[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-astronomer-migrating-airflow-2-to-3":3,"mdc-8ilc3s-key":55,"related-org-astronomer-migrating-airflow-2-to-3":1738,"related-repo-astronomer-migrating-airflow-2-to-3":1906},{"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},"migrating-airflow-2-to-3","migrate Airflow 2 projects to Airflow 3","Guide for migrating Apache Airflow 2.x projects to Airflow 3.x. Use when the user mentions Airflow 3 migration, upgrade, compatibility issues, breaking changes, or wants to modernize their Airflow codebase. If you detect Airflow 2.x code that needs migration, prompt the user and ask if they want you to help upgrade. Always load this skill as the first step for any migration-related request.",{"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},"Modernization","modernization","tag",{"name":17,"slug":18,"type":15},"Airflow","airflow",{"name":20,"slug":21,"type":15},"Migration","migration",{"name":23,"slug":24,"type":15},"Python","python",412,"https:\u002F\u002Fgithub.com\u002Fastronomer\u002Fagents","2026-04-06T18:02:06.194769",null,55,[31,32,33,34,18,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49],"agentic-workflow","agents","ai","ai-agents","apache-airflow","claude","cursor","dag","data-engineering","data-pipelines","dbt","llm","mcp","orchestrator","skills","workflow-automation","workflow-management","workflow-orchestration","workflows",{"repoUrl":26,"stars":25,"forks":29,"topics":51,"description":52},[31,32,33,34,18,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49],"AI agent tooling for data engineering workflows.","https:\u002F\u002Fgithub.com\u002Fastronomer\u002Fagents\u002Ftree\u002FHEAD\u002Fskills\u002Fmigrating-airflow-2-to-3","---\nname: migrating-airflow-2-to-3\ndescription: Guide for migrating Apache Airflow 2.x projects to Airflow 3.x. Use when the user mentions Airflow 3 migration, upgrade, compatibility issues, breaking changes, or wants to modernize their Airflow codebase. If you detect Airflow 2.x code that needs migration, prompt the user and ask if they want you to help upgrade. Always load this skill as the first step for any migration-related request.\nhooks:\n  PostToolUse:\n    - matcher: \"Edit\"\n      hooks:\n        - type: command\n          command: \"echo 'Consider running: ruff check --preview --select AIR .'\"\n---\n\n# Airflow 2 to 3 Migration\n\nThis skill helps migrate **Airflow 2.x DAG code** to **Airflow 3.x**, focusing on code changes (imports, operators, hooks, context, API usage).\n\n**Important**: Before migrating to Airflow 3, strongly recommend upgrading to Airflow 2.11 first, then to at least Airflow 3.0.11 (ideally directly to 3.1). Other upgrade paths would make rollbacks impossible. See: https:\u002F\u002Fwww.astronomer.io\u002Fdocs\u002Fastro\u002Fairflow3\u002Fupgrade-af3#upgrade-your-airflow-2-deployment-to-airflow-3. Additionally, early 3.0 versions have many bugs - 3.1 provides a much better experience.\n\n## Migration at a Glance\n\n1. Run Ruff's Airflow migration rules to auto-fix detectable issues (AIR30\u002FAIR301\u002FAIR302\u002FAIR31\u002FAIR311\u002FAIR312).\n   - `ruff check --preview --select AIR --fix --unsafe-fixes .`\n2. Scan for remaining issues using the manual search checklist in [reference\u002Fmigration-checklist.md](reference\u002Fmigration-checklist.md).\n   - Focus on: direct metadata DB access, legacy imports, scheduling\u002Fcontext keys, XCom pickling, datasets-to-assets, REST API\u002Fauth, plugins, and file paths.\n   - Hard behavior\u002Fconfig gotchas to explicitly review:\n     - Cron scheduling semantics: consider `AIRFLOW__SCHEDULER__CREATE_CRON_DATA_INTERVAL=True` if you need Airflow 2-style cron data intervals.\n     - `.airflowignore` syntax changed from regexp to glob; set `AIRFLOW__CORE__DAG_IGNORE_FILE_SYNTAX=regexp` if you must keep regexp behavior.\n     - OAuth callback URLs add an `\u002Fauth\u002F` prefix (e.g. `\u002Fauth\u002Foauth-authorized\u002Fgoogle`).\n     - **Shared utility imports**: Bare imports like `import common` from `dags\u002Fcommon\u002F` no longer work on Astro. Use fully qualified imports: `import dags.common`.\n3. Plan changes per file and issue type:\n   - Fix imports - update operators\u002Fhooks\u002Fproviders - refactor metadata access to using the Airflow client instead of direct access - fix use of outdated context variables - fix scheduling logic.\n4. Implement changes incrementally, re-running Ruff and code searches after each major change.\n5. Explain changes to the user and caution them to test any updated logic such as refactored metadata, scheduling logic and use of the Airflow context.\n\n---\n\n## Architecture & Metadata DB Access\n\nAirflow 3 changes how components talk to the metadata database:\n\n- Workers no longer connect directly to the metadata DB.\n- Task code runs via the **Task Execution API** exposed by the **API server**.\n- The **DAG processor** runs as an independent process **separate from the scheduler**.\n- The **Triggerer** uses the task execution mechanism via an **in-process API server**.\n\n**Trigger implementation gotcha**: If a trigger calls hooks synchronously inside the asyncio event loop, it may fail or block. Prefer calling hooks via `sync_to_async(...)` (or otherwise ensure hook calls are async-safe).\n\n**Key code impact**: Task code can still import ORM sessions\u002Fmodels, but **any attempt to use them to talk to the metadata DB will fail** with:\n\n```text\nRuntimeError: Direct database access via the ORM is not allowed in Airflow 3.x\n```\n\n### Patterns to search for\n\nWhen scanning DAGs, custom operators, and `@task` functions, look for:\n\n- Session helpers: `provide_session`, `create_session`, `@provide_session`\n- Sessions from settings: `from airflow.settings import Session`\n- Engine access: `from airflow.settings import engine`\n- ORM usage with models: `session.query(DagModel)...`, `session.query(DagRun)...`\n\n### Replacement: Airflow Python client\n\nPreferred for rich metadata access patterns. Add to `requirements.txt`:\n\n```text\napache-airflow-client==\u003Cyour-airflow-runtime-version>\n```\n\nExample usage:\n\n```python\nimport os\nfrom airflow.sdk import BaseOperator\nimport airflow_client.client\nfrom airflow_client.client.api.dag_api import DAGApi\n\n_HOST = os.getenv(\"AIRFLOW__API__BASE_URL\", \"https:\u002F\u002F\u003Cyour-org>.astronomer.run\u002F\u003Cdeployment>\u002F\")\n_TOKEN = os.getenv(\"DEPLOYMENT_API_TOKEN\")\n\nclass ListDagsOperator(BaseOperator):\n    def execute(self, context):\n        config = airflow_client.client.Configuration(host=_HOST, access_token=_TOKEN)\n        with airflow_client.client.ApiClient(config) as api_client:\n            dag_api = DAGApi(api_client)\n            dags = dag_api.get_dags(limit=10)\n            self.log.info(\"Found %d DAGs\", len(dags.dags))\n```\n\n### Replacement: Direct REST API calls\n\nFor simple cases, call the REST API directly using `requests`:\n\n```python\nfrom airflow.sdk import task\nimport os\nimport requests\n\n_HOST = os.getenv(\"AIRFLOW__API__BASE_URL\", \"https:\u002F\u002F\u003Cyour-org>.astronomer.run\u002F\u003Cdeployment>\u002F\")\n_TOKEN = os.getenv(\"DEPLOYMENT_API_TOKEN\")\n\n@task\ndef list_dags_via_api() -> None:\n    response = requests.get(\n        f\"{_HOST}\u002Fapi\u002Fv2\u002Fdags\",\n        headers={\"Accept\": \"application\u002Fjson\", \"Authorization\": f\"Bearer {_TOKEN}\"},\n        params={\"limit\": 10}\n    )\n    response.raise_for_status()\n    print(response.json())\n```\n\n---\n\n## Ruff Airflow Migration Rules\n\nUse Ruff's Airflow rules to detect and fix many breaking changes automatically.\n\n- **AIR30 \u002F AIR301 \u002F AIR302**: Removed code and imports in Airflow 3 - **must be fixed**.\n- **AIR31 \u002F AIR311 \u002F AIR312**: Deprecated code and imports - still work but will be removed in future versions; **should be fixed**.\n\nCommands to run (via `uv`) against the project root:\n\n```bash\n# Auto-fix all detectable Airflow issues (safe + unsafe)\nruff check --preview --select AIR --fix --unsafe-fixes .\n\n# Check remaining Airflow issues without fixing\nruff check --preview --select AIR .\n```\n\n---\n\n## Reference Files\n\nFor detailed code examples and migration patterns, see:\n\n- **[reference\u002Fconfig-changes.md](reference\u002Fconfig-changes.md)** - `airflow.cfg` section moves, renames, and removals\n- **[reference\u002Fmigration-patterns.md](reference\u002Fmigration-patterns.md)** - Code examples for imports, scheduling, XCom, Assets, DAG bundles, runtime behavior changes\n- **[reference\u002Fremoved-methods.md](reference\u002Fremoved-methods.md)** - Removed model methods with SDK\u002FAPI migration paths\n- **[reference\u002Fmigration-checklist.md](reference\u002Fmigration-checklist.md)** - Search patterns and fixes for issues Ruff doesn't catch\n\n---\n\n## Quick Reference Tables\n\n### Key Import Changes\n\n| Airflow 2.x | Airflow 3 |\n|-------------|-----------|\n| `airflow.operators.dummy_operator.DummyOperator` | `airflow.providers.standard.operators.empty.EmptyOperator` |\n| `airflow.operators.bash.BashOperator` | `airflow.providers.standard.operators.bash.BashOperator` |\n| `airflow.operators.python.PythonOperator` | `airflow.providers.standard.operators.python.PythonOperator` |\n| `airflow.decorators.dag` | `airflow.sdk.dag` |\n| `airflow.decorators.task` | `airflow.sdk.task` |\n| `airflow.datasets.Dataset` | `airflow.sdk.Asset` |\n\n### Context Key Changes\n\n| Removed Key | Replacement |\n|-------------|-------------|\n| `execution_date` | `context[\"dag_run\"].logical_date` |\n| `tomorrow_ds` \u002F `yesterday_ds` | Use `ds` with date math: `macros.ds_add(ds, 1)` \u002F `macros.ds_add(ds, -1)` |\n| `prev_ds` \u002F `next_ds` | `prev_start_date_success` or timetable API |\n| `triggering_dataset_events` | `triggering_asset_events` |\n| `templates_dict` | `context[\"params\"]` |\n\n**Asset-triggered runs**: `logical_date` may be `None`; use `context[\"dag_run\"].logical_date` defensively.\n\n**Cannot trigger with future `logical_date`**: Use `logical_date=None` and rely on `run_id` instead.\n\nCron note: for scheduled runs using cron, `logical_date` semantics differ under `CronTriggerTimetable` (aligning `logical_date` with `run_after`). If you need Airflow 2-style cron data intervals, consider `AIRFLOW__SCHEDULER__CREATE_CRON_DATA_INTERVAL=True`.\n\n### Default Behavior Changes\n\n| Setting | Airflow 2 Default | Airflow 3 Default |\n|---------|-------------------|-------------------|\n| `schedule` | `timedelta(days=1)` | `None` |\n| `catchup` | `True` | `False` |\n\n### Callback Behavior Changes\n\n- `on_success_callback` no longer runs on skip; use `on_skipped_callback` if needed.\n- `@teardown` with `TriggerRule.ALWAYS` not allowed; teardowns now execute even if DAG run terminated early.\n\n---\n\n## Resources\n\n- [Astronomer Airflow 3 Upgrade Guide](https:\u002F\u002Fwww.astronomer.io\u002Fdocs\u002Fastro\u002Fairflow3\u002Fupgrade-af3)\n- [Airflow 3 Release Notes](https:\u002F\u002Fairflow.apache.org\u002Fdocs\u002Fapache-airflow\u002Fstable\u002Frelease_notes.html)\n- [Ruff Airflow Rules](https:\u002F\u002Fdocs.astral.sh\u002Fruff\u002Frules\u002F#airflow-air)\n\n---\n\n## Related Skills\n\n- **testing-dags**: For testing DAGs after migration\n- **debugging-dags**: For troubleshooting migration issues\n- **deploying-airflow**: For deploying migrated DAGs to production\n",{"data":56,"body":65},{"name":4,"description":6,"hooks":57},{"PostToolUse":58},[59],{"matcher":60,"hooks":61},"Edit",[62],{"type":63,"command":64},"command","echo 'Consider running: ruff check --preview --select AIR .'",{"type":66,"children":67},"root",[68,77,98,118,125,287,291,297,302,363,381,398,410,417,430,499,505,518,527,532,677,683,695,826,829,835,840,875,888,993,996,1002,1007,1069,1072,1078,1084,1238,1244,1405,1438,1469,1510,1516,1602,1608,1648,1651,1657,1690,1693,1699,1732],{"type":69,"tag":70,"props":71,"children":73},"element","h1",{"id":72},"airflow-2-to-3-migration",[74],{"type":75,"value":76},"text","Airflow 2 to 3 Migration",{"type":69,"tag":78,"props":79,"children":80},"p",{},[81,83,89,91,96],{"type":75,"value":82},"This skill helps migrate ",{"type":69,"tag":84,"props":85,"children":86},"strong",{},[87],{"type":75,"value":88},"Airflow 2.x DAG code",{"type":75,"value":90}," to ",{"type":69,"tag":84,"props":92,"children":93},{},[94],{"type":75,"value":95},"Airflow 3.x",{"type":75,"value":97},", focusing on code changes (imports, operators, hooks, context, API usage).",{"type":69,"tag":78,"props":99,"children":100},{},[101,106,108,116],{"type":69,"tag":84,"props":102,"children":103},{},[104],{"type":75,"value":105},"Important",{"type":75,"value":107},": Before migrating to Airflow 3, strongly recommend upgrading to Airflow 2.11 first, then to at least Airflow 3.0.11 (ideally directly to 3.1). 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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},[1762,1763,1766],{"name":17,"slug":18,"type":15},{"name":1764,"slug":1765,"type":15},"Approvals","approvals",{"name":1750,"slug":1751,"type":15},"2026-04-06T18:01:46.758548",{"slug":1769,"name":1769,"fn":1770,"description":1771,"org":1772,"tags":1773,"stars":25,"repoUrl":26,"updatedAt":1782},"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},[1774,1775,1778,1779],{"name":17,"slug":18,"type":15},{"name":1776,"slug":1777,"type":15},"Plugin Development","plugin-development",{"name":23,"slug":24,"type":15},{"name":1780,"slug":1781,"type":15},"UI Components","ui-components","2026-04-06T18:01:56.827891",{"slug":1784,"name":1784,"fn":1785,"description":1786,"org":1787,"tags":1788,"stars":25,"repoUrl":26,"updatedAt":1796},"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},[1789,1790,1792,1793],{"name":17,"slug":18,"type":15},{"name":1791,"slug":39,"type":15},"Data Engineering",{"name":1750,"slug":1751,"type":15},{"name":1794,"slug":1795,"type":15},"Operations","operations","2026-07-07T06:43:11.160671",{"slug":1798,"name":1798,"fn":1799,"description":1800,"org":1801,"tags":1802,"stars":25,"repoUrl":26,"updatedAt":1813},"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},[1803,1806,1809,1810],{"name":1804,"slug":1805,"type":15},"Analytics","analytics",{"name":1807,"slug":1808,"type":15},"Data Analysis","data-analysis",{"name":1791,"slug":39,"type":15},{"name":1811,"slug":1812,"type":15},"SQL","sql","2026-04-06T18:01:49.599775",{"slug":1815,"name":1815,"fn":1816,"description":1817,"org":1818,"tags":1819,"stars":25,"repoUrl":26,"updatedAt":1826},"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},[1820,1821,1822,1823],{"name":17,"slug":18,"type":15},{"name":1791,"slug":39,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1824,"slug":1825,"type":15},"Observability","observability","2026-04-06T18:02:03.487365",{"slug":1828,"name":1828,"fn":1829,"description":1830,"org":1831,"tags":1832,"stars":25,"repoUrl":26,"updatedAt":1839},"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},[1833,1834,1835,1838],{"name":17,"slug":18,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1836,"slug":1837,"type":15},"ETL","etl",{"name":23,"slug":24,"type":15},"2026-04-06T18:01:52.679888",{"slug":1841,"name":1841,"fn":1842,"description":1843,"org":1844,"tags":1845,"stars":25,"repoUrl":26,"updatedAt":1854},"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},[1846,1847,1850,1851],{"name":17,"slug":18,"type":15},{"name":1848,"slug":1849,"type":15},"API Development","api-development",{"name":1750,"slug":1751,"type":15},{"name":1852,"slug":1853,"type":15},"Go","go","2026-07-11T05:39:13.552213",{"slug":1856,"name":1856,"fn":1857,"description":1858,"org":1859,"tags":1860,"stars":25,"repoUrl":26,"updatedAt":1868},"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},[1861,1862,1865],{"name":1750,"slug":1751,"type":15},{"name":1863,"slug":1864,"type":15},"Engineering","engineering",{"name":1866,"slug":1867,"type":15},"Java","java","2026-07-18T05:48:13.374003",{"slug":1870,"name":1870,"fn":1871,"description":1872,"org":1873,"tags":1874,"stars":25,"repoUrl":26,"updatedAt":1878},"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},[1875,1876,1877],{"name":17,"slug":18,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1863,"slug":1864,"type":15},"2026-07-18T05:11:54.496539",{"slug":1880,"name":1880,"fn":1881,"description":1882,"org":1883,"tags":1884,"stars":25,"repoUrl":26,"updatedAt":1891},"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},[1885,1886,1887,1888],{"name":17,"slug":18,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1836,"slug":1837,"type":15},{"name":1889,"slug":1890,"type":15},"Templates","templates","2026-04-06T18:01:45.361425",{"slug":1893,"name":1893,"fn":1894,"description":1895,"org":1896,"tags":1897,"stars":25,"repoUrl":26,"updatedAt":1904},"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},[1898,1899,1900,1903],{"name":17,"slug":18,"type":15},{"name":1791,"slug":39,"type":15},{"name":1901,"slug":1902,"type":15},"Data Quality","data-quality",{"name":1836,"slug":1837,"type":15},"2026-04-06T18:02:02.138565",34,{"items":1907,"total":1905},[1908,1915,1921,1928,1935,1942,1949],{"slug":18,"name":18,"fn":1741,"description":1742,"org":1909,"tags":1910,"stars":25,"repoUrl":26,"updatedAt":1755},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1911,1912,1913,1914],{"name":17,"slug":18,"type":15},{"name":1747,"slug":1748,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1753,"slug":1754,"type":15},{"slug":1757,"name":1757,"fn":1758,"description":1759,"org":1916,"tags":1917,"stars":25,"repoUrl":26,"updatedAt":1767},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1918,1919,1920],{"name":17,"slug":18,"type":15},{"name":1764,"slug":1765,"type":15},{"name":1750,"slug":1751,"type":15},{"slug":1769,"name":1769,"fn":1770,"description":1771,"org":1922,"tags":1923,"stars":25,"repoUrl":26,"updatedAt":1782},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1924,1925,1926,1927],{"name":17,"slug":18,"type":15},{"name":1776,"slug":1777,"type":15},{"name":23,"slug":24,"type":15},{"name":1780,"slug":1781,"type":15},{"slug":1784,"name":1784,"fn":1785,"description":1786,"org":1929,"tags":1930,"stars":25,"repoUrl":26,"updatedAt":1796},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1931,1932,1933,1934],{"name":17,"slug":18,"type":15},{"name":1791,"slug":39,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1794,"slug":1795,"type":15},{"slug":1798,"name":1798,"fn":1799,"description":1800,"org":1936,"tags":1937,"stars":25,"repoUrl":26,"updatedAt":1813},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1938,1939,1940,1941],{"name":1804,"slug":1805,"type":15},{"name":1807,"slug":1808,"type":15},{"name":1791,"slug":39,"type":15},{"name":1811,"slug":1812,"type":15},{"slug":1815,"name":1815,"fn":1816,"description":1817,"org":1943,"tags":1944,"stars":25,"repoUrl":26,"updatedAt":1826},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1945,1946,1947,1948],{"name":17,"slug":18,"type":15},{"name":1791,"slug":39,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1824,"slug":1825,"type":15},{"slug":1828,"name":1828,"fn":1829,"description":1830,"org":1950,"tags":1951,"stars":25,"repoUrl":26,"updatedAt":1839},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1952,1953,1954,1955],{"name":17,"slug":18,"type":15},{"name":1750,"slug":1751,"type":15},{"name":1836,"slug":1837,"type":15},{"name":23,"slug":24,"type":15}]