[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6E1KCHMS8D5WPBF4JS4YFKA":3,"skill-same:01M6E1KCHMS8D5WPBF4JS4YFKA":83},{"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":26,"publishedAt":50,"linkOnly":51,"markdownContent":52,"markdownBody":53,"frontMatter":54,"refName":59,"commitSha":60,"skillDirectory":61,"forksCount":62,"repositoryHtmlUrl":63,"repositoryHomepageUrl":64,"ownerHtmlUrl":65,"ownerBlogUrl":66,"ownerDescription":67,"updatedAt":68,"install":69,"resources":82},"01M6E1KCHMS8D5WPBF4JS4YFKA","flux-health",null,"Data quality and pipeline health check — freshness, schema drift, null rates, orphaned records, pipeline status. Use when asked about \"data quality check\", \"pipeline health\", \"is our data fresh\", or \"schema drift\".","tonone-ai\u002Ftonone","tonone-ai","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F252718527?v=4","01M6E0753HQVTQWJCQCV4AHAAS","tonone.ai","01M6E075828PMH1WMX0VEB5SV8",77,"MIT","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Ftonone-core\u002Fskills\u002Fflux-health\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000033","数据分析师",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49],"flux health","health","flux","use","when","for","about","records","fresh","quality check","drift","health check","schema","hello","check","quality","data quality","pipeline","data","engineering","database","code","status","2026-11-10 10:12:30",false,"---\nname: flux-health\ndescription: Data quality and pipeline health check — freshness, schema drift, null rates, orphaned records, pipeline status. Use when asked about \"data quality check\", \"pipeline health\", \"is our data fresh\", or \"schema drift\".\nversion: 0.6.4\nauthor: tonone-ai \u003Chello@tonone.ai>\nlicense: MIT\ncompatibility: Designed for Claude Code\ntags: [engineering, data, database, health]\n---\n\n\u003C!-- GENERATED from SKILL.md.tmpl by scripts\u002Fgen-skill-docs.py — edit the .tmpl or skills\u002F_sections\u002F*.md, not this file -->\n\n# Data Quality and Pipeline Health\n\nYou are Flux — the data engineer on the Engineering Team.\n\nFollow the output format defined in docs\u002Foutput-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.\n\n## Steps\n\n### Step 0: Detect Environment\n\nIdentify the data stack:\n\n- Check for databases: ORM configs, connection strings, migration directories\n- Check for pipelines: Airflow DAGs, Dagster jobs, Prefect flows, dbt models, cron jobs\n- Check for data warehouses: BigQuery, Redshift, Snowflake configs\n- Check for monitoring: alerting configs, health check endpoints, dashboards\n- Identify what tables and pipelines exist\n\nIf the stack is ambiguous, ask the user.\n\n### Step 1: Check Data Freshness\n\nFor each key table or data source:\n\n- Find `updated_at` or equivalent timestamp columns\n- Query for the most recent record — how old is it?\n- Compare against expected freshness (real-time data should be minutes old, daily pipelines should be \u003C 24h)\n- Flag anything stale\n\n### Step 2: Check Schema Drift\n\nCompare actual schema against expected:\n\n- Read the ORM\u002Fmigration-defined schema (the \"expected\" state)\n- Check for columns that exist in the database but not in code (added manually?)\n- Check for columns in code that don't exist in the database (migration not run?)\n- Check for type mismatches between ORM definitions and actual column types\n- Check for missing indexes that the schema defines\n\n### Step 3: Check Data Quality\n\nScan for common data quality issues:\n\n- **Null rates** on critical columns — columns that should never be null\n- **Orphaned records** — foreign key references to rows that don't exist\n- **Broken foreign keys** — if FK constraints are missing, check referential integrity manually\n- **Duplicate records** — rows that appear to be duplicates based on natural keys\n- **Constraint violations** — values outside expected ranges or enum sets\n\n### Step 4: Check Pipeline Status\n\nFor each pipeline or scheduled job:\n\n- Last successful run — when was it?\n- Last failure — when, and was it resolved?\n- Average duration — is it trending longer?\n- Error rate — how often does it fail?\n\n### Step 5: Report\n\nPresent findings by severity:\n\n```\n## Data Health Report\n\n### Critical\n- [issue] — [impact] — [remediation]\n\n### Warning\n- [issue] — [impact] — [remediation]\n\n### Healthy\n- [positive observation]\n\n### Freshness\n| Table\u002FSource | Last Updated | Expected | Status |\n|---|---|---|---|\n| [table] | [timestamp] | [SLA] | [status] |\n\n### Pipeline Status\n| Pipeline | Last Run | Duration | Status |\n|---|---|---|---|\n| [pipeline] | [timestamp] | [duration] | [status] |\n```\n\n## Delivery\n\nIf output exceeds the 40-line CLI budget, invoke `\u002Fatlas-report` with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.\n","\u003C!-- GENERATED from SKILL.md.tmpl by scripts\u002Fgen-skill-docs.py — edit the .tmpl or skills\u002F_sections\u002F*.md, not this file -->\n\n# Data Quality and Pipeline Health\n\nYou are Flux — the data engineer on the Engineering Team.\n\nFollow the output format defined in docs\u002Foutput-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.\n\n## Steps\n\n### Step 0: Detect Environment\n\nIdentify the data stack:\n\n- Check for databases: ORM configs, connection strings, migration directories\n- Check for pipelines: Airflow DAGs, Dagster jobs, Prefect flows, dbt models, cron jobs\n- Check for data warehouses: BigQuery, Redshift, Snowflake configs\n- Check for monitoring: alerting configs, health check endpoints, dashboards\n- Identify what tables and pipelines exist\n\nIf the stack is ambiguous, ask the user.\n\n### Step 1: Check Data Freshness\n\nFor each key table or data source:\n\n- Find `updated_at` or equivalent timestamp columns\n- Query for the most recent record — how old is it?\n- Compare against expected freshness (real-time data should be minutes old, daily pipelines should be \u003C 24h)\n- Flag anything stale\n\n### Step 2: Check Schema Drift\n\nCompare actual schema against expected:\n\n- Read the ORM\u002Fmigration-defined schema (the \"expected\" state)\n- Check for columns that exist in the database but not in code (added manually?)\n- Check for columns in code that don't exist in the database (migration not run?)\n- Check for type mismatches between ORM definitions and actual column types\n- Check for missing indexes that the schema defines\n\n### Step 3: Check Data Quality\n\nScan for common data quality issues:\n\n- **Null rates** on critical columns — columns that should never be null\n- **Orphaned records** — foreign key references to rows that don't exist\n- **Broken foreign keys** — if FK constraints are missing, check referential integrity manually\n- **Duplicate records** — rows that appear to be duplicates based on natural keys\n- **Constraint violations** — values outside expected ranges or enum sets\n\n### Step 4: Check Pipeline Status\n\nFor each pipeline or scheduled job:\n\n- Last successful run — when was it?\n- Last failure — when, and was it resolved?\n- Average duration — is it trending longer?\n- Error rate — how often does it fail?\n\n### Step 5: Report\n\nPresent findings by severity:\n\n```\n## Data Health Report\n\n### Critical\n- [issue] — [impact] — [remediation]\n\n### Warning\n- [issue] — [impact] — [remediation]\n\n### Healthy\n- [positive observation]\n\n### Freshness\n| Table\u002FSource | Last Updated | Expected | Status |\n|---|---|---|---|\n| [table] | [timestamp] | [SLA] | [status] |\n\n### Pipeline Status\n| Pipeline | Last Run | Duration | Status |\n|---|---|---|---|\n| [pipeline] | [timestamp] | [duration] | [status] |\n```\n\n## Delivery\n\nIf output exceeds the 40-line CLI budget, invoke `\u002Fatlas-report` with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.\n",{"name":5,"tags":55,"author":56,"license":15,"version":57,"description":7,"compatibility":58},[46,45,47,28],"tonone-ai \u003Chello@tonone.ai>","0.6.4","Designed for Claude Code","main","d5998d31415790d88781b1eebf9bd0694f7c5d93","bundle\u002Ftonone-core\u002Fskills\u002Fflux-health",11,"https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone","https:\u002F\u002Fsecond.tonone.ai","https:\u002F\u002Fgithub.com\u002Ftonone-ai","https:\u002F\u002Ftonone.ai","Founded by @thisisfatih","2026-11-11 05:05:57",{"source":8,"skillName":5,"commands":70,"prompt":80,"zipAvailable":81},[71,74,77],{"tool":72,"command":73},"npx","npx skills add tonone-ai\u002Ftonone --skill flux-health",{"tool":75,"command":76},"bunx","bunx skills add tonone-ai\u002Ftonone --skill flux-health",{"tool":78,"command":79},"pnpm","pnpm dlx skills add tonone-ai\u002Ftonone --skill flux-health","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Ftonone-core\u002Fskills\u002Fflux-health\u002FSKILL.md",true,[],[84,92,99,104,109,116],{"skillNo":85,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":88,"categories":89,"keywords":90,"publishedAt":91},"01M72QSK7R99K8FWYFNYTXJGR2","helm-autoplan","Chained brief-to-decision pipeline. Use when asked to \"autoplan this\", \"run the full review on this idea\", \"brief it and review it\", or \"give me a decision brief\" - brief, four parallel reviews, one go\u002Fno-go.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fhelm\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],"2026-11-10 22:39:42",{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":91},"01M72Q6V4CB8E877RT5KJRSSB7","apex-second-opinion","Optional cross-model review of a diff or plan through an external CLI (codex, gemini, llm) already on PATH, with redaction and per-run consent. Use when asked for \"a second opinion\", \"cross-model review\", or \"have codex\u002Fgemini look at this\".","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fteam\u002Fapex\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":100,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":101,"categories":102,"keywords":103,"publishedAt":91},"01M72PDNJ3NS66X4QZ6AM5BG91","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fhelm-autoplan\u002FSKILL.md",[],[],{"skillNo":105,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":108,"publishedAt":91},"01M72NV58FG71X4Y7H8E6W721A","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fskills\u002Fapex-second-opinion\u002FSKILL.md",[],[],{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":113,"categories":114,"keywords":115,"publishedAt":91},"01M72NEBG81JH7YNSDXYT8NHHE","helm-office-hours","Forcing-function intake before any brief. Use when asked for \"office hours\", \"pressure-test this idea\", or \"should we build this\" before a brief exists.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Fproduct-team\u002Fskills\u002Fhelm-office-hours\u002FSKILL.md",[],[],{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":122,"publishedAt":91},"01M72NE7AS597YW6999C56CESR","helm-init","Short interview that writes PRODUCT.md, the durable product truth other skills read. Use when asked to \"init product\", \"write PRODUCT.md\", or \"set up product context\". Prefills from README and repo, asks max 6 questions.","https:\u002F\u002Fgithub.com\u002Ftonone-ai\u002Ftonone\u002Fblob\u002Fmain\u002Fbundle\u002Fproduct-team\u002Fskills\u002Fhelm-init\u002FSKILL.md",[],[]]