Browse published AI skills maintained by dsa110. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
9Repository stars across indexed skills
0Repository forks
0Average repository stars per indexed skill
0Repository stars may repeat across skills from the same repository.
DSA-110 radio astronomy pipeline development with Python 3.11+, Dagster workflows, CASA integration, FastAPI, GraphQL/Strawberry, and scientific computing best practices. Use for any work on the dsa110-contimg...
DSA-110 radio astronomy pipeline development with Python 3.11+, Dagster workflows, CASA integration, FastAPI, GraphQL/Strawberry, and scientific computing best practices. Use for any work on the dsa110-contimg...
Incident response and troubleshooting for pipeline failures. Use when investigating errors, log anomalies, failed runs, or degraded performance and when preparing recovery steps or mitigations.
Frontend UI/UX changes, dashboards, visualizations, and UI testing. Use when modifying the web UI, improving UX, adjusting visualizations, or running frontend tests.
Quality assurance, validation checks, metrics, and regression verification for pipeline outputs. Use when running validation suites, checking image quality, or defining acceptance criteria.
Documentation updates, run reports, verification summaries, and status notes for the pipeline. Use when creating or updating docs, reports, or change logs.
Development workflows for the pipeline including tests, linting, local dev servers, CI checks, and code organization. Use when implementing features, running tests, or preparing changes for review.
Environment setup, configuration management, ports, and runtime settings for the pipeline. Use when adjusting configs, setting env vars, or diagnosing environment-specific behavior.
Run, monitor, and control the DSA-110 continuum imaging pipeline or its orchestration. Use for starting/stopping runs, backfills, scheduling, retries, runtime state inspection, Dagster/CLI entrypoints, and oper...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.