[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-astronomer-analyzing-data":3,"mdc-a4fs5b-key":55,"related-org-astronomer-analyzing-data":1945,"related-repo-astronomer-analyzing-data":2105},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":25,"repoUrl":26,"updatedAt":27,"license":28,"forks":29,"topics":30,"repo":50,"sourceUrl":53,"mdContent":54},"analyzing-data","query data warehouses for business questions","Queries the data warehouse with SQL and answers business questions about data. Use when answering anything that needs warehouse data - counts, metrics, trends, aggregations, joins across tables, data lookups, or ad-hoc SQL analysis (for example \"who uses X\", \"how many Y\", \"show me Z\", \"find customers\", \"what is the count\").",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"astronomer","Astronomer","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fastronomer.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Data Engineering","data-engineering","tag",{"name":17,"slug":18,"type":15},"Data Analysis","data-analysis",{"name":20,"slug":21,"type":15},"Analytics","analytics",{"name":23,"slug":24,"type":15},"SQL","sql",412,"https:\u002F\u002Fgithub.com\u002Fastronomer\u002Fagents","2026-04-06T18:01:49.599775",null,55,[31,32,33,34,35,36,37,38,39,14,40,41,42,43,44,45,46,47,48,49],"agentic-workflow","agents","ai","ai-agents","airflow","apache-airflow","claude","cursor","dag","data-pipelines","dbt","llm","mcp","orchestrator","skills","workflow-automation","workflow-management","workflow-orchestration","workflows",{"repoUrl":26,"stars":25,"forks":29,"topics":51,"description":52},[31,32,33,34,35,36,37,38,39,14,40,41,42,43,44,45,46,47,48,49],"AI agent tooling for data engineering workflows.","https:\u002F\u002Fgithub.com\u002Fastronomer\u002Fagents\u002Ftree\u002FHEAD\u002Fskills\u002Fanalyzing-data","---\nname: analyzing-data\ndescription: Queries the data warehouse with SQL and answers business questions about data. Use when answering anything that needs warehouse data - counts, metrics, trends, aggregations, joins across tables, data lookups, or ad-hoc SQL analysis (for example \"who uses X\", \"how many Y\", \"show me Z\", \"find customers\", \"what is the count\").\n---\n\n# Data Analysis\n\nAnswer business questions by querying the data warehouse. The kernel auto-starts on first `exec` call.\n\n**All CLI commands below are relative to this skill's directory.** Before running any `scripts\u002Fcli.py` command, `cd` to the directory containing this file.\n\n## Workflow\n\n1. **Pattern lookup** — Check for a cached query strategy:\n   ```bash\n   uv run scripts\u002Fcli.py pattern lookup \"\u003Cuser's question>\"\n   ```\n   If a pattern exists, follow its strategy. Record the outcome after executing:\n   ```bash\n   uv run scripts\u002Fcli.py pattern record \u003Cname> --success  # or --failure\n   ```\n\n2. **Concept lookup** — Find known table mappings:\n   ```bash\n   uv run scripts\u002Fcli.py concept lookup \u003Cconcept>\n   ```\n\n3. **Table discovery** — If cache misses, search the codebase (`Grep pattern=\"\u003Cconcept>\" glob=\"**\u002F*.sql\"`) or query `INFORMATION_SCHEMA`. See [reference\u002Fdiscovery-warehouse.md](reference\u002Fdiscovery-warehouse.md).\n\n4. **Execute query**:\n   ```bash\n   uv run scripts\u002Fcli.py exec \"df = run_sql('SELECT ...')\"\n   uv run scripts\u002Fcli.py exec \"print(df)\"\n   ```\n\n5. **Cache learnings** — Always cache before presenting results:\n   ```bash\n   # Cache concept → table mapping\n   uv run scripts\u002Fcli.py concept learn \u003Cconcept> \u003CTABLE> -k \u003CKEY_COL>\n   # Cache query strategy (if discovery was needed)\n   uv run scripts\u002Fcli.py pattern learn \u003Cname> -q \"question\" -s \"step\" -t \"TABLE\" -g \"gotcha\"\n   ```\n\n6. **Present findings** to user.\n\n## Kernel Functions\n\n| Function | Returns |\n|----------|---------|\n| `run_sql(query, limit=100)` | Polars DataFrame |\n| `run_sql_pandas(query, limit=100)` | Pandas DataFrame |\n| `run_sql_many(queries, limit=100)` | List of Polars DataFrames (one per query) |\n\n`pl` (Polars) and `pd` (Pandas) are pre-imported.\n\n**Run independent queries together** with `run_sql_many` — they execute concurrently (Snowflake async \u002F connection-pool fan-out) instead of one at a time:\n\n```bash\nuv run scripts\u002Fcli.py exec \"dfs = run_sql_many(['SELECT ...', 'SELECT ...']); print(dfs[0])\"\n```\n\n`run_sql_many` is **fail-fast**: if any query errors, the call raises and the results of the queries that succeeded are discarded. Use separate `run_sql` calls if you need partial results.\n\n**Timeouts:** `exec` waits up to 120s by default, then interrupts the query and returns a \"client stopped waiting\" message (the query may still finish server-side). Raise it for known long-running queries: `uv run scripts\u002Fcli.py exec \"...\" -t 600`.\n\n**Idle kernel:** the kernel self-terminates after 2h idle (preserving state until then). Override with `ASTRO_KERNEL_IDLE_TIMEOUT` (seconds; `0` disables).\n\n## CLI Reference\n\n### Kernel\n\n```bash\nuv run scripts\u002Fcli.py warehouse list      # List warehouses\nuv run scripts\u002Fcli.py start [-w name]     # Start kernel (with optional warehouse)\nuv run scripts\u002Fcli.py exec \"...\"          # Execute Python code\nuv run scripts\u002Fcli.py status              # Kernel status\nuv run scripts\u002Fcli.py restart             # Restart kernel\nuv run scripts\u002Fcli.py stop                # Stop kernel\nuv run scripts\u002Fcli.py install \u003Cpkg>       # Install package\n```\n\n### Concept Cache\n\n```bash\nuv run scripts\u002Fcli.py concept lookup \u003Cname>                     # Look up\nuv run scripts\u002Fcli.py concept learn \u003Cname> \u003CTABLE> -k \u003CKEY_COL> # Learn\nuv run scripts\u002Fcli.py concept list                               # List all\nuv run scripts\u002Fcli.py concept import -p \u002Fpath\u002Fto\u002Fwarehouse.md   # Bulk import\n```\n\n### Pattern Cache\n\n```bash\nuv run scripts\u002Fcli.py pattern lookup \"question\"                                      # Look up\nuv run scripts\u002Fcli.py pattern learn \u003Cname> -q \"...\" -s \"...\" -t \"TABLE\" -g \"gotcha\"  # Learn\nuv run scripts\u002Fcli.py pattern record \u003Cname> --success                                # Record outcome\nuv run scripts\u002Fcli.py pattern list                                                   # List all\nuv run scripts\u002Fcli.py pattern delete \u003Cname>                                          # Delete\n```\n\n### Table Schema Cache\n\n```bash\nuv run scripts\u002Fcli.py table lookup \u003CTABLE>            # Look up schema\nuv run scripts\u002Fcli.py table cache \u003CTABLE> -c '[...]'  # Cache schema\nuv run scripts\u002Fcli.py table list                       # List cached\nuv run scripts\u002Fcli.py table delete \u003CTABLE>             # Delete\n```\n\n### Cache Management\n\n```bash\nuv run scripts\u002Fcli.py cache status                # Stats\nuv run scripts\u002Fcli.py cache clear [--stale-only]  # Clear\n```\n\n## References\n\n- [reference\u002Fdiscovery-warehouse.md](reference\u002Fdiscovery-warehouse.md) — Large table handling, warehouse exploration, INFORMATION_SCHEMA queries\n- [reference\u002Fcommon-patterns.md](reference\u002Fcommon-patterns.md) — SQL templates for trends, comparisons, top-N, distributions, cohorts\n",{"data":56,"body":57},{"name":4,"description":6},{"type":58,"children":59},"root",[60,67,82,109,116,675,681,760,779,797,836,861,885,911,917,924,1154,1160,1358,1364,1640,1646,1835,1841,1910,1916,1939],{"type":61,"tag":62,"props":63,"children":64},"element","h1",{"id":18},[65],{"type":66,"value":17},"text",{"type":61,"tag":68,"props":69,"children":70},"p",{},[71,73,80],{"type":66,"value":72},"Answer business questions by querying the data warehouse. The kernel auto-starts on first ",{"type":61,"tag":74,"props":75,"children":77},"code",{"className":76},[],[78],{"type":66,"value":79},"exec",{"type":66,"value":81}," call.",{"type":61,"tag":68,"props":83,"children":84},{},[85,91,93,99,101,107],{"type":61,"tag":86,"props":87,"children":88},"strong",{},[89],{"type":66,"value":90},"All CLI commands below are relative to this skill's directory.",{"type":66,"value":92}," Before running any ",{"type":61,"tag":74,"props":94,"children":96},{"className":95},[],[97],{"type":66,"value":98},"scripts\u002Fcli.py",{"type":66,"value":100}," command, ",{"type":61,"tag":74,"props":102,"children":104},{"className":103},[],[105],{"type":66,"value":106},"cd",{"type":66,"value":108}," to the directory containing this file.",{"type":61,"tag":110,"props":111,"children":113},"h2",{"id":112},"workflow",[114],{"type":66,"value":115},"Workflow",{"type":61,"tag":117,"props":118,"children":119},"ol",{},[120,260,320,354,437,665],{"type":61,"tag":121,"props":122,"children":123},"li",{},[124,129,131,191,195,197],{"type":61,"tag":86,"props":125,"children":126},{},[127],{"type":66,"value":128},"Pattern lookup",{"type":66,"value":130}," — Check for a cached query strategy:",{"type":61,"tag":132,"props":133,"children":138},"pre",{"className":134,"code":135,"language":136,"meta":137,"style":137},"language-bash shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","uv run scripts\u002Fcli.py pattern lookup \"\u003Cuser's question>\"\n","bash","",[139],{"type":61,"tag":74,"props":140,"children":141},{"__ignoreMap":137},[142],{"type":61,"tag":143,"props":144,"children":147},"span",{"class":145,"line":146},"line",1,[148,154,160,165,170,175,181,186],{"type":61,"tag":143,"props":149,"children":151},{"style":150},"--shiki-light:#E2931D;--shiki-default:#FFCB6B;--shiki-dark:#FFCB6B",[152],{"type":66,"value":153},"uv",{"type":61,"tag":143,"props":155,"children":157},{"style":156},"--shiki-light:#91B859;--shiki-default:#C3E88D;--shiki-dark:#C3E88D",[158],{"type":66,"value":159}," run",{"type":61,"tag":143,"props":161,"children":162},{"style":156},[163],{"type":66,"value":164}," scripts\u002Fcli.py",{"type":61,"tag":143,"props":166,"children":167},{"style":156},[168],{"type":66,"value":169}," pattern",{"type":61,"tag":143,"props":171,"children":172},{"style":156},[173],{"type":66,"value":174}," lookup",{"type":61,"tag":143,"props":176,"children":178},{"style":177},"--shiki-light:#39ADB5;--shiki-default:#89DDFF;--shiki-dark:#89DDFF",[179],{"type":66,"value":180}," \"",{"type":61,"tag":143,"props":182,"children":183},{"style":156},[184],{"type":66,"value":185},"\u003Cuser's question>",{"type":61,"tag":143,"props":187,"children":188},{"style":177},[189],{"type":66,"value":190},"\"\n",{"type":61,"tag":192,"props":193,"children":194},"br",{},[],{"type":66,"value":196},"If a pattern exists, follow its strategy. Record the outcome after executing:",{"type":61,"tag":132,"props":198,"children":200},{"className":134,"code":199,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py pattern record \u003Cname> --success  # or --failure\n",[201],{"type":61,"tag":74,"props":202,"children":203},{"__ignoreMap":137},[204],{"type":61,"tag":143,"props":205,"children":206},{"class":145,"line":146},[207,211,215,219,223,228,233,238,244,249,254],{"type":61,"tag":143,"props":208,"children":209},{"style":150},[210],{"type":66,"value":153},{"type":61,"tag":143,"props":212,"children":213},{"style":156},[214],{"type":66,"value":159},{"type":61,"tag":143,"props":216,"children":217},{"style":156},[218],{"type":66,"value":164},{"type":61,"tag":143,"props":220,"children":221},{"style":156},[222],{"type":66,"value":169},{"type":61,"tag":143,"props":224,"children":225},{"style":156},[226],{"type":66,"value":227}," record",{"type":61,"tag":143,"props":229,"children":230},{"style":177},[231],{"type":66,"value":232}," \u003C",{"type":61,"tag":143,"props":234,"children":235},{"style":156},[236],{"type":66,"value":237},"nam",{"type":61,"tag":143,"props":239,"children":241},{"style":240},"--shiki-light:#90A4AE;--shiki-default:#EEFFFF;--shiki-dark:#BABED8",[242],{"type":66,"value":243},"e",{"type":61,"tag":143,"props":245,"children":246},{"style":177},[247],{"type":66,"value":248},">",{"type":61,"tag":143,"props":250,"children":251},{"style":156},[252],{"type":66,"value":253}," --success",{"type":61,"tag":143,"props":255,"children":257},{"style":256},"--shiki-light:#90A4AE;--shiki-light-font-style:italic;--shiki-default:#546E7A;--shiki-default-font-style:italic;--shiki-dark:#676E95;--shiki-dark-font-style:italic",[258],{"type":66,"value":259},"  # or --failure\n",{"type":61,"tag":121,"props":261,"children":262},{},[263,268,270],{"type":61,"tag":86,"props":264,"children":265},{},[266],{"type":66,"value":267},"Concept lookup",{"type":66,"value":269}," — Find known table mappings:",{"type":61,"tag":132,"props":271,"children":273},{"className":134,"code":272,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py concept lookup \u003Cconcept>\n",[274],{"type":61,"tag":74,"props":275,"children":276},{"__ignoreMap":137},[277],{"type":61,"tag":143,"props":278,"children":279},{"class":145,"line":146},[280,284,288,292,297,301,305,310,315],{"type":61,"tag":143,"props":281,"children":282},{"style":150},[283],{"type":66,"value":153},{"type":61,"tag":143,"props":285,"children":286},{"style":156},[287],{"type":66,"value":159},{"type":61,"tag":143,"props":289,"children":290},{"style":156},[291],{"type":66,"value":164},{"type":61,"tag":143,"props":293,"children":294},{"style":156},[295],{"type":66,"value":296}," concept",{"type":61,"tag":143,"props":298,"children":299},{"style":156},[300],{"type":66,"value":174},{"type":61,"tag":143,"props":302,"children":303},{"style":177},[304],{"type":66,"value":232},{"type":61,"tag":143,"props":306,"children":307},{"style":156},[308],{"type":66,"value":309},"concep",{"type":61,"tag":143,"props":311,"children":312},{"style":240},[313],{"type":66,"value":314},"t",{"type":61,"tag":143,"props":316,"children":317},{"style":177},[318],{"type":66,"value":319},">\n",{"type":61,"tag":121,"props":321,"children":322},{},[323,328,330,336,338,344,346,352],{"type":61,"tag":86,"props":324,"children":325},{},[326],{"type":66,"value":327},"Table discovery",{"type":66,"value":329}," — If cache misses, search the codebase (",{"type":61,"tag":74,"props":331,"children":333},{"className":332},[],[334],{"type":66,"value":335},"Grep pattern=\"\u003Cconcept>\" glob=\"**\u002F*.sql\"",{"type":66,"value":337},") or query ",{"type":61,"tag":74,"props":339,"children":341},{"className":340},[],[342],{"type":66,"value":343},"INFORMATION_SCHEMA",{"type":66,"value":345},". See ",{"type":61,"tag":347,"props":348,"children":350},"a",{"href":349},"reference\u002Fdiscovery-warehouse.md",[351],{"type":66,"value":349},{"type":66,"value":353},".",{"type":61,"tag":121,"props":355,"children":356},{},[357,362,364],{"type":61,"tag":86,"props":358,"children":359},{},[360],{"type":66,"value":361},"Execute query",{"type":66,"value":363},":",{"type":61,"tag":132,"props":365,"children":367},{"className":134,"code":366,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py exec \"df = run_sql('SELECT ...')\"\nuv run scripts\u002Fcli.py exec \"print(df)\"\n",[368],{"type":61,"tag":74,"props":369,"children":370},{"__ignoreMap":137},[371,404],{"type":61,"tag":143,"props":372,"children":373},{"class":145,"line":146},[374,378,382,386,391,395,400],{"type":61,"tag":143,"props":375,"children":376},{"style":150},[377],{"type":66,"value":153},{"type":61,"tag":143,"props":379,"children":380},{"style":156},[381],{"type":66,"value":159},{"type":61,"tag":143,"props":383,"children":384},{"style":156},[385],{"type":66,"value":164},{"type":61,"tag":143,"props":387,"children":388},{"style":156},[389],{"type":66,"value":390}," exec",{"type":61,"tag":143,"props":392,"children":393},{"style":177},[394],{"type":66,"value":180},{"type":61,"tag":143,"props":396,"children":397},{"style":156},[398],{"type":66,"value":399},"df = run_sql('SELECT ...')",{"type":61,"tag":143,"props":401,"children":402},{"style":177},[403],{"type":66,"value":190},{"type":61,"tag":143,"props":405,"children":407},{"class":145,"line":406},2,[408,412,416,420,424,428,433],{"type":61,"tag":143,"props":409,"children":410},{"style":150},[411],{"type":66,"value":153},{"type":61,"tag":143,"props":413,"children":414},{"style":156},[415],{"type":66,"value":159},{"type":61,"tag":143,"props":417,"children":418},{"style":156},[419],{"type":66,"value":164},{"type":61,"tag":143,"props":421,"children":422},{"style":156},[423],{"type":66,"value":390},{"type":61,"tag":143,"props":425,"children":426},{"style":177},[427],{"type":66,"value":180},{"type":61,"tag":143,"props":429,"children":430},{"style":156},[431],{"type":66,"value":432},"print(df)",{"type":61,"tag":143,"props":434,"children":435},{"style":177},[436],{"type":66,"value":190},{"type":61,"tag":121,"props":438,"children":439},{},[440,445,447],{"type":61,"tag":86,"props":441,"children":442},{},[443],{"type":66,"value":444},"Cache learnings",{"type":66,"value":446}," — Always cache before presenting results:",{"type":61,"tag":132,"props":448,"children":450},{"className":134,"code":449,"language":136,"meta":137,"style":137},"# Cache concept → table mapping\nuv run scripts\u002Fcli.py concept learn \u003Cconcept> \u003CTABLE> -k \u003CKEY_COL>\n# Cache query strategy (if discovery was needed)\nuv run scripts\u002Fcli.py pattern learn \u003Cname> -q \"question\" -s \"step\" -t \"TABLE\" -g \"gotcha\"\n",[451],{"type":61,"tag":74,"props":452,"children":453},{"__ignoreMap":137},[454,462,543,552],{"type":61,"tag":143,"props":455,"children":456},{"class":145,"line":146},[457],{"type":61,"tag":143,"props":458,"children":459},{"style":256},[460],{"type":66,"value":461},"# Cache concept → table mapping\n",{"type":61,"tag":143,"props":463,"children":464},{"class":145,"line":406},[465,469,473,477,481,486,490,494,498,502,506,511,516,520,525,529,534,539],{"type":61,"tag":143,"props":466,"children":467},{"style":150},[468],{"type":66,"value":153},{"type":61,"tag":143,"props":470,"children":471},{"style":156},[472],{"type":66,"value":159},{"type":61,"tag":143,"props":474,"children":475},{"style":156},[476],{"type":66,"value":164},{"type":61,"tag":143,"props":478,"children":479},{"style":156},[480],{"type":66,"value":296},{"type":61,"tag":143,"props":482,"children":483},{"style":156},[484],{"type":66,"value":485}," learn",{"type":61,"tag":143,"props":487,"children":488},{"style":177},[489],{"type":66,"value":232},{"type":61,"tag":143,"props":491,"children":492},{"style":156},[493],{"type":66,"value":309},{"type":61,"tag":143,"props":495,"children":496},{"style":240},[497],{"type":66,"value":314},{"type":61,"tag":143,"props":499,"children":500},{"style":177},[501],{"type":66,"value":248},{"type":61,"tag":143,"props":503,"children":504},{"style":177},[505],{"type":66,"value":232},{"type":61,"tag":143,"props":507,"children":508},{"style":156},[509],{"type":66,"value":510},"TABL",{"type":61,"tag":143,"props":512,"children":513},{"style":240},[514],{"type":66,"value":515},"E",{"type":61,"tag":143,"props":517,"children":518},{"style":177},[519],{"type":66,"value":248},{"type":61,"tag":143,"props":521,"children":522},{"style":156},[523],{"type":66,"value":524}," -k",{"type":61,"tag":143,"props":526,"children":527},{"style":177},[528],{"type":66,"value":232},{"type":61,"tag":143,"props":530,"children":531},{"style":156},[532],{"type":66,"value":533},"KEY_CO",{"type":61,"tag":143,"props":535,"children":536},{"style":240},[537],{"type":66,"value":538},"L",{"type":61,"tag":143,"props":540,"children":541},{"style":177},[542],{"type":66,"value":319},{"type":61,"tag":143,"props":544,"children":546},{"class":145,"line":545},3,[547],{"type":61,"tag":143,"props":548,"children":549},{"style":256},[550],{"type":66,"value":551},"# Cache query strategy (if discovery was needed)\n",{"type":61,"tag":143,"props":553,"children":555},{"class":145,"line":554},4,[556,560,564,568,572,576,580,584,588,592,597,601,606,611,616,620,625,629,634,638,643,647,652,656,661],{"type":61,"tag":143,"props":557,"children":558},{"style":150},[559],{"type":66,"value":153},{"type":61,"tag":143,"props":561,"children":562},{"style":156},[563],{"type":66,"value":159},{"type":61,"tag":143,"props":565,"children":566},{"style":156},[567],{"type":66,"value":164},{"type":61,"tag":143,"props":569,"children":570},{"style":156},[571],{"type":66,"value":169},{"type":61,"tag":143,"props":573,"children":574},{"style":156},[575],{"type":66,"value":485},{"type":61,"tag":143,"props":577,"children":578},{"style":177},[579],{"type":66,"value":232},{"type":61,"tag":143,"props":581,"children":582},{"style":156},[583],{"type":66,"value":237},{"type":61,"tag":143,"props":585,"children":586},{"style":240},[587],{"type":66,"value":243},{"type":61,"tag":143,"props":589,"children":590},{"style":177},[591],{"type":66,"value":248},{"type":61,"tag":143,"props":593,"children":594},{"style":156},[595],{"type":66,"value":596}," -q",{"type":61,"tag":143,"props":598,"children":599},{"style":177},[600],{"type":66,"value":180},{"type":61,"tag":143,"props":602,"children":603},{"style":156},[604],{"type":66,"value":605},"question",{"type":61,"tag":143,"props":607,"children":608},{"style":177},[609],{"type":66,"value":610},"\"",{"type":61,"tag":143,"props":612,"children":613},{"style":156},[614],{"type":66,"value":615}," -s",{"type":61,"tag":143,"props":617,"children":618},{"style":177},[619],{"type":66,"value":180},{"type":61,"tag":143,"props":621,"children":622},{"style":156},[623],{"type":66,"value":624},"step",{"type":61,"tag":143,"props":626,"children":627},{"style":177},[628],{"type":66,"value":610},{"type":61,"tag":143,"props":630,"children":631},{"style":156},[632],{"type":66,"value":633}," -t",{"type":61,"tag":143,"props":635,"children":636},{"style":177},[637],{"type":66,"value":180},{"type":61,"tag":143,"props":639,"children":640},{"style":156},[641],{"type":66,"value":642},"TABLE",{"type":61,"tag":143,"props":644,"children":645},{"style":177},[646],{"type":66,"value":610},{"type":61,"tag":143,"props":648,"children":649},{"style":156},[650],{"type":66,"value":651}," -g",{"type":61,"tag":143,"props":653,"children":654},{"style":177},[655],{"type":66,"value":180},{"type":61,"tag":143,"props":657,"children":658},{"style":156},[659],{"type":66,"value":660},"gotcha",{"type":61,"tag":143,"props":662,"children":663},{"style":177},[664],{"type":66,"value":190},{"type":61,"tag":121,"props":666,"children":667},{},[668,673],{"type":61,"tag":86,"props":669,"children":670},{},[671],{"type":66,"value":672},"Present findings",{"type":66,"value":674}," to user.",{"type":61,"tag":110,"props":676,"children":678},{"id":677},"kernel-functions",[679],{"type":66,"value":680},"Kernel Functions",{"type":61,"tag":682,"props":683,"children":684},"table",{},[685,704],{"type":61,"tag":686,"props":687,"children":688},"thead",{},[689],{"type":61,"tag":690,"props":691,"children":692},"tr",{},[693,699],{"type":61,"tag":694,"props":695,"children":696},"th",{},[697],{"type":66,"value":698},"Function",{"type":61,"tag":694,"props":700,"children":701},{},[702],{"type":66,"value":703},"Returns",{"type":61,"tag":705,"props":706,"children":707},"tbody",{},[708,726,743],{"type":61,"tag":690,"props":709,"children":710},{},[711,721],{"type":61,"tag":712,"props":713,"children":714},"td",{},[715],{"type":61,"tag":74,"props":716,"children":718},{"className":717},[],[719],{"type":66,"value":720},"run_sql(query, limit=100)",{"type":61,"tag":712,"props":722,"children":723},{},[724],{"type":66,"value":725},"Polars DataFrame",{"type":61,"tag":690,"props":727,"children":728},{},[729,738],{"type":61,"tag":712,"props":730,"children":731},{},[732],{"type":61,"tag":74,"props":733,"children":735},{"className":734},[],[736],{"type":66,"value":737},"run_sql_pandas(query, limit=100)",{"type":61,"tag":712,"props":739,"children":740},{},[741],{"type":66,"value":742},"Pandas DataFrame",{"type":61,"tag":690,"props":744,"children":745},{},[746,755],{"type":61,"tag":712,"props":747,"children":748},{},[749],{"type":61,"tag":74,"props":750,"children":752},{"className":751},[],[753],{"type":66,"value":754},"run_sql_many(queries, limit=100)",{"type":61,"tag":712,"props":756,"children":757},{},[758],{"type":66,"value":759},"List of Polars DataFrames (one per query)",{"type":61,"tag":68,"props":761,"children":762},{},[763,769,771,777],{"type":61,"tag":74,"props":764,"children":766},{"className":765},[],[767],{"type":66,"value":768},"pl",{"type":66,"value":770}," (Polars) and ",{"type":61,"tag":74,"props":772,"children":774},{"className":773},[],[775],{"type":66,"value":776},"pd",{"type":66,"value":778}," (Pandas) are pre-imported.",{"type":61,"tag":68,"props":780,"children":781},{},[782,787,789,795],{"type":61,"tag":86,"props":783,"children":784},{},[785],{"type":66,"value":786},"Run independent queries together",{"type":66,"value":788}," with ",{"type":61,"tag":74,"props":790,"children":792},{"className":791},[],[793],{"type":66,"value":794},"run_sql_many",{"type":66,"value":796}," — they execute concurrently (Snowflake async \u002F connection-pool fan-out) instead of one at a time:",{"type":61,"tag":132,"props":798,"children":800},{"className":134,"code":799,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py exec \"dfs = run_sql_many(['SELECT ...', 'SELECT ...']); print(dfs[0])\"\n",[801],{"type":61,"tag":74,"props":802,"children":803},{"__ignoreMap":137},[804],{"type":61,"tag":143,"props":805,"children":806},{"class":145,"line":146},[807,811,815,819,823,827,832],{"type":61,"tag":143,"props":808,"children":809},{"style":150},[810],{"type":66,"value":153},{"type":61,"tag":143,"props":812,"children":813},{"style":156},[814],{"type":66,"value":159},{"type":61,"tag":143,"props":816,"children":817},{"style":156},[818],{"type":66,"value":164},{"type":61,"tag":143,"props":820,"children":821},{"style":156},[822],{"type":66,"value":390},{"type":61,"tag":143,"props":824,"children":825},{"style":177},[826],{"type":66,"value":180},{"type":61,"tag":143,"props":828,"children":829},{"style":156},[830],{"type":66,"value":831},"dfs = run_sql_many(['SELECT ...', 'SELECT ...']); print(dfs[0])",{"type":61,"tag":143,"props":833,"children":834},{"style":177},[835],{"type":66,"value":190},{"type":61,"tag":68,"props":837,"children":838},{},[839,844,846,851,853,859],{"type":61,"tag":74,"props":840,"children":842},{"className":841},[],[843],{"type":66,"value":794},{"type":66,"value":845}," is ",{"type":61,"tag":86,"props":847,"children":848},{},[849],{"type":66,"value":850},"fail-fast",{"type":66,"value":852},": if any query errors, the call raises and the results of the queries that succeeded are discarded. Use separate ",{"type":61,"tag":74,"props":854,"children":856},{"className":855},[],[857],{"type":66,"value":858},"run_sql",{"type":66,"value":860}," calls if you need partial results.",{"type":61,"tag":68,"props":862,"children":863},{},[864,869,871,876,878,884],{"type":61,"tag":86,"props":865,"children":866},{},[867],{"type":66,"value":868},"Timeouts:",{"type":66,"value":870}," ",{"type":61,"tag":74,"props":872,"children":874},{"className":873},[],[875],{"type":66,"value":79},{"type":66,"value":877}," waits up to 120s by default, then interrupts the query and returns a \"client stopped waiting\" message (the query may still finish server-side). Raise it for known long-running queries: ",{"type":61,"tag":74,"props":879,"children":881},{"className":880},[],[882],{"type":66,"value":883},"uv run scripts\u002Fcli.py exec \"...\" -t 600",{"type":66,"value":353},{"type":61,"tag":68,"props":886,"children":887},{},[888,893,895,901,903,909],{"type":61,"tag":86,"props":889,"children":890},{},[891],{"type":66,"value":892},"Idle kernel:",{"type":66,"value":894}," the kernel self-terminates after 2h idle (preserving state until then). Override with ",{"type":61,"tag":74,"props":896,"children":898},{"className":897},[],[899],{"type":66,"value":900},"ASTRO_KERNEL_IDLE_TIMEOUT",{"type":66,"value":902}," (seconds; ",{"type":61,"tag":74,"props":904,"children":906},{"className":905},[],[907],{"type":66,"value":908},"0",{"type":66,"value":910}," disables).",{"type":61,"tag":110,"props":912,"children":914},{"id":913},"cli-reference",[915],{"type":66,"value":916},"CLI Reference",{"type":61,"tag":918,"props":919,"children":921},"h3",{"id":920},"kernel",[922],{"type":66,"value":923},"Kernel",{"type":61,"tag":132,"props":925,"children":927},{"className":134,"code":926,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py warehouse list      # List warehouses\nuv run scripts\u002Fcli.py start [-w name]     # Start kernel (with optional warehouse)\nuv run scripts\u002Fcli.py exec \"...\"          # Execute Python code\nuv run scripts\u002Fcli.py status              # Kernel status\nuv run scripts\u002Fcli.py restart             # Restart kernel\nuv run scripts\u002Fcli.py stop                # Stop kernel\nuv run scripts\u002Fcli.py install \u003Cpkg>       # Install package\n",[928],{"type":61,"tag":74,"props":929,"children":930},{"__ignoreMap":137},[931,961,996,1033,1058,1084,1110],{"type":61,"tag":143,"props":932,"children":933},{"class":145,"line":146},[934,938,942,946,951,956],{"type":61,"tag":143,"props":935,"children":936},{"style":150},[937],{"type":66,"value":153},{"type":61,"tag":143,"props":939,"children":940},{"style":156},[941],{"type":66,"value":159},{"type":61,"tag":143,"props":943,"children":944},{"style":156},[945],{"type":66,"value":164},{"type":61,"tag":143,"props":947,"children":948},{"style":156},[949],{"type":66,"value":950}," warehouse",{"type":61,"tag":143,"props":952,"children":953},{"style":156},[954],{"type":66,"value":955}," list",{"type":61,"tag":143,"props":957,"children":958},{"style":256},[959],{"type":66,"value":960},"      # List warehouses\n",{"type":61,"tag":143,"props":962,"children":963},{"class":145,"line":406},[964,968,972,976,981,986,991],{"type":61,"tag":143,"props":965,"children":966},{"style":150},[967],{"type":66,"value":153},{"type":61,"tag":143,"props":969,"children":970},{"style":156},[971],{"type":66,"value":159},{"type":61,"tag":143,"props":973,"children":974},{"style":156},[975],{"type":66,"value":164},{"type":61,"tag":143,"props":977,"children":978},{"style":156},[979],{"type":66,"value":980}," start",{"type":61,"tag":143,"props":982,"children":983},{"style":240},[984],{"type":66,"value":985}," [-w ",{"type":61,"tag":143,"props":987,"children":988},{"style":156},[989],{"type":66,"value":990},"name]",{"type":61,"tag":143,"props":992,"children":993},{"style":256},[994],{"type":66,"value":995},"     # Start kernel (with optional warehouse)\n",{"type":61,"tag":143,"props":997,"children":998},{"class":145,"line":545},[999,1003,1007,1011,1015,1019,1024,1028],{"type":61,"tag":143,"props":1000,"children":1001},{"style":150},[1002],{"type":66,"value":153},{"type":61,"tag":143,"props":1004,"children":1005},{"style":156},[1006],{"type":66,"value":159},{"type":61,"tag":143,"props":1008,"children":1009},{"style":156},[1010],{"type":66,"value":164},{"type":61,"tag":143,"props":1012,"children":1013},{"style":156},[1014],{"type":66,"value":390},{"type":61,"tag":143,"props":1016,"children":1017},{"style":177},[1018],{"type":66,"value":180},{"type":61,"tag":143,"props":1020,"children":1021},{"style":156},[1022],{"type":66,"value":1023},"...",{"type":61,"tag":143,"props":1025,"children":1026},{"style":177},[1027],{"type":66,"value":610},{"type":61,"tag":143,"props":1029,"children":1030},{"style":256},[1031],{"type":66,"value":1032},"          # Execute Python code\n",{"type":61,"tag":143,"props":1034,"children":1035},{"class":145,"line":554},[1036,1040,1044,1048,1053],{"type":61,"tag":143,"props":1037,"children":1038},{"style":150},[1039],{"type":66,"value":153},{"type":61,"tag":143,"props":1041,"children":1042},{"style":156},[1043],{"type":66,"value":159},{"type":61,"tag":143,"props":1045,"children":1046},{"style":156},[1047],{"type":66,"value":164},{"type":61,"tag":143,"props":1049,"children":1050},{"style":156},[1051],{"type":66,"value":1052}," status",{"type":61,"tag":143,"props":1054,"children":1055},{"style":256},[1056],{"type":66,"value":1057},"              # Kernel status\n",{"type":61,"tag":143,"props":1059,"children":1061},{"class":145,"line":1060},5,[1062,1066,1070,1074,1079],{"type":61,"tag":143,"props":1063,"children":1064},{"style":150},[1065],{"type":66,"value":153},{"type":61,"tag":143,"props":1067,"children":1068},{"style":156},[1069],{"type":66,"value":159},{"type":61,"tag":143,"props":1071,"children":1072},{"style":156},[1073],{"type":66,"value":164},{"type":61,"tag":143,"props":1075,"children":1076},{"style":156},[1077],{"type":66,"value":1078}," restart",{"type":61,"tag":143,"props":1080,"children":1081},{"style":256},[1082],{"type":66,"value":1083},"             # Restart kernel\n",{"type":61,"tag":143,"props":1085,"children":1087},{"class":145,"line":1086},6,[1088,1092,1096,1100,1105],{"type":61,"tag":143,"props":1089,"children":1090},{"style":150},[1091],{"type":66,"value":153},{"type":61,"tag":143,"props":1093,"children":1094},{"style":156},[1095],{"type":66,"value":159},{"type":61,"tag":143,"props":1097,"children":1098},{"style":156},[1099],{"type":66,"value":164},{"type":61,"tag":143,"props":1101,"children":1102},{"style":156},[1103],{"type":66,"value":1104}," stop",{"type":61,"tag":143,"props":1106,"children":1107},{"style":256},[1108],{"type":66,"value":1109},"                # Stop kernel\n",{"type":61,"tag":143,"props":1111,"children":1113},{"class":145,"line":1112},7,[1114,1118,1122,1126,1131,1135,1140,1145,1149],{"type":61,"tag":143,"props":1115,"children":1116},{"style":150},[1117],{"type":66,"value":153},{"type":61,"tag":143,"props":1119,"children":1120},{"style":156},[1121],{"type":66,"value":159},{"type":61,"tag":143,"props":1123,"children":1124},{"style":156},[1125],{"type":66,"value":164},{"type":61,"tag":143,"props":1127,"children":1128},{"style":156},[1129],{"type":66,"value":1130}," install",{"type":61,"tag":143,"props":1132,"children":1133},{"style":177},[1134],{"type":66,"value":232},{"type":61,"tag":143,"props":1136,"children":1137},{"style":156},[1138],{"type":66,"value":1139},"pk",{"type":61,"tag":143,"props":1141,"children":1142},{"style":240},[1143],{"type":66,"value":1144},"g",{"type":61,"tag":143,"props":1146,"children":1147},{"style":177},[1148],{"type":66,"value":248},{"type":61,"tag":143,"props":1150,"children":1151},{"style":256},[1152],{"type":66,"value":1153},"       # Install package\n",{"type":61,"tag":918,"props":1155,"children":1157},{"id":1156},"concept-cache",[1158],{"type":66,"value":1159},"Concept Cache",{"type":61,"tag":132,"props":1161,"children":1163},{"className":134,"code":1162,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py concept lookup \u003Cname>                     # Look up\nuv run scripts\u002Fcli.py concept learn \u003Cname> \u003CTABLE> -k \u003CKEY_COL> # Learn\nuv run scripts\u002Fcli.py concept list                               # List all\nuv run scripts\u002Fcli.py concept import -p \u002Fpath\u002Fto\u002Fwarehouse.md   # Bulk import\n",[1164],{"type":61,"tag":74,"props":1165,"children":1166},{"__ignoreMap":137},[1167,1211,1291,1319],{"type":61,"tag":143,"props":1168,"children":1169},{"class":145,"line":146},[1170,1174,1178,1182,1186,1190,1194,1198,1202,1206],{"type":61,"tag":143,"props":1171,"children":1172},{"style":150},[1173],{"type":66,"value":153},{"type":61,"tag":143,"props":1175,"children":1176},{"style":156},[1177],{"type":66,"value":159},{"type":61,"tag":143,"props":1179,"children":1180},{"style":156},[1181],{"type":66,"value":164},{"type":61,"tag":143,"props":1183,"children":1184},{"style":156},[1185],{"type":66,"value":296},{"type":61,"tag":143,"props":1187,"children":1188},{"style":156},[1189],{"type":66,"value":174},{"type":61,"tag":143,"props":1191,"children":1192},{"style":177},[1193],{"type":66,"value":232},{"type":61,"tag":143,"props":1195,"children":1196},{"style":156},[1197],{"type":66,"value":237},{"type":61,"tag":143,"props":1199,"children":1200},{"style":240},[1201],{"type":66,"value":243},{"type":61,"tag":143,"props":1203,"children":1204},{"style":177},[1205],{"type":66,"value":248},{"type":61,"tag":143,"props":1207,"children":1208},{"style":256},[1209],{"type":66,"value":1210},"                     # Look up\n",{"type":61,"tag":143,"props":1212,"children":1213},{"class":145,"line":406},[1214,1218,1222,1226,1230,1234,1238,1242,1246,1250,1254,1258,1262,1266,1270,1274,1278,1282,1286],{"type":61,"tag":143,"props":1215,"children":1216},{"style":150},[1217],{"type":66,"value":153},{"type":61,"tag":143,"props":1219,"children":1220},{"style":156},[1221],{"type":66,"value":159},{"type":61,"tag":143,"props":1223,"children":1224},{"style":156},[1225],{"type":66,"value":164},{"type":61,"tag":143,"props":1227,"children":1228},{"style":156},[1229],{"type":66,"value":296},{"type":61,"tag":143,"props":1231,"children":1232},{"style":156},[1233],{"type":66,"value":485},{"type":61,"tag":143,"props":1235,"children":1236},{"style":177},[1237],{"type":66,"value":232},{"type":61,"tag":143,"props":1239,"children":1240},{"style":156},[1241],{"type":66,"value":237},{"type":61,"tag":143,"props":1243,"children":1244},{"style":240},[1245],{"type":66,"value":243},{"type":61,"tag":143,"props":1247,"children":1248},{"style":177},[1249],{"type":66,"value":248},{"type":61,"tag":143,"props":1251,"children":1252},{"style":177},[1253],{"type":66,"value":232},{"type":61,"tag":143,"props":1255,"children":1256},{"style":156},[1257],{"type":66,"value":510},{"type":61,"tag":143,"props":1259,"children":1260},{"style":240},[1261],{"type":66,"value":515},{"type":61,"tag":143,"props":1263,"children":1264},{"style":177},[1265],{"type":66,"value":248},{"type":61,"tag":143,"props":1267,"children":1268},{"style":156},[1269],{"type":66,"value":524},{"type":61,"tag":143,"props":1271,"children":1272},{"style":177},[1273],{"type":66,"value":232},{"type":61,"tag":143,"props":1275,"children":1276},{"style":156},[1277],{"type":66,"value":533},{"type":61,"tag":143,"props":1279,"children":1280},{"style":240},[1281],{"type":66,"value":538},{"type":61,"tag":143,"props":1283,"children":1284},{"style":177},[1285],{"type":66,"value":248},{"type":61,"tag":143,"props":1287,"children":1288},{"style":256},[1289],{"type":66,"value":1290}," # Learn\n",{"type":61,"tag":143,"props":1292,"children":1293},{"class":145,"line":545},[1294,1298,1302,1306,1310,1314],{"type":61,"tag":143,"props":1295,"children":1296},{"style":150},[1297],{"type":66,"value":153},{"type":61,"tag":143,"props":1299,"children":1300},{"style":156},[1301],{"type":66,"value":159},{"type":61,"tag":143,"props":1303,"children":1304},{"style":156},[1305],{"type":66,"value":164},{"type":61,"tag":143,"props":1307,"children":1308},{"style":156},[1309],{"type":66,"value":296},{"type":61,"tag":143,"props":1311,"children":1312},{"style":156},[1313],{"type":66,"value":955},{"type":61,"tag":143,"props":1315,"children":1316},{"style":256},[1317],{"type":66,"value":1318},"                               # List all\n",{"type":61,"tag":143,"props":1320,"children":1321},{"class":145,"line":554},[1322,1326,1330,1334,1338,1343,1348,1353],{"type":61,"tag":143,"props":1323,"children":1324},{"style":150},[1325],{"type":66,"value":153},{"type":61,"tag":143,"props":1327,"children":1328},{"style":156},[1329],{"type":66,"value":159},{"type":61,"tag":143,"props":1331,"children":1332},{"style":156},[1333],{"type":66,"value":164},{"type":61,"tag":143,"props":1335,"children":1336},{"style":156},[1337],{"type":66,"value":296},{"type":61,"tag":143,"props":1339,"children":1340},{"style":156},[1341],{"type":66,"value":1342}," import",{"type":61,"tag":143,"props":1344,"children":1345},{"style":156},[1346],{"type":66,"value":1347}," -p",{"type":61,"tag":143,"props":1349,"children":1350},{"style":156},[1351],{"type":66,"value":1352}," \u002Fpath\u002Fto\u002Fwarehouse.md",{"type":61,"tag":143,"props":1354,"children":1355},{"style":256},[1356],{"type":66,"value":1357},"   # Bulk import\n",{"type":61,"tag":918,"props":1359,"children":1361},{"id":1360},"pattern-cache",[1362],{"type":66,"value":1363},"Pattern Cache",{"type":61,"tag":132,"props":1365,"children":1367},{"className":134,"code":1366,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py pattern lookup \"question\"                                      # Look up\nuv run scripts\u002Fcli.py pattern learn \u003Cname> -q \"...\" -s \"...\" -t \"TABLE\" -g \"gotcha\"  # Learn\nuv run scripts\u002Fcli.py pattern record \u003Cname> --success                                # Record outcome\nuv run scripts\u002Fcli.py pattern list                                                   # List all\nuv run scripts\u002Fcli.py pattern delete \u003Cname>                                          # Delete\n",[1368],{"type":61,"tag":74,"props":1369,"children":1370},{"__ignoreMap":137},[1371,1411,1519,1567,1595],{"type":61,"tag":143,"props":1372,"children":1373},{"class":145,"line":146},[1374,1378,1382,1386,1390,1394,1398,1402,1406],{"type":61,"tag":143,"props":1375,"children":1376},{"style":150},[1377],{"type":66,"value":153},{"type":61,"tag":143,"props":1379,"children":1380},{"style":156},[1381],{"type":66,"value":159},{"type":61,"tag":143,"props":1383,"children":1384},{"style":156},[1385],{"type":66,"value":164},{"type":61,"tag":143,"props":1387,"children":1388},{"style":156},[1389],{"type":66,"value":169},{"type":61,"tag":143,"props":1391,"children":1392},{"style":156},[1393],{"type":66,"value":174},{"type":61,"tag":143,"props":1395,"children":1396},{"style":177},[1397],{"type":66,"value":180},{"type":61,"tag":143,"props":1399,"children":1400},{"style":156},[1401],{"type":66,"value":605},{"type":61,"tag":143,"props":1403,"children":1404},{"style":177},[1405],{"type":66,"value":610},{"type":61,"tag":143,"props":1407,"children":1408},{"style":256},[1409],{"type":66,"value":1410},"                                      # Look up\n",{"type":61,"tag":143,"props":1412,"children":1413},{"class":145,"line":406},[1414,1418,1422,1426,1430,1434,1438,1442,1446,1450,1454,1458,1462,1466,1470,1474,1478,1482,1486,1490,1494,1498,1502,1506,1510,1514],{"type":61,"tag":143,"props":1415,"children":1416},{"style":150},[1417],{"type":66,"value":153},{"type":61,"tag":143,"props":1419,"children":1420},{"style":156},[1421],{"type":66,"value":159},{"type":61,"tag":143,"props":1423,"children":1424},{"style":156},[1425],{"type":66,"value":164},{"type":61,"tag":143,"props":1427,"children":1428},{"style":156},[1429],{"type":66,"value":169},{"type":61,"tag":143,"props":1431,"children":1432},{"style":156},[1433],{"type":66,"value":485},{"type":61,"tag":143,"props":1435,"children":1436},{"style":177},[1437],{"type":66,"value":232},{"type":61,"tag":143,"props":1439,"children":1440},{"style":156},[1441],{"type":66,"value":237},{"type":61,"tag":143,"props":1443,"children":1444},{"style":240},[1445],{"type":66,"value":243},{"type":61,"tag":143,"props":1447,"children":1448},{"style":177},[1449],{"type":66,"value":248},{"type":61,"tag":143,"props":1451,"children":1452},{"style":156},[1453],{"type":66,"value":596},{"type":61,"tag":143,"props":1455,"children":1456},{"style":177},[1457],{"type":66,"value":180},{"type":61,"tag":143,"props":1459,"children":1460},{"style":156},[1461],{"type":66,"value":1023},{"type":61,"tag":143,"props":1463,"children":1464},{"style":177},[1465],{"type":66,"value":610},{"type":61,"tag":143,"props":1467,"children":1468},{"style":156},[1469],{"type":66,"value":615},{"type":61,"tag":143,"props":1471,"children":1472},{"style":177},[1473],{"type":66,"value":180},{"type":61,"tag":143,"props":1475,"children":1476},{"style":156},[1477],{"type":66,"value":1023},{"type":61,"tag":143,"props":1479,"children":1480},{"style":177},[1481],{"type":66,"value":610},{"type":61,"tag":143,"props":1483,"children":1484},{"style":156},[1485],{"type":66,"value":633},{"type":61,"tag":143,"props":1487,"children":1488},{"style":177},[1489],{"type":66,"value":180},{"type":61,"tag":143,"props":1491,"children":1492},{"style":156},[1493],{"type":66,"value":642},{"type":61,"tag":143,"props":1495,"children":1496},{"style":177},[1497],{"type":66,"value":610},{"type":61,"tag":143,"props":1499,"children":1500},{"style":156},[1501],{"type":66,"value":651},{"type":61,"tag":143,"props":1503,"children":1504},{"style":177},[1505],{"type":66,"value":180},{"type":61,"tag":143,"props":1507,"children":1508},{"style":156},[1509],{"type":66,"value":660},{"type":61,"tag":143,"props":1511,"children":1512},{"style":177},[1513],{"type":66,"value":610},{"type":61,"tag":143,"props":1515,"children":1516},{"style":256},[1517],{"type":66,"value":1518},"  # Learn\n",{"type":61,"tag":143,"props":1520,"children":1521},{"class":145,"line":545},[1522,1526,1530,1534,1538,1542,1546,1550,1554,1558,1562],{"type":61,"tag":143,"props":1523,"children":1524},{"style":150},[1525],{"type":66,"value":153},{"type":61,"tag":143,"props":1527,"children":1528},{"style":156},[1529],{"type":66,"value":159},{"type":61,"tag":143,"props":1531,"children":1532},{"style":156},[1533],{"type":66,"value":164},{"type":61,"tag":143,"props":1535,"children":1536},{"style":156},[1537],{"type":66,"value":169},{"type":61,"tag":143,"props":1539,"children":1540},{"style":156},[1541],{"type":66,"value":227},{"type":61,"tag":143,"props":1543,"children":1544},{"style":177},[1545],{"type":66,"value":232},{"type":61,"tag":143,"props":1547,"children":1548},{"style":156},[1549],{"type":66,"value":237},{"type":61,"tag":143,"props":1551,"children":1552},{"style":240},[1553],{"type":66,"value":243},{"type":61,"tag":143,"props":1555,"children":1556},{"style":177},[1557],{"type":66,"value":248},{"type":61,"tag":143,"props":1559,"children":1560},{"style":156},[1561],{"type":66,"value":253},{"type":61,"tag":143,"props":1563,"children":1564},{"style":256},[1565],{"type":66,"value":1566},"                                # Record outcome\n",{"type":61,"tag":143,"props":1568,"children":1569},{"class":145,"line":554},[1570,1574,1578,1582,1586,1590],{"type":61,"tag":143,"props":1571,"children":1572},{"style":150},[1573],{"type":66,"value":153},{"type":61,"tag":143,"props":1575,"children":1576},{"style":156},[1577],{"type":66,"value":159},{"type":61,"tag":143,"props":1579,"children":1580},{"style":156},[1581],{"type":66,"value":164},{"type":61,"tag":143,"props":1583,"children":1584},{"style":156},[1585],{"type":66,"value":169},{"type":61,"tag":143,"props":1587,"children":1588},{"style":156},[1589],{"type":66,"value":955},{"type":61,"tag":143,"props":1591,"children":1592},{"style":256},[1593],{"type":66,"value":1594},"                                                   # List all\n",{"type":61,"tag":143,"props":1596,"children":1597},{"class":145,"line":1060},[1598,1602,1606,1610,1614,1619,1623,1627,1631,1635],{"type":61,"tag":143,"props":1599,"children":1600},{"style":150},[1601],{"type":66,"value":153},{"type":61,"tag":143,"props":1603,"children":1604},{"style":156},[1605],{"type":66,"value":159},{"type":61,"tag":143,"props":1607,"children":1608},{"style":156},[1609],{"type":66,"value":164},{"type":61,"tag":143,"props":1611,"children":1612},{"style":156},[1613],{"type":66,"value":169},{"type":61,"tag":143,"props":1615,"children":1616},{"style":156},[1617],{"type":66,"value":1618}," delete",{"type":61,"tag":143,"props":1620,"children":1621},{"style":177},[1622],{"type":66,"value":232},{"type":61,"tag":143,"props":1624,"children":1625},{"style":156},[1626],{"type":66,"value":237},{"type":61,"tag":143,"props":1628,"children":1629},{"style":240},[1630],{"type":66,"value":243},{"type":61,"tag":143,"props":1632,"children":1633},{"style":177},[1634],{"type":66,"value":248},{"type":61,"tag":143,"props":1636,"children":1637},{"style":256},[1638],{"type":66,"value":1639},"                                          # Delete\n",{"type":61,"tag":918,"props":1641,"children":1643},{"id":1642},"table-schema-cache",[1644],{"type":66,"value":1645},"Table Schema Cache",{"type":61,"tag":132,"props":1647,"children":1649},{"className":134,"code":1648,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py table lookup \u003CTABLE>            # Look up schema\nuv run scripts\u002Fcli.py table cache \u003CTABLE> -c '[...]'  # Cache schema\nuv run scripts\u002Fcli.py table list                       # List cached\nuv run scripts\u002Fcli.py table delete \u003CTABLE>             # Delete\n",[1650],{"type":61,"tag":74,"props":1651,"children":1652},{"__ignoreMap":137},[1653,1698,1763,1791],{"type":61,"tag":143,"props":1654,"children":1655},{"class":145,"line":146},[1656,1660,1664,1668,1673,1677,1681,1685,1689,1693],{"type":61,"tag":143,"props":1657,"children":1658},{"style":150},[1659],{"type":66,"value":153},{"type":61,"tag":143,"props":1661,"children":1662},{"style":156},[1663],{"type":66,"value":159},{"type":61,"tag":143,"props":1665,"children":1666},{"style":156},[1667],{"type":66,"value":164},{"type":61,"tag":143,"props":1669,"children":1670},{"style":156},[1671],{"type":66,"value":1672}," table",{"type":61,"tag":143,"props":1674,"children":1675},{"style":156},[1676],{"type":66,"value":174},{"type":61,"tag":143,"props":1678,"children":1679},{"style":177},[1680],{"type":66,"value":232},{"type":61,"tag":143,"props":1682,"children":1683},{"style":156},[1684],{"type":66,"value":510},{"type":61,"tag":143,"props":1686,"children":1687},{"style":240},[1688],{"type":66,"value":515},{"type":61,"tag":143,"props":1690,"children":1691},{"style":177},[1692],{"type":66,"value":248},{"type":61,"tag":143,"props":1694,"children":1695},{"style":256},[1696],{"type":66,"value":1697},"            # Look up schema\n",{"type":61,"tag":143,"props":1699,"children":1700},{"class":145,"line":406},[1701,1705,1709,1713,1717,1722,1726,1730,1734,1738,1743,1748,1753,1758],{"type":61,"tag":143,"props":1702,"children":1703},{"style":150},[1704],{"type":66,"value":153},{"type":61,"tag":143,"props":1706,"children":1707},{"style":156},[1708],{"type":66,"value":159},{"type":61,"tag":143,"props":1710,"children":1711},{"style":156},[1712],{"type":66,"value":164},{"type":61,"tag":143,"props":1714,"children":1715},{"style":156},[1716],{"type":66,"value":1672},{"type":61,"tag":143,"props":1718,"children":1719},{"style":156},[1720],{"type":66,"value":1721}," cache",{"type":61,"tag":143,"props":1723,"children":1724},{"style":177},[1725],{"type":66,"value":232},{"type":61,"tag":143,"props":1727,"children":1728},{"style":156},[1729],{"type":66,"value":510},{"type":61,"tag":143,"props":1731,"children":1732},{"style":240},[1733],{"type":66,"value":515},{"type":61,"tag":143,"props":1735,"children":1736},{"style":177},[1737],{"type":66,"value":248},{"type":61,"tag":143,"props":1739,"children":1740},{"style":156},[1741],{"type":66,"value":1742}," -c",{"type":61,"tag":143,"props":1744,"children":1745},{"style":177},[1746],{"type":66,"value":1747}," '",{"type":61,"tag":143,"props":1749,"children":1750},{"style":156},[1751],{"type":66,"value":1752},"[...]",{"type":61,"tag":143,"props":1754,"children":1755},{"style":177},[1756],{"type":66,"value":1757},"'",{"type":61,"tag":143,"props":1759,"children":1760},{"style":256},[1761],{"type":66,"value":1762},"  # Cache schema\n",{"type":61,"tag":143,"props":1764,"children":1765},{"class":145,"line":545},[1766,1770,1774,1778,1782,1786],{"type":61,"tag":143,"props":1767,"children":1768},{"style":150},[1769],{"type":66,"value":153},{"type":61,"tag":143,"props":1771,"children":1772},{"style":156},[1773],{"type":66,"value":159},{"type":61,"tag":143,"props":1775,"children":1776},{"style":156},[1777],{"type":66,"value":164},{"type":61,"tag":143,"props":1779,"children":1780},{"style":156},[1781],{"type":66,"value":1672},{"type":61,"tag":143,"props":1783,"children":1784},{"style":156},[1785],{"type":66,"value":955},{"type":61,"tag":143,"props":1787,"children":1788},{"style":256},[1789],{"type":66,"value":1790},"                       # List cached\n",{"type":61,"tag":143,"props":1792,"children":1793},{"class":145,"line":554},[1794,1798,1802,1806,1810,1814,1818,1822,1826,1830],{"type":61,"tag":143,"props":1795,"children":1796},{"style":150},[1797],{"type":66,"value":153},{"type":61,"tag":143,"props":1799,"children":1800},{"style":156},[1801],{"type":66,"value":159},{"type":61,"tag":143,"props":1803,"children":1804},{"style":156},[1805],{"type":66,"value":164},{"type":61,"tag":143,"props":1807,"children":1808},{"style":156},[1809],{"type":66,"value":1672},{"type":61,"tag":143,"props":1811,"children":1812},{"style":156},[1813],{"type":66,"value":1618},{"type":61,"tag":143,"props":1815,"children":1816},{"style":177},[1817],{"type":66,"value":232},{"type":61,"tag":143,"props":1819,"children":1820},{"style":156},[1821],{"type":66,"value":510},{"type":61,"tag":143,"props":1823,"children":1824},{"style":240},[1825],{"type":66,"value":515},{"type":61,"tag":143,"props":1827,"children":1828},{"style":177},[1829],{"type":66,"value":248},{"type":61,"tag":143,"props":1831,"children":1832},{"style":256},[1833],{"type":66,"value":1834},"             # Delete\n",{"type":61,"tag":918,"props":1836,"children":1838},{"id":1837},"cache-management",[1839],{"type":66,"value":1840},"Cache Management",{"type":61,"tag":132,"props":1842,"children":1844},{"className":134,"code":1843,"language":136,"meta":137,"style":137},"uv run scripts\u002Fcli.py cache status                # Stats\nuv run scripts\u002Fcli.py cache clear [--stale-only]  # Clear\n",[1845],{"type":61,"tag":74,"props":1846,"children":1847},{"__ignoreMap":137},[1848,1876],{"type":61,"tag":143,"props":1849,"children":1850},{"class":145,"line":146},[1851,1855,1859,1863,1867,1871],{"type":61,"tag":143,"props":1852,"children":1853},{"style":150},[1854],{"type":66,"value":153},{"type":61,"tag":143,"props":1856,"children":1857},{"style":156},[1858],{"type":66,"value":159},{"type":61,"tag":143,"props":1860,"children":1861},{"style":156},[1862],{"type":66,"value":164},{"type":61,"tag":143,"props":1864,"children":1865},{"style":156},[1866],{"type":66,"value":1721},{"type":61,"tag":143,"props":1868,"children":1869},{"style":156},[1870],{"type":66,"value":1052},{"type":61,"tag":143,"props":1872,"children":1873},{"style":256},[1874],{"type":66,"value":1875},"                # Stats\n",{"type":61,"tag":143,"props":1877,"children":1878},{"class":145,"line":406},[1879,1883,1887,1891,1895,1900,1905],{"type":61,"tag":143,"props":1880,"children":1881},{"style":150},[1882],{"type":66,"value":153},{"type":61,"tag":143,"props":1884,"children":1885},{"style":156},[1886],{"type":66,"value":159},{"type":61,"tag":143,"props":1888,"children":1889},{"style":156},[1890],{"type":66,"value":164},{"type":61,"tag":143,"props":1892,"children":1893},{"style":156},[1894],{"type":66,"value":1721},{"type":61,"tag":143,"props":1896,"children":1897},{"style":156},[1898],{"type":66,"value":1899}," clear",{"type":61,"tag":143,"props":1901,"children":1902},{"style":240},[1903],{"type":66,"value":1904}," [--stale-only]  ",{"type":61,"tag":143,"props":1906,"children":1907},{"style":256},[1908],{"type":66,"value":1909},"# Clear\n",{"type":61,"tag":110,"props":1911,"children":1913},{"id":1912},"references",[1914],{"type":66,"value":1915},"References",{"type":61,"tag":1917,"props":1918,"children":1919},"ul",{},[1920,1929],{"type":61,"tag":121,"props":1921,"children":1922},{},[1923,1927],{"type":61,"tag":347,"props":1924,"children":1925},{"href":349},[1926],{"type":66,"value":349},{"type":66,"value":1928}," — Large table handling, warehouse exploration, INFORMATION_SCHEMA queries",{"type":61,"tag":121,"props":1930,"children":1931},{},[1932,1937],{"type":61,"tag":347,"props":1933,"children":1935},{"href":1934},"reference\u002Fcommon-patterns.md",[1936],{"type":66,"value":1934},{"type":66,"value":1938}," — SQL templates for trends, comparisons, top-N, distributions, cohorts",{"type":61,"tag":1940,"props":1941,"children":1942},"style",{},[1943],{"type":66,"value":1944},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":1946,"total":2104},[1947,1964,1976,1993,2006,2013,2026,2039,2054,2068,2078,2091],{"slug":35,"name":35,"fn":1948,"description":1949,"org":1950,"tags":1951,"stars":25,"repoUrl":26,"updatedAt":1963},"manage and troubleshoot Airflow via CLI","Queries, manages, and troubleshoots Apache Airflow using the `af` CLI. Use when working with anything related to Airflow - a DAG, a DAG run, a task log, an import or parse error, a broken DAG, or any Airflow operation. Covers listing and triggering DAGs, retrying runs, reading task logs, diagnosing failures, debugging import and parse errors, checking connections, variables and pools, exploring the REST API, and monitoring health (for example \"trigger a pipeline\", \"retry a run\", \"list connections\", \"check Airflow health\", \"why did my DAG fail\"). This is the entrypoint that routes to sibling skills for authoring, testing, deploying, and migrating Airflow 2 to 3. Not for warehouse\u002FSQL analytics on Airflow metadata tables (use analyzing-data); for deep root-cause reports use debugging-dags or airflow-investigation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1952,1954,1957,1960],{"name":1953,"slug":35,"type":15},"Airflow",{"name":1955,"slug":1956,"type":15},"CLI","cli",{"name":1958,"slug":1959,"type":15},"Data Pipeline","data-pipeline",{"name":1961,"slug":1962,"type":15},"Debugging","debugging","2026-04-06T18:01:43.992997",{"slug":1965,"name":1965,"fn":1966,"description":1967,"org":1968,"tags":1969,"stars":25,"repoUrl":26,"updatedAt":1975},"airflow-hitl","add human-in-the-loop steps to Airflow DAGs","Builds human-in-the-loop (HITL) Airflow workflows - approval gates, form input, and human-driven branching. Use when a DAG needs a human in the loop - an approval or reject step, sign-off before a task runs, a decision or approval UI, branching on a human choice, or collecting form input mid-run; also on mentions of ApprovalOperator, HITLOperator, HITLBranchOperator, HITLEntryOperator, or HITLTrigger. Requires Airflow 3.1+. Not for AI\u002FLLM task calls (see migrating-ai-sdk-to-common-ai).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1970,1971,1974],{"name":1953,"slug":35,"type":15},{"name":1972,"slug":1973,"type":15},"Approvals","approvals",{"name":1958,"slug":1959,"type":15},"2026-04-06T18:01:46.758548",{"slug":1977,"name":1977,"fn":1978,"description":1979,"org":1980,"tags":1981,"stars":25,"repoUrl":26,"updatedAt":1992},"airflow-plugins","build Airflow UI plugins","Builds Airflow 3.1+ plugins that embed FastAPI apps, custom UI pages, React components, middleware, macros, and operator links directly into the Airflow UI. Use when building anything custom inside Airflow 3.1+ that involves Python and a browser-facing interface - creating an Airflow plugin, adding a custom UI page or nav entry, building FastAPI-backed endpoints inside Airflow, serving static assets from a plugin, embedding a React app, adding middleware to the API server, creating custom operator extra links, or calling the Airflow REST API from inside a plugin; also when AirflowPlugin, fastapi_apps, external_views, react_apps, or plugin registration come up.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1982,1983,1986,1989],{"name":1953,"slug":35,"type":15},{"name":1984,"slug":1985,"type":15},"Plugin Development","plugin-development",{"name":1987,"slug":1988,"type":15},"Python","python",{"name":1990,"slug":1991,"type":15},"UI Components","ui-components","2026-04-06T18:01:56.827891",{"slug":1994,"name":1994,"fn":1995,"description":1996,"org":1997,"tags":1998,"stars":25,"repoUrl":26,"updatedAt":2005},"airflow-state-store","persist Airflow task and asset state","Persists task and asset state across retries and DAG runs using Airflow 3.3's AIP-103 key\u002Fvalue stores (`task_state_store`, `asset_state_store`) and the crash-safe `ResumableJobMixin`. Use when the user asks about task state store, checkpointing in tasks, persisting state across retries, job IDs surviving worker crashes, watermarks, asset metadata, resumable tasks, crash-safe operators, or \"what's new in Airflow 3.3\". Also use proactively when reading a DAG that uses Variables or XCom for intra-task coordination state — flag the anti-pattern and recommend task_state_store or asset_state_store instead. Requires Airflow 3.3+.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1999,2000,2001,2002],{"name":1953,"slug":35,"type":15},{"name":13,"slug":14,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2003,"slug":2004,"type":15},"Operations","operations","2026-07-07T06:43:11.160671",{"slug":4,"name":4,"fn":5,"description":6,"org":2007,"tags":2008,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2009,2010,2011,2012],{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":23,"slug":24,"type":15},{"slug":2014,"name":2014,"fn":2015,"description":2016,"org":2017,"tags":2018,"stars":25,"repoUrl":26,"updatedAt":2025},"annotating-task-lineage","annotate Airflow tasks with data lineage","Annotate Airflow tasks with data lineage using inlets and outlets. Use when the user wants to add lineage metadata to tasks, specify input\u002Foutput datasets, or enable lineage tracking for operators without built-in OpenLineage extraction.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2019,2020,2021,2022],{"name":1953,"slug":35,"type":15},{"name":13,"slug":14,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2023,"slug":2024,"type":15},"Observability","observability","2026-04-06T18:02:03.487365",{"slug":2027,"name":2027,"fn":2028,"description":2029,"org":2030,"tags":2031,"stars":25,"repoUrl":26,"updatedAt":2038},"authoring-dags","author Airflow DAGs","Workflow and best practices for writing Apache Airflow DAGs. Use when creating a new DAG, write pipeline code, handling questions about DAG patterns and conventions or extending an existing DAG with a follow-up\u002Fdownstream task. ANY request shaped like 'add a DAG named X', 'write a pipeline', 'add a task that runs after Y', or 'extend the DAG'. For testing and debugging DAGs, see the testing-dags skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2032,2033,2034,2037],{"name":1953,"slug":35,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2035,"slug":2036,"type":15},"ETL","etl",{"name":1987,"slug":1988,"type":15},"2026-04-06T18:01:52.679888",{"slug":2040,"name":2040,"fn":2041,"description":2042,"org":2043,"tags":2044,"stars":25,"repoUrl":26,"updatedAt":2053},"authoring-go-sdk-tasks","implement Airflow tasks in Go","Writes Airflow task logic in Go using the Airflow Go SDK. Use when the user wants to implement Airflow tasks in Go, asks about `BundleProvider`\u002F`RegisterDags`, the `bundlev1` Registry\u002FDag interfaces, registering Go tasks (`AddTask`\u002F`AddTaskWithName`), dependency injection by parameter type (`context.Context`, `sdk.TIRunContext`, `*slog.Logger`, `sdk.Client`), or reading connections\u002Fvariables\u002FXComs from Go. This skill covers the Go-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building\u002Fpacking\u002Fshipping the bundle see deploying-go-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2045,2046,2049,2050],{"name":1953,"slug":35,"type":15},{"name":2047,"slug":2048,"type":15},"API Development","api-development",{"name":1958,"slug":1959,"type":15},{"name":2051,"slug":2052,"type":15},"Go","go","2026-07-11T05:39:13.552213",{"slug":2055,"name":2055,"fn":2056,"description":2057,"org":2058,"tags":2059,"stars":25,"repoUrl":26,"updatedAt":2067},"authoring-java-sdk-tasks","implement Airflow tasks in Java","Writes Airflow task logic in Java, Kotlin, or any JVM language using the Airflow Java SDK. Use when the user wants to implement Airflow tasks in Java\u002FJVM, asks about `@Builder.Dag`\u002F`@Builder.Task`\u002F`@Builder.XCom`, the `Task`\u002F`BundleBuilder` interfaces, reading connections\u002Fvariables\u002FXComs from Java, the JSON-to-Java type mapping, or logging from Java tasks. This skill covers the Java-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building\u002Fshipping the bundle see deploying-java-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2060,2061,2064],{"name":1958,"slug":1959,"type":15},{"name":2062,"slug":2063,"type":15},"Engineering","engineering",{"name":2065,"slug":2066,"type":15},"Java","java","2026-07-18T05:48:13.374003",{"slug":2069,"name":2069,"fn":2070,"description":2071,"org":2072,"tags":2073,"stars":25,"repoUrl":26,"updatedAt":2077},"authoring-language-sdk-tasks","implement non-Python Airflow tasks","The language-neutral foundation for Airflow language SDKs — implement task logic in a non-Python language while the DAG stays in Python. Use when the user wants to run an Airflow task in another language (Java, Kotlin, Go, or other JVM\u002Fnative languages), asks how the Python `@task.stub` pairs with native task code, how task\u002FDAG IDs must match across the two sides, how data passes via XCom as JSON, or which language SDKs exist. This skill owns the shared Python-stub pattern and conceptual model; for a specific language's native API, build, and runtime, use that language's skill (e.g. authoring-java-sdk-tasks, authoring-go-sdk-tasks).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2074,2075,2076],{"name":1953,"slug":35,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2062,"slug":2063,"type":15},"2026-07-18T05:11:54.496539",{"slug":2079,"name":2079,"fn":2080,"description":2081,"org":2082,"tags":2083,"stars":25,"repoUrl":26,"updatedAt":2090},"blueprint","build reusable Airflow task group templates","Define reusable Airflow task group templates with Pydantic validation and compose DAGs from YAML. Use when creating blueprint templates, composing DAGs from YAML, validating configurations, or enabling no-code DAG authoring for non-engineers.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2084,2085,2086,2087],{"name":1953,"slug":35,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2035,"slug":2036,"type":15},{"name":2088,"slug":2089,"type":15},"Templates","templates","2026-04-06T18:01:45.361425",{"slug":2092,"name":2092,"fn":2093,"description":2094,"org":2095,"tags":2096,"stars":25,"repoUrl":26,"updatedAt":2103},"checking-freshness","check data freshness in warehouses","Quick data freshness check. Use when the user asks if data is up to date, when a table was last updated, if data is stale, or needs to verify data currency before using it.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2097,2098,2099,2102],{"name":1953,"slug":35,"type":15},{"name":13,"slug":14,"type":15},{"name":2100,"slug":2101,"type":15},"Data Quality","data-quality",{"name":2035,"slug":2036,"type":15},"2026-04-06T18:02:02.138565",34,{"items":2106,"total":2104},[2107,2114,2120,2127,2134,2141,2148],{"slug":35,"name":35,"fn":1948,"description":1949,"org":2108,"tags":2109,"stars":25,"repoUrl":26,"updatedAt":1963},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2110,2111,2112,2113],{"name":1953,"slug":35,"type":15},{"name":1955,"slug":1956,"type":15},{"name":1958,"slug":1959,"type":15},{"name":1961,"slug":1962,"type":15},{"slug":1965,"name":1965,"fn":1966,"description":1967,"org":2115,"tags":2116,"stars":25,"repoUrl":26,"updatedAt":1975},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2117,2118,2119],{"name":1953,"slug":35,"type":15},{"name":1972,"slug":1973,"type":15},{"name":1958,"slug":1959,"type":15},{"slug":1977,"name":1977,"fn":1978,"description":1979,"org":2121,"tags":2122,"stars":25,"repoUrl":26,"updatedAt":1992},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2123,2124,2125,2126],{"name":1953,"slug":35,"type":15},{"name":1984,"slug":1985,"type":15},{"name":1987,"slug":1988,"type":15},{"name":1990,"slug":1991,"type":15},{"slug":1994,"name":1994,"fn":1995,"description":1996,"org":2128,"tags":2129,"stars":25,"repoUrl":26,"updatedAt":2005},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2130,2131,2132,2133],{"name":1953,"slug":35,"type":15},{"name":13,"slug":14,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2003,"slug":2004,"type":15},{"slug":4,"name":4,"fn":5,"description":6,"org":2135,"tags":2136,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2137,2138,2139,2140],{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"name":23,"slug":24,"type":15},{"slug":2014,"name":2014,"fn":2015,"description":2016,"org":2142,"tags":2143,"stars":25,"repoUrl":26,"updatedAt":2025},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2144,2145,2146,2147],{"name":1953,"slug":35,"type":15},{"name":13,"slug":14,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2023,"slug":2024,"type":15},{"slug":2027,"name":2027,"fn":2028,"description":2029,"org":2149,"tags":2150,"stars":25,"repoUrl":26,"updatedAt":2038},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2151,2152,2153,2154],{"name":1953,"slug":35,"type":15},{"name":1958,"slug":1959,"type":15},{"name":2035,"slug":2036,"type":15},{"name":1987,"slug":1988,"type":15}]