[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6X7YZ5WBGSAB23K0DAARY1N":3,"skill-same:01M6X7YZ5WBGSAB23K0DAARY1N":55},{"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":28,"linkOnly":29,"markdownContent":30,"markdownBody":31,"frontMatter":32,"refName":33,"commitSha":34,"skillDirectory":35,"forksCount":36,"repositoryHtmlUrl":37,"repositoryHomepageUrl":6,"ownerHtmlUrl":38,"ownerBlogUrl":6,"ownerDescription":39,"updatedAt":40,"install":41,"resources":54},"01M6X7YZ5WBGSAB23K0DAARY1N","weakness-detection",null,"Analyzes idea-scoring output to identify the weakest dimensions, root causes of low scores, and probable failure modes if the idea were pursued as-is.","MaxKmet\u002Fidea-validation-agents","MaxKmet","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F19517077?v=4","01M6X7QNAFCSMWXN7FDJS2KFGY","Max Kmet","01M6X7QNEEA69XPH7DCQRS5NJE",510,"MIT","https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Fweakness-detection\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27],"detection","weakness detection","idea","scoring","dimensions","as","output","root","modes","2026-11-10 10:12:30",false,"---\nname: weakness-detection\ndescription: Analyzes idea-scoring output to identify the weakest dimensions, root causes of low scores, and probable failure modes if the idea were pursued as-is.\n---\n\n\u003C!-- version: 0.1.0 | outputs: memory\u002Fideas\u002F\u003Cslug>\u002Fweaknesses.json -->\n\n# Skill: weakness-detection\n\n## Purpose\n\nBefore triggering the pivot engine, understand WHY dimensions are weak. A low distribution score might mean \"no viral loop\" (fixable) or \"fundamentally wrong category for organic growth\" (structural). Surface the root cause, not just the symptom.\n\n## Input\n\n- Idea slug\n- `memory\u002Fideas\u002F\u003Cslug>\u002Fscores.json` (required)\n- All available dimension files in `memory\u002Fideas\u002F\u003Cslug>\u002F`\n\n## Weakness Classification\n\n| Root Cause Type | Description | Fix Type |\n|---|---|---|\n| Structural | Inherent to the idea, can't be pivoted away | Drop or major pivot |\n| Situational | Weak due to user's current constraints | Fixable (more time, budget) |\n| Knowledge gap | Weak because data is missing | Run more research |\n| Addressable | Weak but has a clear fix | Targeted pivot |\n\n## Process\n\n\u003C!-- TODO: Add failure mode library by app category -->\n\u003C!-- TODO: Define threshold for \"weak\" (e.g., dimension score \u003C 40) -->\n\n1. Load scores.json, identify dimensions scoring below threshold.\n2. For each weak dimension, read the source file to understand why.\n3. Classify the root cause (structural \u002F situational \u002F knowledge gap \u002F addressable).\n4. Describe the failure mode if the idea proceeded without fixing this weakness.\n\n## Output\n\nWrite to `memory\u002Fideas\u002F\u003Cslug>\u002Fweaknesses.json`:\n\n```json\n{\n  \"weak_dimensions\": [\n    {\n      \"dimension\": \"\",\n      \"score\": 0,\n      \"root_cause_type\": \"structural | situational | knowledge-gap | addressable\",\n      \"root_cause_description\": \"\",\n      \"failure_mode\": \"\"\n    }\n  ],\n  \"critical_weaknesses\": [],\n  \"addressable_weaknesses\": [],\n  \"overall_weakness_severity\": \"fatal | major | minor\"\n}\n```\n\n## Notes\n\n\u003C!-- TODO: Define \"fatal\" vs \"major\" vs \"minor\" by combination of weak dimensions -->\n","\u003C!-- version: 0.1.0 | outputs: memory\u002Fideas\u002F\u003Cslug>\u002Fweaknesses.json -->\n\n# Skill: weakness-detection\n\n## Purpose\n\nBefore triggering the pivot engine, understand WHY dimensions are weak. A low distribution score might mean \"no viral loop\" (fixable) or \"fundamentally wrong category for organic growth\" (structural). Surface the root cause, not just the symptom.\n\n## Input\n\n- Idea slug\n- `memory\u002Fideas\u002F\u003Cslug>\u002Fscores.json` (required)\n- All available dimension files in `memory\u002Fideas\u002F\u003Cslug>\u002F`\n\n## Weakness Classification\n\n| Root Cause Type | Description | Fix Type |\n|---|---|---|\n| Structural | Inherent to the idea, can't be pivoted away | Drop or major pivot |\n| Situational | Weak due to user's current constraints | Fixable (more time, budget) |\n| Knowledge gap | Weak because data is missing | Run more research |\n| Addressable | Weak but has a clear fix | Targeted pivot |\n\n## Process\n\n\u003C!-- TODO: Add failure mode library by app category -->\n\u003C!-- TODO: Define threshold for \"weak\" (e.g., dimension score \u003C 40) -->\n\n1. Load scores.json, identify dimensions scoring below threshold.\n2. For each weak dimension, read the source file to understand why.\n3. Classify the root cause (structural \u002F situational \u002F knowledge gap \u002F addressable).\n4. Describe the failure mode if the idea proceeded without fixing this weakness.\n\n## Output\n\nWrite to `memory\u002Fideas\u002F\u003Cslug>\u002Fweaknesses.json`:\n\n```json\n{\n  \"weak_dimensions\": [\n    {\n      \"dimension\": \"\",\n      \"score\": 0,\n      \"root_cause_type\": \"structural | situational | knowledge-gap | addressable\",\n      \"root_cause_description\": \"\",\n      \"failure_mode\": \"\"\n    }\n  ],\n  \"critical_weaknesses\": [],\n  \"addressable_weaknesses\": [],\n  \"overall_weakness_severity\": \"fatal | major | minor\"\n}\n```\n\n## Notes\n\n\u003C!-- TODO: Define \"fatal\" vs \"major\" vs \"minor\" by combination of weak dimensions -->\n",{"name":5,"description":7},"main","3a4c800a3022e73e9997533b603c79b60ee7597a","skills\u002Fweakness-detection",58,"https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents","https:\u002F\u002Fgithub.com\u002FMaxKmet","Senior AI Engineer","2026-06-16 23:18:56",{"source":8,"skillName":5,"commands":42,"prompt":52,"zipAvailable":53},[43,46,49],{"tool":44,"command":45},"npx","npx skills add MaxKmet\u002Fidea-validation-agents --skill weakness-detection",{"tool":47,"command":48},"bunx","bunx skills add MaxKmet\u002Fidea-validation-agents --skill weakness-detection",{"tool":50,"command":51},"pnpm","pnpm dlx skills add MaxKmet\u002Fidea-validation-agents --skill weakness-detection","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Fweakness-detection\u002FSKILL.md",true,[],[56,82,101,128,150,169],{"skillNo":57,"name":58,"nameZh":6,"description":59,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":60,"categories":61,"keywords":67,"publishedAt":28},"01M6X7YRHWXGBHBT70ZY1YTCC6","user-segmentation-profiler","Classifies the user into an ICP tier (beginner\u002Fbuilder\u002Fgrowth) based on experience, constraints, and goals. Run once per user session before any workflow.","https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Fuser-segmentation-profiler\u002FSKILL.md",[62],{"categoryNo":63,"categoryName":64,"taxonomyType":65,"taxonomyTypeDesc":66},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[68,69,70,71,72,73,74,75,76,77,78,79,80,81],"segmentation","user","user segmentation","profiler","user segmentation profiler","workflow","beginner","icp","goals","builder","growth","session","constraints","run",{"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":88,"publishedAt":28},"01M6X7YJKM9DRPMEDW22PETKDE","user-background-interviewer","Conducts a deep background interview to understand what types of app ideas this specific user is most likely to succeed with based on their domain knowledge, networks, and skills.","https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Fuser-background-interviewer\u002FSKILL.md",[],[89,90,69,91,92,93,94,95,96,97,98,99,100],"background","user background interviewer","networks","knowledge","with","types","understand","app","deep","ideas","domain","interview",{"skillNo":102,"name":103,"nameZh":6,"description":104,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":112,"publishedAt":28},"01M6X7YEX3NTXGXAY8SQRSK7YG","trend-to-product-mapper","Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.","https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Ftrend-to-product-mapper\u002FSKILL.md",[107],{"categoryNo":108,"categoryName":109,"taxonomyType":110,"taxonomyTypeDesc":111},"01JBSEEDCAT000000000000031","产品经理","PROFESSION","适用职业",[113,114,115,116,117,118,119,120,121,122,96,123,124,125,126,127],"trend","mapper","trend to product mapper","product","maps","topics","extracting","trending","problem","fit","viral","monetization","social","content","social content",{"skillNo":129,"name":130,"nameZh":6,"description":131,"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":28},"01M6X7Y9PJGB5W9Y2RGC7MMC8T","trend-analysis","Analyzes market trends across platforms (TikTok, Reddit, App Store, Google Trends) for a given topic or category. Writes a new file to memory\u002Fmarket_insights\u002F.","https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Ftrend-analysis\u002FSKILL.md",[],[113,135,136,137,138,139,140,141,142,143,96,144,145,146,147,148,149],"trend analysis","analysis","google trends","tiktok","app store","for","insights","store","trends","across","reddit","Market","file","memory","google",{"skillNo":151,"name":152,"nameZh":6,"description":153,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":156,"publishedAt":28},"01M6X7Y5GHKXC295FGVJN4Y93R","tam-sam-som-builder","Estimates TAM, SAM, and realistic SOM for a B2C app idea using triangulated bottom-up methodology anchored to market_insights trend data, competitor revenue proxies, and community size signals. Includes indie capture rate benchmarks and growth-rate adjustments by trend velocity.","https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Ftam-sam-som-builder\u002FSKILL.md",[],[157,77,158,78,96,159,113,160,161,21,162,163,146,164,165,166,167,168,140,141],"sam","tam sam som builder","proxies","signals","velocity","community","benchmarks","up","revenue","data","competitor","rate",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":175,"publishedAt":28},"01M6X7Y2P6FGZWH8GNJMDNZ2E0","retention-predictor","Predicts retention potential by evaluating usage frequency, habit formation mechanics, and churn risk factors for a B2C app idea.","https:\u002F\u002Fgithub.com\u002FMaxKmet\u002Fidea-validation-agents\u002Fblob\u002Fmain\u002Fskills\u002Fretention-predictor\u002FSKILL.md",[],[176,177,178,140,179,180,96,181,21,182,183],"retention predictor","retention","churn risk","usage","churn","mechanics","habit","risk"]