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在实现前澄清需求、探索设计选择,并形成清晰的开发方向。
mage-ai【开发与工程】Mage AI repo skill for platform operations, pipeline authoring, integrations, dbt, streaming, and AI workflows.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this skill for the mage-ai repository and package. It is self-contained: future work should rely on the bundled references and scripts in this skill tree, not on the original checkout.
| User need | Route |
|---|---|
| Install Mage, bootstrap a project, start the server, run a pipeline, clean logs/variables, or diagnose auth/logging/runtime startup issues | sub-skills/platform-ops/ |
| Author batch pipelines with Python, SQL, or R blocks; use runtime variables; work with dynamic blocks or templates | sub-skills/pipeline-authoring/ |
Configure io_config.yaml, batch data integration pipelines, source/destination profiles, or connector settings | sub-skills/batch-integrations/ |
| Build or debug real-time pipelines, Kafka/CDC flows, or streaming sources/sinks | sub-skills/streaming/ |
| Add existing dbt projects, run dbt models or tests, or interpolate Mage values into dbt workflows | sub-skills/dbt-workflows/ |
| Set up AI generation, documentation helpers, or AI credentials and failures | sub-skills/ai-workflows/ |
mage-aimagemage_ai.run(pipeline_uuid, project_path=None, block_uuid=None, run_sensors=True, **global_vars)pip, and conda.mage-ai[ai], mage-ai[streaming], and mage-ai[dbt].SKILL.md and bundled references first.scripts/smoke_cli.py — import and CLI help smoke testscripts/check_project_layout.py — inspect a Mage project path without mutating it