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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.\nhooks:\n  Stop:\n    - hooks:\n        - type: command\n          command: \"echo 'Remember to test your DAG with the testing-dags skill'\"\n---\n\n# DAG Authoring Skill\n\nThis skill guides you through creating and validating Airflow DAGs using best practices and `af` CLI commands.\n\n> **For testing and debugging DAGs**, see the **testing-dags** skill which covers the full test -> debug -> fix -> retest workflow.\n\n---\n\n## Running the CLI\n\nThese commands assume `af` is on PATH. Run via `astro otto` to get it automatically, or install standalone with `uv tool install astro-airflow-mcp`.\n\n---\n\n## Workflow Overview\n\n```\n+-----------------------------------------+\n| 1. DISCOVER                             |\n|    Understand codebase & environment    |\n+-----------------------------------------+\n                 |\n+-----------------------------------------+\n| 2. PLAN                                 |\n|    Propose structure, get approval      |\n+-----------------------------------------+\n                 |\n+-----------------------------------------+\n| 3. IMPLEMENT                            |\n|    Write DAG following patterns         |\n+-----------------------------------------+\n                 |\n+-----------------------------------------+\n| 4. VALIDATE                             |\n|    Check import errors, warnings        |\n+-----------------------------------------+\n                 |\n+-----------------------------------------+\n| 5. TEST (with user consent)             |\n|    Trigger, monitor, check logs         |\n+-----------------------------------------+\n                 |\n+-----------------------------------------+\n| 6. ITERATE                              |\n|    Fix issues, re-validate              |\n+-----------------------------------------+\n```\n\n---\n\n## Phase 1: Discover\n\nBefore writing code, understand the context.\n\n### Explore the Codebase\n\nUse file tools to find existing patterns:\n- `Glob` for `**\u002Fdags\u002F**\u002F*.py` to find existing DAGs\n- `Read` similar DAGs to understand conventions\n- Check `requirements.txt` for available packages\n\n### Query the Airflow Environment\n\nUse `af` CLI commands to understand what's available:\n\n| Command | Purpose |\n|---------|---------|\n| `af config connections` | What external systems are configured |\n| `af config variables` | What configuration values exist |\n| `af config providers` | What operator packages are installed |\n| `af config version` | Version constraints and features |\n| `af dags list` | Existing DAGs and naming conventions |\n| `af config pools` | Resource pools for concurrency |\n\n**Example discovery questions:**\n- \"Is there a Snowflake connection?\" -> `af config connections`\n- \"What Airflow version?\" -> `af config version`\n- \"Are S3 operators available?\" -> `af config providers`\n\n---\n\n## Phase 2: Plan\n\nBased on discovery, propose:\n\n1. **DAG structure** - Tasks, dependencies, schedule\n2. **Operators to use** - Based on available providers\n3. **Connections needed** - Existing or to be created\n4. **Variables needed** - Existing or to be created\n5. **Packages needed** - Additions to requirements.txt\n\n**Get user approval before implementing.**\n\n---\n\n## Phase 3: Implement\n\nWrite the DAG following best practices (see below). Key steps:\n\n1. Create DAG file in appropriate location\n2. Update `requirements.txt` if needed\n3. Save the file\n\n---\n\n## Phase 4: Validate\n\n**Use `af` CLI as a feedback loop to validate your DAG.**\n\n### Step 1: Check Import Errors\n\nAfter saving, check for parse errors (Airflow will have already parsed the file):\n\n```bash\naf dags errors\n```\n\n- If your file appears -> **fix and retry**\n- If no errors -> **continue**\n\nCommon causes: missing imports, syntax errors, missing packages.\n\n### Step 2: Verify DAG Exists\n\n```bash\naf dags get \u003Cdag_id>\n```\n\nCheck: DAG exists, schedule correct, tags set, paused status.\n\n### Step 3: Check Warnings\n\n```bash\naf dags warnings\n```\n\nLook for deprecation warnings or configuration issues.\n\n### Step 4: Explore DAG Structure\n\n```bash\naf dags explore \u003Cdag_id>\n```\n\nReturns in one call: metadata, tasks, dependencies, source code.\n\n### On Astro\n\nIf you're running on Astro, you can also validate locally before deploying:\n\n- **Parse check**: Run `astro dev parse` to catch import errors and DAG-level issues without starting a full Airflow environment\n- **DAG-only deploy**: Once validated, use `astro deploy --dags` for fast DAG-only deploys that skip the Docker image build — ideal for iterating on DAG code\n\n---\n\n## Phase 5: Test\n\n> See the **testing-dags** skill for comprehensive testing guidance.\n\nOnce validation passes, test the DAG using the workflow in the **testing-dags** skill:\n\n1. **Get user consent** -- Always ask before triggering\n2. **Trigger and wait** -- `af runs trigger-wait \u003Cdag_id> --timeout 300`\n3. **Analyze results** -- Check success\u002Ffailure status\n4. **Debug if needed** -- `af runs diagnose \u003Cdag_id> \u003Crun_id>` and `af tasks logs \u003Cdag_id> \u003Crun_id> \u003Ctask_id>`\n\n### Quick Test (Minimal)\n\n```bash\n# Ask user first, then:\naf runs trigger-wait \u003Cdag_id> --timeout 300\n```\n\nFor the full test -> debug -> fix -> retest loop, see **testing-dags**.\n\n---\n\n## Phase 6: Iterate\n\nIf issues found:\n1. Fix the code\n2. Check for import errors: `af dags errors`\n3. Re-validate (Phase 4)\n4. Re-test using the **testing-dags** skill workflow (Phase 5)\n\n---\n\n## CLI Quick Reference\n\n| Phase | Command | Purpose |\n|-------|---------|---------|\n| Discover | `af config connections` | Available connections |\n| Discover | `af config variables` | Configuration values |\n| Discover | `af config providers` | Installed operators |\n| Discover | `af config version` | Version info |\n| Validate | `af dags errors` | Parse errors (check first!) |\n| Validate | `af dags get \u003Cdag_id>` | Verify DAG config |\n| Validate | `af dags warnings` | Configuration warnings |\n| Validate | `af dags explore \u003Cdag_id>` | Full DAG inspection |\n\n> **Testing commands** -- See the **testing-dags** skill for `af runs trigger-wait`, `af runs diagnose`, `af tasks logs`, etc.\n\n---\n\n## Best Practices & Anti-Patterns\n\nFor code patterns and anti-patterns, see **[reference\u002Fbest-practices.md](reference\u002Fbest-practices.md)**.\n\n**Read this reference when writing new DAGs or reviewing existing ones.** It covers what patterns are correct (including Airflow 3-specific behavior) and what to avoid.\n\n---\n\n## Related Skills\n\n- **testing-dags**: For testing DAGs, debugging failures, and the test -> fix -> retest loop\n- **debugging-dags**: For troubleshooting failed DAGs\n- **deploying-airflow**: For deploying DAGs to production (Astro or open-source)\n- **migrating-airflow-2-to-3**: For migrating DAGs to Airflow 3\n",{"data":56,"body":64},{"name":4,"description":6,"hooks":57},{"Stop":58},[59],{"hooks":60},[61],{"type":62,"command":63},"command","echo 'Remember to test your DAG with the testing-dags skill'",{"type":65,"children":66},"root",[67,76,91,113,117,124,152,155,161,173,176,182,187,194,199,247,253,265,395,403,436,439,445,450,503,511,514,520,525,550,553,559,573,579,584,615,638,643,649,694,699,705,728,733,739,778,783,789,794,833,836,842,856,867,929,935,997,1007,1010,1016,1021,1056,1059,1065,1255,1297,1300,1306,1321,1331,1334,1340,1382],{"type":68,"tag":69,"props":70,"children":72},"element","h1",{"id":71},"dag-authoring-skill",[73],{"type":74,"value":75},"text","DAG Authoring Skill",{"type":68,"tag":77,"props":78,"children":79},"p",{},[80,82,89],{"type":74,"value":81},"This skill guides you through creating and validating Airflow DAGs using best practices and ",{"type":68,"tag":83,"props":84,"children":86},"code",{"className":85},[],[87],{"type":74,"value":88},"af",{"type":74,"value":90}," CLI commands.",{"type":68,"tag":92,"props":93,"children":94},"blockquote",{},[95],{"type":68,"tag":77,"props":96,"children":97},{},[98,104,106,111],{"type":68,"tag":99,"props":100,"children":101},"strong",{},[102],{"type":74,"value":103},"For testing and debugging DAGs",{"type":74,"value":105},", see the ",{"type":68,"tag":99,"props":107,"children":108},{},[109],{"type":74,"value":110},"testing-dags",{"type":74,"value":112}," skill which covers the full test -> debug -> fix -> retest workflow.",{"type":68,"tag":114,"props":115,"children":116},"hr",{},[],{"type":68,"tag":118,"props":119,"children":121},"h2",{"id":120},"running-the-cli",[122],{"type":74,"value":123},"Running the CLI",{"type":68,"tag":77,"props":125,"children":126},{},[127,129,134,136,142,144,150],{"type":74,"value":128},"These commands assume ",{"type":68,"tag":83,"props":130,"children":132},{"className":131},[],[133],{"type":74,"value":88},{"type":74,"value":135}," is on PATH. 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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},[1395,1396,1399,1400],{"name":13,"slug":14,"type":15},{"name":1397,"slug":1398,"type":15},"CLI","cli",{"name":20,"slug":21,"type":15},{"name":1401,"slug":1402,"type":15},"Debugging","debugging","2026-04-06T18:01:43.992997",{"slug":1405,"name":1405,"fn":1406,"description":1407,"org":1408,"tags":1409,"stars":25,"repoUrl":26,"updatedAt":1415},"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},[1410,1411,1414],{"name":13,"slug":14,"type":15},{"name":1412,"slug":1413,"type":15},"Approvals","approvals",{"name":20,"slug":21,"type":15},"2026-04-06T18:01:46.758548",{"slug":1417,"name":1417,"fn":1418,"description":1419,"org":1420,"tags":1421,"stars":25,"repoUrl":26,"updatedAt":1430},"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},[1422,1423,1426,1427],{"name":13,"slug":14,"type":15},{"name":1424,"slug":1425,"type":15},"Plugin Development","plugin-development",{"name":23,"slug":24,"type":15},{"name":1428,"slug":1429,"type":15},"UI Components","ui-components","2026-04-06T18:01:56.827891",{"slug":1432,"name":1432,"fn":1433,"description":1434,"org":1435,"tags":1436,"stars":25,"repoUrl":26,"updatedAt":1444},"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},[1437,1438,1440,1441],{"name":13,"slug":14,"type":15},{"name":1439,"slug":39,"type":15},"Data Engineering",{"name":20,"slug":21,"type":15},{"name":1442,"slug":1443,"type":15},"Operations","operations","2026-07-07T06:43:11.160671",{"slug":1446,"name":1446,"fn":1447,"description":1448,"org":1449,"tags":1450,"stars":25,"repoUrl":26,"updatedAt":1461},"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},[1451,1454,1457,1458],{"name":1452,"slug":1453,"type":15},"Analytics","analytics",{"name":1455,"slug":1456,"type":15},"Data Analysis","data-analysis",{"name":1439,"slug":39,"type":15},{"name":1459,"slug":1460,"type":15},"SQL","sql","2026-04-06T18:01:49.599775",{"slug":1463,"name":1463,"fn":1464,"description":1465,"org":1466,"tags":1467,"stars":25,"repoUrl":26,"updatedAt":1474},"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},[1468,1469,1470,1471],{"name":13,"slug":14,"type":15},{"name":1439,"slug":39,"type":15},{"name":20,"slug":21,"type":15},{"name":1472,"slug":1473,"type":15},"Observability","observability","2026-04-06T18:02:03.487365",{"slug":4,"name":4,"fn":5,"description":6,"org":1476,"tags":1477,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1478,1479,1480,1481],{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":23,"slug":24,"type":15},{"slug":1483,"name":1483,"fn":1484,"description":1485,"org":1486,"tags":1487,"stars":25,"repoUrl":26,"updatedAt":1496},"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},[1488,1489,1492,1493],{"name":13,"slug":14,"type":15},{"name":1490,"slug":1491,"type":15},"API Development","api-development",{"name":20,"slug":21,"type":15},{"name":1494,"slug":1495,"type":15},"Go","go","2026-07-11T05:39:13.552213",{"slug":1498,"name":1498,"fn":1499,"description":1500,"org":1501,"tags":1502,"stars":25,"repoUrl":26,"updatedAt":1510},"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},[1503,1504,1507],{"name":20,"slug":21,"type":15},{"name":1505,"slug":1506,"type":15},"Engineering","engineering",{"name":1508,"slug":1509,"type":15},"Java","java","2026-07-18T05:48:13.374003",{"slug":1512,"name":1512,"fn":1513,"description":1514,"org":1515,"tags":1516,"stars":25,"repoUrl":26,"updatedAt":1520},"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},[1517,1518,1519],{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":1505,"slug":1506,"type":15},"2026-07-18T05:11:54.496539",{"slug":1522,"name":1522,"fn":1523,"description":1524,"org":1525,"tags":1526,"stars":25,"repoUrl":26,"updatedAt":1533},"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},[1527,1528,1529,1530],{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":1531,"slug":1532,"type":15},"Templates","templates","2026-04-06T18:01:45.361425",{"slug":1535,"name":1535,"fn":1536,"description":1537,"org":1538,"tags":1539,"stars":25,"repoUrl":26,"updatedAt":1546},"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},[1540,1541,1542,1545],{"name":13,"slug":14,"type":15},{"name":1439,"slug":39,"type":15},{"name":1543,"slug":1544,"type":15},"Data Quality","data-quality",{"name":17,"slug":18,"type":15},"2026-04-06T18:02:02.138565",34,{"items":1549,"total":1547},[1550,1557,1563,1570,1577,1584,1591],{"slug":14,"name":14,"fn":1391,"description":1392,"org":1551,"tags":1552,"stars":25,"repoUrl":26,"updatedAt":1403},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1553,1554,1555,1556],{"name":13,"slug":14,"type":15},{"name":1397,"slug":1398,"type":15},{"name":20,"slug":21,"type":15},{"name":1401,"slug":1402,"type":15},{"slug":1405,"name":1405,"fn":1406,"description":1407,"org":1558,"tags":1559,"stars":25,"repoUrl":26,"updatedAt":1415},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1560,1561,1562],{"name":13,"slug":14,"type":15},{"name":1412,"slug":1413,"type":15},{"name":20,"slug":21,"type":15},{"slug":1417,"name":1417,"fn":1418,"description":1419,"org":1564,"tags":1565,"stars":25,"repoUrl":26,"updatedAt":1430},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1566,1567,1568,1569],{"name":13,"slug":14,"type":15},{"name":1424,"slug":1425,"type":15},{"name":23,"slug":24,"type":15},{"name":1428,"slug":1429,"type":15},{"slug":1432,"name":1432,"fn":1433,"description":1434,"org":1571,"tags":1572,"stars":25,"repoUrl":26,"updatedAt":1444},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1573,1574,1575,1576],{"name":13,"slug":14,"type":15},{"name":1439,"slug":39,"type":15},{"name":20,"slug":21,"type":15},{"name":1442,"slug":1443,"type":15},{"slug":1446,"name":1446,"fn":1447,"description":1448,"org":1578,"tags":1579,"stars":25,"repoUrl":26,"updatedAt":1461},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1580,1581,1582,1583],{"name":1452,"slug":1453,"type":15},{"name":1455,"slug":1456,"type":15},{"name":1439,"slug":39,"type":15},{"name":1459,"slug":1460,"type":15},{"slug":1463,"name":1463,"fn":1464,"description":1465,"org":1585,"tags":1586,"stars":25,"repoUrl":26,"updatedAt":1474},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1587,1588,1589,1590],{"name":13,"slug":14,"type":15},{"name":1439,"slug":39,"type":15},{"name":20,"slug":21,"type":15},{"name":1472,"slug":1473,"type":15},{"slug":4,"name":4,"fn":5,"description":6,"org":1592,"tags":1593,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1594,1595,1596,1597],{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":23,"slug":24,"type":15}]