[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AE1J6ES71611CVDP2MAQ8E":3,"skill-same:01M6AE1J6ES71611CVDP2MAQ8E":87},{"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":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":54,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6AE1J6ES71611CVDP2MAQ8E","qdrant-monitoring-debugging",null,"Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.","github\u002Fawesome-copilot","github","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","01M6AC83DS133TPXFSP1DHNCC6","GitHub","01M6AD3PBDYPK7NVFJNJ66Y8RS",41046,"MIT","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fqdrant-monitoring\u002Fdebugging\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"debugging","monitoring","Qdrant","qdrant monitoring","qdrant monitoring debugging","Production","when","changes","now","oom","latency","indexing","optimizer","queries","reports","use","spike","fast","search","observability","metrics","issues","config","performance","memory","2026-11-10 10:12:30",false,"---\nname: qdrant-monitoring-debugging\ndescription: \"Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.\"\n---\n\n# How to Debug Qdrant with Metrics\n\nFirst check optimizer status. Most production issues trace back to active optimizations competing for resources. If optimizer is clean, check memory, then request metrics.\n\n\n## Optimizer Stuck or Too Slow\n\nUse when: optimizer running for hours, not finishing, or showing errors.\n\n- Use `\u002Fcollections\u002F{collection_name}\u002Foptimizations` endpoint (v1.17+) to check status [Optimization monitoring](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Foptimizer\u002F?s=optimization-monitoring)\n- Query with optional detail flags: `?with=queued,completed,idle_segments`\n- Returns: queued optimizations count, active optimizer type, involved segments, progress tracking\n- Web UI has an Optimizations tab with timeline view and per-task duration metrics [Web UI](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Foptimizer\u002F?s=web-ui)\n- If `optimizer_status` shows an error in collection info, check logs for disk full or corrupted segments\n- Large merges and HNSW rebuilds legitimately take hours on big datasets. Check progress before assuming it's stuck.\n\n\n## Memory Seems Too High\n\nUse when: memory exceeds expectations, node crashes with OOM, or memory keeps growing.\n\n- Process memory metrics available via `\u002Fmetrics` (RSS, allocated bytes, page faults)\n- Qdrant uses two types of RAM: resident memory (data structures, quantized vectors) and OS page cache (cached disk reads). Page cache filling available RAM is normal. [Memory article](https:\u002F\u002Fqdrant.tech\u002Farticles\u002Fmemory-consumption\u002F)\n- If resident memory (RSSAnon) exceeds 80% of total RAM, investigate\n- Check `\u002Ftelemetry` for per-collection breakdown of point counts and vector configurations\n- Estimate expected memory: `num_vectors * dimensions * 4 bytes * 1.5` for vectors, plus payload and index overhead [Capacity planning](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Fcapacity-planning\u002F)\n- Common causes of unexpected growth: quantized vectors with `always_ram=true`, too many payload indexes, large `max_segment_size` during optimization\n\n\n## Queries Are Slow\n\nUse when: queries slower than expected and you need to identify the cause.\n\n- Track `rest_responses_avg_duration_seconds` and `rest_responses_max_duration_seconds` per endpoint\n- Use histogram metric `rest_responses_duration_seconds` (v1.8+) for percentile analysis in Grafana\n- Equivalent gRPC metrics with `grpc_responses_` prefix\n- Check optimizer status first. Active optimizations compete for CPU and I\u002FO, degrading search latency.\n- Check segment count via collection info. Too many unmerged segments after bulk upload causes slower search.\n- Compare filtered vs unfiltered query times. Large gap means missing payload index. [Payload index](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Findexing\u002F?s=payload-index)\n\n\n## What NOT to Do\n\n- Ignore optimizer status when debugging slow queries (most common root cause)\n- Assume memory leak when page cache fills RAM (normal OS behavior)\n- Make config changes while optimizer is running (causes cascading re-optimizations)\n- Blame Qdrant before checking if bulk upload just finished (unmerged segments)\n","# How to Debug Qdrant with Metrics\n\nFirst check optimizer status. Most production issues trace back to active optimizations competing for resources. If optimizer is clean, check memory, then request metrics.\n\n\n## Optimizer Stuck or Too Slow\n\nUse when: optimizer running for hours, not finishing, or showing errors.\n\n- Use `\u002Fcollections\u002F{collection_name}\u002Foptimizations` endpoint (v1.17+) to check status [Optimization monitoring](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Foptimizer\u002F?s=optimization-monitoring)\n- Query with optional detail flags: `?with=queued,completed,idle_segments`\n- Returns: queued optimizations count, active optimizer type, involved segments, progress tracking\n- Web UI has an Optimizations tab with timeline view and per-task duration metrics [Web UI](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Foptimizer\u002F?s=web-ui)\n- If `optimizer_status` shows an error in collection info, check logs for disk full or corrupted segments\n- Large merges and HNSW rebuilds legitimately take hours on big datasets. Check progress before assuming it's stuck.\n\n\n## Memory Seems Too High\n\nUse when: memory exceeds expectations, node crashes with OOM, or memory keeps growing.\n\n- Process memory metrics available via `\u002Fmetrics` (RSS, allocated bytes, page faults)\n- Qdrant uses two types of RAM: resident memory (data structures, quantized vectors) and OS page cache (cached disk reads). Page cache filling available RAM is normal. [Memory article](https:\u002F\u002Fqdrant.tech\u002Farticles\u002Fmemory-consumption\u002F)\n- If resident memory (RSSAnon) exceeds 80% of total RAM, investigate\n- Check `\u002Ftelemetry` for per-collection breakdown of point counts and vector configurations\n- Estimate expected memory: `num_vectors * dimensions * 4 bytes * 1.5` for vectors, plus payload and index overhead [Capacity planning](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Foperations\u002Fcapacity-planning\u002F)\n- Common causes of unexpected growth: quantized vectors with `always_ram=true`, too many payload indexes, large `max_segment_size` during optimization\n\n\n## Queries Are Slow\n\nUse when: queries slower than expected and you need to identify the cause.\n\n- Track `rest_responses_avg_duration_seconds` and `rest_responses_max_duration_seconds` per endpoint\n- Use histogram metric `rest_responses_duration_seconds` (v1.8+) for percentile analysis in Grafana\n- Equivalent gRPC metrics with `grpc_responses_` prefix\n- Check optimizer status first. Active optimizations compete for CPU and I\u002FO, degrading search latency.\n- Check segment count via collection info. Too many unmerged segments after bulk upload causes slower search.\n- Compare filtered vs unfiltered query times. Large gap means missing payload index. [Payload index](https:\u002F\u002Fsearch.qdrant.tech\u002Fmd\u002Fdocumentation\u002Fmanage-data\u002Findexing\u002F?s=payload-index)\n\n\n## What NOT to Do\n\n- Ignore optimizer status when debugging slow queries (most common root cause)\n- Assume memory leak when page cache fills RAM (normal OS behavior)\n- Make config changes while optimizer is running (causes cascading re-optimizations)\n- Blame Qdrant before checking if bulk upload just finished (unmerged segments)\n",{"name":5,"description":7},"main","5269f7ea2d6c3a9bfda5ed878b6726cf509121fd","skills\u002Fqdrant-monitoring\u002Fdebugging",5340,"https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot","https:\u002F\u002Fawesome-copilot.github.com\u002F","https:\u002F\u002Fgithub.com\u002Fgithub","https:\u002F\u002Fgithub.com\u002Fabout","How people build software.","2026-11-11 13:41:32",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add github\u002Fawesome-copilot --skill qdrant-monitoring-debugging",{"tool":65,"command":66},"bunx","bunx skills add github\u002Fawesome-copilot --skill qdrant-monitoring-debugging",{"tool":68,"command":69},"pnpm","pnpm dlx skills add github\u002Fawesome-copilot --skill qdrant-monitoring-debugging","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fqdrant-monitoring\u002Fdebugging\u002FSKILL.md",true,[73,79,83],{"path":74,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":77,"sourceHtmlUrl":78},"agents\u002Fopenai.yaml","REFERENCE","参考文档",87,"https:\u002F\u002Fgithub.com\u002FVortex375\u002Fseraph\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ftdd\u002Fagents\u002Fopenai.yaml",{"path":80,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":81,"sourceHtmlUrl":82},"mocking.md",1481,"https:\u002F\u002Fgithub.com\u002FVortex375\u002Fseraph\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ftdd\u002Fmocking.md",{"path":84,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":85,"sourceHtmlUrl":86},"tests.md",2214,"https:\u002F\u002Fgithub.com\u002FVortex375\u002Fseraph\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Ftdd\u002Ftests.md",[88,121,149,178,211,228],{"skillNo":89,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":102,"publishedAt":44},"01M70KXZNX9ES38N2A8M58ZZMZ","supabase-rls-policies","Write, review, and test Supabase Row Level Security (RLS) policies so that one user cannot read or change another user's rows. Use when creating or changing tables, policies, views, or security definer functions in a Supabase project, when reviewing a migration that touches RLS, or when asked to prove user isolation with pgTAP tests that sign in as two users.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fsupabase-rls-policies\u002FSKILL.md",[94,99],{"categoryNo":95,"categoryName":96,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":100,"categoryName":101,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000023","Skill与智能体开发",[103,104,105,106,107,25,108,109,110,111,112,113,114,115,116,117,34,118,119,120],"supabase","rls","supabase rls","supabase rls policies","project","review","change","read","write","security","isolation","tables","as","tests","prove","users","functions","with",{"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":128,"publishedAt":44},"01M70KWA5YWXDV6V8DZ19E3T2Y","skill-distribution-audit","Audit a skill collection before release or investigate installer omissions, archived\u002Ftemplate leakage, duplicate identities, and manifest drift. Reconcile the intended public source set, distribution manifest, and actual discovery output for a specified consumer version. Includes a deterministic set-comparison helper.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fskill-distribution-audit\u002FSKILL.md",[127],{"categoryNo":100,"categoryName":101,"taxonomyType":97,"taxonomyTypeDesc":98},[129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148],"distribution","skill distribution audit","audit","SET","deterministic","installer","for","discovery","comparison","helper","manifest","version","collection","drift","output","investigate","duplicate","template","release","reconcile",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":153,"sourceHtmlUrl":154,"categories":155,"keywords":161,"publishedAt":44},"01M70KCJPFVW7PPQ49CC5R8JGK","logicapps-custom-code-net10-migration","Migrate Azure Logic Apps Standard local-function custom-code projects from .NET 8 to .NET 10. Use for legacy Logic Apps custom-code workspace upgrades, project\u002Fpackage configuration, custom-worker settings, publication, and integrated VS Code debugging. Not for ordinary .NET applications, standalone Azure Functions, Consumption workflows, or cloud deployment.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FSKILL.md",[156],{"categoryNo":157,"categoryName":158,"taxonomyType":159,"taxonomyTypeDesc":160},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[162,163,164,165,166,167,135,107,168,169,170,171,172,173,174,34,175,176,19,177],"custom","code","logicapps custom code net10 migration","migration","projects","standalone","deployment","applications","local","azure","worker","upgrades","package","apps","Legacy","workflows",{"skillNo":179,"name":180,"nameZh":6,"description":181,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":182,"sourceHtmlUrl":183,"categories":184,"keywords":189,"publishedAt":44},"01M6AEBN37RQMXJ3298PEY7PG1","winmd-api-search","Find and explore Windows desktop APIs. Use when building features that need platform capabilities — camera, file access, notifications, UI controls, AI\u002FML, sensors, networking, etc. Discovers the right API for a task and retrieves full type details (methods, properties, events, enumeration values).","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FSKILL.md",[185,188],{"categoryNo":186,"categoryName":187,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":157,"categoryName":158,"taxonomyType":159,"taxonomyTypeDesc":160},[190,37,191,192,193,194,195,196,197,198,199,200,201,202,203,25,204,205,206,207,208,135,209,210],"winmd api search","api","windows","desktop","file access","enumeration","ui","ml","file","networking","capabilities","notifications","explore","access","features","full","camera","events","platform","methods","controls",{"skillNo":212,"name":213,"nameZh":6,"description":214,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":215,"licenseFileUrl":216,"sourceHtmlUrl":217,"categories":218,"keywords":224,"publishedAt":44},"01M6AE571R3SC1ZGE202B3NB5S","resemble-detect","Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using Resemble AI","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FSKILL.md",[219,220,223],{"categoryNo":186,"categoryName":187,"taxonomyType":97,"taxonomyTypeDesc":98},{"categoryNo":221,"categoryName":222,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":100,"categoryName":101,"taxonomyType":97,"taxonomyTypeDesc":98},[225,132,198,226,227],"resemble detect","https","identity",{"skillNo":229,"name":230,"nameZh":6,"description":231,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":215,"licenseFileUrl":232,"sourceHtmlUrl":233,"categories":234,"keywords":239,"publishedAt":44},"01M6AE30BSK2HCY4TQQ22Z8JRD","quality-playbook","Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch. Works with any language. Trigger on 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', or 'coverage theater'.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FSKILL.md",[235,238],{"categoryNo":236,"categoryName":237,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":100,"categoryName":101,"taxonomyType":97,"taxonomyTypeDesc":98},[240,241,242,243,163,108,9,131,244,245,226,246,247,248,249,250,251,252,253,254,255,256,116,257,258,259,260],"playbook","quality playbook","quality","code review","tdd","run","report","spec","bug report","council","engineering","functional","spec audit","bug","verified","multi-model","three","coverage","model","regression","structural"]