的产品战略报告, 帮团队回答: \"我们和它们到底差在哪里, 下一步该怎么打?\"\n\n【适合输入】\n- 竞品官网 \u002F 定价页 \u002F changelog \u002F 用户评论 \u002F 销售反馈 \u002F 内部调研笔记\n- 2-6 个竞品最合适; 如果用户只给一个竞品, 输出单竞品 deep dive\n- 可以包含表格、bullet、链接摘录、访谈记录、截图说明\n\n【必须输出的结构】\n1. Header: 市场 \u002F 产品类别 \u002F 报告日期 \u002F 结论一句话。\n2. Executive takeaway: 3 条最重要判断, 每条必须包含 \"so what\"。\n3. Positioning map: 用 2×2 象限或坐标图表现竞品定位。坐标轴必须来自用户内容, 不要套模板词。\n4. Competitor cards: 每个竞品一张卡, 包含 target user、core promise、pricing signal、primary strength、visible weakness。\n5. Feature matrix: 行是关键能力, 列是竞品 + \"Us \u002F Opportunity\"; 用 ✓ \u002F △ \u002F — 表达覆盖度, 并用短注释说明。\n6. Pricing \u002F packaging read: 价格层级、免费试用、限制项、企业销售动作。\n7. UX \u002F messaging notes: 从用户材料中抽取 4-6 条可观察细节, 不要泛泛而谈。\n8. Opportunity windows: 3 个机会窗口, 每个包含 why now、target segment、first move、risk。\n9. Recommended moves: 近期 30 天 \u002F 90 天 \u002F 180 天行动建议。\n\n【设计要求】\n- 战略咨询 + 产品战情室风格: 信息密度高、扫描快、图表清楚。\n- 使用 restrained palette: ink \u002F paper \u002F muted blue \u002F signal amber 或类似专业色。\n- Feature matrix 必须横向可读; 小屏可变成 stacked cards。\n- 不要做成营销落地页, 不要做成普通文章。\n\n【可选风格模板 — 参考 assets\u002F】\n根据用户内容选择最贴合的一种, 不要三种混用:\n- `assets\u002Fwar-room-grid.html`: 默认风格。浅色战情室 \u002F 咨询报告, 适合产品团队、PM、普通商业读者。\n- `assets\u002Fradar-map.html`: 深色雷达图 \u002F market intelligence console, 适合安全、AI、开发者工具、平台型竞品。\n- `assets\u002Fanalyst-dossier.html`: 纸质分析档案 \u002F investment research dossier, 适合投研、行业分析、正式战略备忘。\n\n如果用户没有指定风格, 优先使用 `war-room-grid`; 如果输入强调市场格局、技术雷达、攻防态势, 使用 `radar-map`; 如果输入像研究笔记、投资备忘或行业报告, 使用 `analyst-dossier`。\n\n【内容真实性】\n- 只使用用户提供的竞品、价格、功能、评论。缺失信息用 \"not found in source\" 或 \"unknown\" 标注。\n- 不要发明市场份额、ARR、客户名、定价数字。\n- 如果用户资料明显不足, 仍然输出报告, 但在 \"Evidence gaps\" 中列出缺口。\n",{"name":5,"tags":24,"emoji":31,"en_name":32,"zh_name":33,"category":34,"featured":35,"scenario":28,"example_id":36,"aspect_hint":37,"description":7,"example_desc":38,"example_name":39,"example_format":40,"example_tagline":41},[25,26,27,28,29,30],"competitive","teardown","strategy","product","竞品","拆解","🧩","Competitive Teardown","竞品拆解","doc",8,"sample-competitive-teardown","战略长页面","把三家竞品的定位、价格、功能、评价转成产品团队可行动的拆解报告。","竞品拆解 · AI Meeting Assistants","markdown","比较矩阵 + 定位象限 + 我们的应对","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa","tools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown",1,"https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI","https:\u002F\u002Fyana.vutam.link\u002F","https:\u002F\u002Fgithub.com\u002FHoronomos-laps","https:\u002F\u002Fyana.vutam.link","An open-source governed runtime & execution environment for multi-agent AI systems.","2026-11-11 23:56:26",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill competitive-teardown",{"tool":58,"command":59},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill competitive-teardown",{"tool":61,"command":62},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill competitive-teardown","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Ftools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown\u002FSKILL.md",true,[66,72,76,80,85],{"path":67,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":70,"sourceHtmlUrl":71},"assets\u002Fanalyst-dossier.html","ASSET","资产文件",3795,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Ftools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown\u002Fassets\u002Fanalyst-dossier.html",{"path":73,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":74,"sourceHtmlUrl":75},"assets\u002Fradar-map.html",5133,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Ftools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown\u002Fassets\u002Fradar-map.html",{"path":77,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":78,"sourceHtmlUrl":79},"assets\u002Fwar-room-grid.html",7227,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Ftools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown\u002Fassets\u002Fwar-room-grid.html",{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":78,"sourceHtmlUrl":84},"example.html","REFERENCE","参考文档","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Ftools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown\u002Fexample.html",{"path":86,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":87,"sourceHtmlUrl":88},"example.md",2055,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Ftools\u002Fyana-web\u002Fhtml-skills\u002Fcompetitive-teardown\u002Fexample.md",[90,98,105,113,121,129],{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":94,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":19},"01M735GKET5YVYKAY62W2P5YXB","openai--sentry--sentry","Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.","MIT","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fopenai--sentry--sentry\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},"01M73DCAP83T17HY7SMGK7MGFE","ito-basket-compare","Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis. Use for read-only basket comparison and gap analysis without investment advice or live trading.","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fito-basket-compare\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":109,"sourceHtmlUrl":110,"categories":111,"keywords":112,"publishedAt":19},"01M734CYEMZFDR3KH6SW0JP8TD","implementing-network-traffic-baselining","Build network traffic baselines from NetFlow\u002FIPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly\u002Fdaily traffic pattern profiling","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FSKILL.md",[],[],{"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":117,"sourceHtmlUrl":118,"categories":119,"keywords":120,"publishedAt":19},"01M73ASZ6NJRJM44Z2P84NGQ3Q","detecting-evasion-techniques-in-endpoint-logs","Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FSKILL.md",[],[],{"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":125,"sourceHtmlUrl":126,"categories":127,"keywords":128,"publishedAt":19},"01M734AFNXD06Z78QRK0VKGT7Q","implementing-microsegmentation-with-guardicore","Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FSKILL.md",[],[],{"skillNo":130,"name":131,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":132,"categories":133,"keywords":134,"publishedAt":19},"01M736TK27QMCXK0DVCH25SJN5","ramdisk-tmpfs-patterns","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Framdisk-tmpfs-patterns\u002FSKILL.md",[],[]]