[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7182PBYMCXTJQVM760CCEAB":3,"skill-same:01M7182PBYMCXTJQVM760CCEAB":77},{"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":57,"commitSha":58,"skillDirectory":59,"forksCount":14,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":62,"install":63,"resources":76},"01M7182PBYMCXTJQVM760CCEAB","bdistill-behavioral-xray",null,"X-ray any AI model's behavioral patterns — refusal boundaries, hallucination tendencies, reasoning style, formatting defaults. No API key needed.","sapsapshen\u002Fai-memory-router","sapsapshen","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F20347959?v=4","01M6XDQEF1DP50DKF37H81J3J5","shenmian","01M6XDQEJPE41Y3DT2763X8ZJN",0,"MIT","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fglobal\u002Fbdistill-behavioral-xray\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"xray","bdistill behavioral xray","behavioral","team","ai-testing","style","model-evaluation","community","cursor","model","testing","api","analysis","Ray","behavioral-analysis","compliance","red-team","copilot","codex","MCP","2026-11-10 10:12:30",false,"---\nname: bdistill-behavioral-xray\ndescription: \"X-ray any AI model's behavioral patterns — refusal boundaries, hallucination tendencies, reasoning style, formatting defaults. No API key needed.\"\ncategory: ai-testing\nrisk: safe\nsource: community\ndate_added: \"2026-03-20\"\nauthor: FrancyJGLisboa\ntags: [ai, testing, behavioral-analysis, model-evaluation, red-team, compliance, mcp]\ntools: [claude, cursor, codex, copilot]\n---\n\n# Behavioral X-Ray\n\nSystematically probe an AI model's behavioral patterns and generate a visual report. The AI agent probes *itself* — no API key or external setup needed.\n\n## Overview\n\nbdistill's Behavioral X-Ray runs 30 carefully designed probe questions across 6 dimensions, auto-tags each response with behavioral metadata, and compiles results into a styled HTML report with radar charts and actionable insights.\n\nUse it to understand your model before building with it, compare models for task selection, or track behavioral drift over time.\n\n## When to Use This Skill\n\n- Use when you want to understand how your AI model actually behaves (not how it claims to)\n- Use when choosing between models for a specific task\n- Use when debugging unexpected refusals, hallucinations, or formatting issues\n- Use for compliance auditing — documenting model behavior at deployment boundaries\n- Use for red team assessments — systematic boundary mapping across safety dimensions\n\n## How It Works\n\n### Step 1: Install\n\n```bash\npip install bdistill\nclaude mcp add bdistill -- bdistill-mcp   # Claude Code\n```\n\nFor other tools, add bdistill-mcp as an MCP server in your project config.\n\n### Step 2: Run the probe\n\nIn Claude Code:\n```\n\u002Fxray                          # Full behavioral probe (30 questions)\n\u002Fxray --dimensions refusal     # Probe just one dimension\n\u002Fxray-report                   # Generate report from completed probe\n```\n\nIn any tool with MCP:\n```\n\"X-ray your behavioral patterns\"\n\"Test your refusal boundaries\"\n\"Generate a behavioral report\"\n```\n\n## Probe Dimensions\n\n| Dimension | What it measures |\n|-----------|-----------------|\n| **tool_use** | When does it call tools vs. answer from knowledge? |\n| **refusal** | Where does it draw safety boundaries? Does it over-refuse? |\n| **formatting** | Lists vs. prose? Code blocks? Length calibration? |\n| **reasoning** | Does it show chain-of-thought? Handle trick questions? |\n| **persona** | Identity, tone matching, composure under hostility |\n| **grounding** | Hallucination resistance, fabrication traps, knowledge limits |\n\n## Output\n\nA styled HTML report showing:\n- Refusal rate, hedge rate, chain-of-thought usage\n- Per-dimension breakdown with bar charts\n- Notable response examples with behavioral tags\n- Actionable insights (e.g., \"you already show CoT 85% of the time, no need to prompt for it\")\n\n## Best Practices\n\n- Answer probe questions honestly — the value is in authentic behavioral data\n- Run probes on the same model periodically to track behavioral drift\n- Compare reports across models to make informed selection decisions\n- Use adversarial knowledge extraction (`\u002Fdistill --adversarial`) alongside behavioral probes for complete model profiling\n\n## Related Skills\n\n- `@bdistill-knowledge-extraction` - Extract structured domain knowledge from any AI model\n","# Behavioral X-Ray\n\nSystematically probe an AI model's behavioral patterns and generate a visual report. The AI agent probes *itself* — no API key or external setup needed.\n\n## Overview\n\nbdistill's Behavioral X-Ray runs 30 carefully designed probe questions across 6 dimensions, auto-tags each response with behavioral metadata, and compiles results into a styled HTML report with radar charts and actionable insights.\n\nUse it to understand your model before building with it, compare models for task selection, or track behavioral drift over time.\n\n## When to Use This Skill\n\n- Use when you want to understand how your AI model actually behaves (not how it claims to)\n- Use when choosing between models for a specific task\n- Use when debugging unexpected refusals, hallucinations, or formatting issues\n- Use for compliance auditing — documenting model behavior at deployment boundaries\n- Use for red team assessments — systematic boundary mapping across safety dimensions\n\n## How It Works\n\n### Step 1: Install\n\n```bash\npip install bdistill\nclaude mcp add bdistill -- bdistill-mcp   # Claude Code\n```\n\nFor other tools, add bdistill-mcp as an MCP server in your project config.\n\n### Step 2: Run the probe\n\nIn Claude Code:\n```\n\u002Fxray                          # Full behavioral probe (30 questions)\n\u002Fxray --dimensions refusal     # Probe just one dimension\n\u002Fxray-report                   # Generate report from completed probe\n```\n\nIn any tool with MCP:\n```\n\"X-ray your behavioral patterns\"\n\"Test your refusal boundaries\"\n\"Generate a behavioral report\"\n```\n\n## Probe Dimensions\n\n| Dimension | What it measures |\n|-----------|-----------------|\n| **tool_use** | When does it call tools vs. answer from knowledge? |\n| **refusal** | Where does it draw safety boundaries? Does it over-refuse? |\n| **formatting** | Lists vs. prose? Code blocks? Length calibration? |\n| **reasoning** | Does it show chain-of-thought? Handle trick questions? |\n| **persona** | Identity, tone matching, composure under hostility |\n| **grounding** | Hallucination resistance, fabrication traps, knowledge limits |\n\n## Output\n\nA styled HTML report showing:\n- Refusal rate, hedge rate, chain-of-thought usage\n- Per-dimension breakdown with bar charts\n- Notable response examples with behavioral tags\n- Actionable insights (e.g., \"you already show CoT 85% of the time, no need to prompt for it\")\n\n## Best Practices\n\n- Answer probe questions honestly — the value is in authentic behavioral data\n- Run probes on the same model periodically to track behavioral drift\n- Compare reports across models to make informed selection decisions\n- Use adversarial knowledge extraction (`\u002Fdistill --adversarial`) alongside behavioral probes for complete model profiling\n\n## Related Skills\n\n- `@bdistill-knowledge-extraction` - Extract structured domain knowledge from any AI model\n",{"name":5,"risk":49,"tags":50,"tools":53,"author":55,"source":31,"category":28,"date_added":56,"description":7},"safe",[51,34,38,30,40,39,52],"ai","mcp",[54,32,42,41],"claude","FrancyJGLisboa","2026-03-20","main","7a38d8e7073e61c16eda85681cb32fb68a8657a5","skills-store\u002Fglobal\u002Fbdistill-behavioral-xray","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router","https:\u002F\u002Fgithub.com\u002Fsapsapshen","2026-04-14 21:12:12",{"source":8,"skillName":5,"commands":64,"prompt":74,"zipAvailable":75},[65,68,71],{"tool":66,"command":67},"npx","npx skills add sapsapshen\u002Fai-memory-router --skill bdistill-behavioral-xray",{"tool":69,"command":70},"bunx","bunx skills add sapsapshen\u002Fai-memory-router --skill bdistill-behavioral-xray",{"tool":72,"command":73},"pnpm","pnpm dlx skills add sapsapshen\u002Fai-memory-router --skill bdistill-behavioral-xray","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fglobal\u002Fbdistill-behavioral-xray\u002FSKILL.md",true,[],[78,101,126,136,149,166],{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":89,"publishedAt":44},"01M71ATQRKG48SH06FQ697T5G9","wechat-search","Search WeChat Official Account articles using OpenClaw's web search and fetch capabilities with compliance-focused design.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fwechat-search-release\u002FSKILL.md",[84],{"categoryNo":85,"categoryName":86,"taxonomyType":87,"taxonomyTypeDesc":88},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[90,91,92,93,94,95,96,39,97,98,99,100],"wechat search","wechat","search","capabilities","openclaw","design","web search","web","official","fetch","with",{"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":107,"publishedAt":44},"01M71ATNAVGZB35PFYM2GC5N00","trend-tap","Real-time trending topics aggregator across 7 platforms (X\u002FTwitter, Reddit, Google Trends, Hacker News, Zhihu, Bilibili, Weibo). 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