[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6RADBH5PB8JFB6N7PXM4V8B":3,"skill-same:01M6RADBH5PB8JFB6N7PXM4V8B":75},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":47,"repositoryHtmlUrl":48,"repositoryHomepageUrl":6,"ownerHtmlUrl":49,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":50,"install":51,"resources":64},"01M6RADBH5PB8JFB6N7PXM4V8B","audit-vision-config",null,"Audit YAML, model paths, OpenVINO device selection, camera and serial settings, and camera\u002Fgimbal calibration values for this repository. Use when parameters appear ignored, deployment differs between machines, or pose and model behavior are suspicious.","HNUST-Dust\u002FDust_infantry_vision","HNUST-Dust","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F242605597?v=4","01M6RAD8QP9GXRZWD7WEN7KXWZ","01M6RAD8XNF76XNGYHDPX4AV12",5,"MIT","https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Faudit-vision-config\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"config","audit vision config","vision","audit","selection","ignored","suspicious","when","pose","calibration","for","values","paths","camera","deployment","use","settings","behavior","model","repository","yaml","2026-11-10 10:12:30",false,"---\nname: audit-vision-config\ndescription: Audit YAML, model paths, OpenVINO device selection, camera and serial settings, and camera\u002Fgimbal calibration values for this repository. Use when parameters appear ignored, deployment differs between machines, or pose and model behavior are suspicious.\n---\n\n# Audit Vision Config\n\nUse this skill before changing a threshold, model, device, or calibration number. Report facts and mismatches; do not silently rewrite the user's config.\n\n## Workflow\n\n1. Identify the exact YAML file and the executable that consumes it. Run from the repository root because model and demo paths are relative.\n2. Compare the YAML against the actual reads in code, not just the README. Search `tools::read`, `yaml[`, and `tools::load` in the relevant module.\n3. Check file existence and compatibility for `classify_model` and `yolov5_model_path`; ensure `detector_name` selects the intended detector and `device` is available.\n4. Validate camera fields (`camera_name`, `vid_pid`, exposure, gain\u002Fgamma, frame rate) and gimbal fields (`com_port`, optional CRC setting) without opening hardware. Hand hardware failures to `$diagnose-camera-stack` or `$diagnose-gimbal-link`.\n5. Validate calibration structure and units: 3x3 `camera_matrix`, distortion vector, 3x3 rotations, 3-vector translation, and consistent coordinate\u002Fframe conventions. Check rotation orthonormality and determinant near `+1`; flag implausible values rather than auto-correcting them.\n6. Check that OpenVINO lookup paths are consistent in root `CMakeLists.txt`, `tasks\u002Fauto_aim\u002FCMakeLists.txt`, and `tasks\u002Fomniperception\u002FCMakeLists.txt`.\n7. Produce a report with `missing`, `unused`, `conditionally required`, and `suspicious value` categories. A syntactically valid YAML file is not a valid deployment configuration.\n\n## Boundaries\n\n- Never overwrite `configs\u002Fstandard3.yaml` or calibration values during an audit.\n- Use a copied temporary config for CPU fallback or an experiment, and identify every changed key.\n- Do not call a calibration result correct solely because reprojection runs; preserve the measured error and coordinate-frame assumptions.\n\nRead [config-map.md](references\u002Fconfig-map.md) for project-specific keys and checks.\n","# Audit Vision Config\n\nUse this skill before changing a threshold, model, device, or calibration number. Report facts and mismatches; do not silently rewrite the user's config.\n\n## Workflow\n\n1. Identify the exact YAML file and the executable that consumes it. Run from the repository root because model and demo paths are relative.\n2. Compare the YAML against the actual reads in code, not just the README. Search `tools::read`, `yaml[`, and `tools::load` in the relevant module.\n3. Check file existence and compatibility for `classify_model` and `yolov5_model_path`; ensure `detector_name` selects the intended detector and `device` is available.\n4. Validate camera fields (`camera_name`, `vid_pid`, exposure, gain\u002Fgamma, frame rate) and gimbal fields (`com_port`, optional CRC setting) without opening hardware. Hand hardware failures to `$diagnose-camera-stack` or `$diagnose-gimbal-link`.\n5. Validate calibration structure and units: 3x3 `camera_matrix`, distortion vector, 3x3 rotations, 3-vector translation, and consistent coordinate\u002Fframe conventions. Check rotation orthonormality and determinant near `+1`; flag implausible values rather than auto-correcting them.\n6. Check that OpenVINO lookup paths are consistent in root `CMakeLists.txt`, `tasks\u002Fauto_aim\u002FCMakeLists.txt`, and `tasks\u002Fomniperception\u002FCMakeLists.txt`.\n7. Produce a report with `missing`, `unused`, `conditionally required`, and `suspicious value` categories. A syntactically valid YAML file is not a valid deployment configuration.\n\n## Boundaries\n\n- Never overwrite `configs\u002Fstandard3.yaml` or calibration values during an audit.\n- Use a copied temporary config for CPU fallback or an experiment, and identify every changed key.\n- Do not call a calibration result correct solely because reprojection runs; preserve the measured error and coordinate-frame assumptions.\n\nRead [config-map.md](references\u002Fconfig-map.md) for project-specific keys and checks.\n",{"name":5,"description":7},"main","1ce4eeca9e26627f8e445d56f5abf69f372eb3dd",".codex\u002Fskills\u002Faudit-vision-config",1,"https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision","https:\u002F\u002Fgithub.com\u002FHNUST-Dust","2026-11-12 13:36:09",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add HNUST-Dust\u002FDust_infantry_vision --skill audit-vision-config",{"tool":57,"command":58},"bunx","bunx skills add HNUST-Dust\u002FDust_infantry_vision --skill audit-vision-config",{"tool":60,"command":61},"pnpm","pnpm dlx skills add HNUST-Dust\u002FDust_infantry_vision --skill audit-vision-config","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Faudit-vision-config\u002FSKILL.md",true,[65,71],{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"agents\u002Fopenai.yaml","REFERENCE","参考文档",253,"https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Faudit-vision-config\u002Fagents\u002Fopenai.yaml",{"path":72,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":73,"sourceHtmlUrl":74},"references\u002Fconfig-map.md",1751,"https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Faudit-vision-config\u002Freferences\u002Fconfig-map.md",[76,100,127,145,163,179],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":39},"01M6RAEVD39W5QTD1BTNMR8XK3","replay-auto-aim","Reproduce and isolate auto-aim detection, tracking, solving, aiming, and planning issues from recorded video in this repository. Use for false positives, missed armors, tracker state changes, aim jitter, fire decisions, or latency regressions.","https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Freplay-auto-aim\u002FSKILL.md",[],[83,84,85,86,33,87,28,88,89,90,91,92,93,94,95,96,97,37,98,99],"auto","replay","replay auto aim","planning","changes","false","latency","missed","tracker","tracking","decisions","jitter","reproduce","Video","detection","issues","state",{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":111,"publishedAt":39},"01M6RAER0Q716PFNKAPVXX7AVC","improve-codebase-architecture","Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.","https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Fimprove-codebase-architecture\u002FSKILL.md",[106],{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},"01JBSEEDCAT000000000000009","前端开发","SCENARIO","使用场景",[112,113,114,115,116,28,117,118,119,120,121,122,123,124,125,126],"improve codebase architecture","architecture","improve","codebase","deepening","you","as","present","visual","scan","grill","html","pick","html report","report",{"skillNo":128,"name":129,"nameZh":6,"description":130,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":131,"categories":132,"keywords":133,"publishedAt":39},"01M6RAEE88RSKY2HX0WVN67WJN","grill-with-docs","A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.","https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Fgrill-with-docs\u002FSKILL.md",[],[122,134,135,136,137,138,139,140,141,142,143,144,118],"docs","grill with docs","with","which","interview","glossary","adr","sharpen","plan","go","design",{"skillNo":146,"name":147,"nameZh":6,"description":148,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":149,"categories":150,"keywords":151,"publishedAt":39},"01M6RAE7BMHJQJRMP79E5AGTNK","diagnosing-bugs","Diagnosis loop for hard bugs and performance regressions. Use when the user says \"diagnose\"\u002F\"debug this\", or reports something broken\u002Fthrowing\u002Ffailing\u002Fslow.","https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Fdiagnosing-bugs\u002FSKILL.md",[],[152,153,154,155,156,157,158,25,28,159,160,33,161,162],"diagnosing bugs","bugs","diagnose","debug","performance","loop","failing","diagnosis","reports","user","broken",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":169,"publishedAt":39},"01M6RAE1HQRFJ1PQFHK3YX0AKH","diagnose-gimbal-link","Safely diagnose this repository's gimbal serial link, packet framing, CRC, timing, quaternion interpolation, and reconnect behavior. Use for \u002Fdev\u002Fgimbal failures, stale state, CRC errors, dropped packets, or incorrect control data.","https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Fdiagnose-gimbal-link\u002FSKILL.md",[],[154,170,171,172,28,173,174,175,176,33,35,177,37,99,178],"link","diagnose gimbal link","interpolation","errors","timing","control","stale","data","dev",{"skillNo":180,"name":181,"nameZh":6,"description":182,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":183,"categories":184,"keywords":185,"publishedAt":39},"01M6RADMNKPPTZS63V1W0EJG1S","diagnose-camera-stack","Diagnose HikRobot, MindVision, or USB camera discovery, SDK, streaming, frame, and frame-rate failures in this repository. Use when camera initialization fails, frames are empty, FPS is wrong, or exposure\u002Fgain\u002FVID-PID settings look suspect.","https:\u002F\u002Fgithub.com\u002FHNUST-Dust\u002FDust_infantry_vision\u002Fblob\u002Fmain\u002F.codex\u002Fskills\u002Fdiagnose-camera-stack\u002FSKILL.md",[],[186,154,31,187,188,34,33,189,25,190,37,191,192,193,194,195,196,197,198],"diagnose camera stack","stack","discovery","look","streaming","sdk","Wrong","initialization","frame","rate","empty","PID","usb"]