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Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
47K starsAug 25, 2026 pushdata-analysisPythonETL
$ npx skills add apache/airflowAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Assemble a reviewable first version of an analytics agent's context from what a data stack already has: a warehouse schema export, a dbt project, docs, dashboards, query logs. Produces a Cassis ontology tree (domain READMEs, table and metric YAML, joins) with the evidence behind every claim attached and unresolved meaning filed as questions. Scripts do everything the inputs determine; the user decides at four checkpoints. Runs fully offline: no account, no key, no network. Optional dbt write-back merges descriptions into the project's own schema.yml files without overwriting anything already there. Use when asked to "bootstrap an ontology", "build context for an analytics agent", "document the warehouse for AI", "turn our dbt project into an ontology", or "make our data agent-ready".
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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$ npx skills add streamlit/streamlitHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep ontology-bootstrap if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.