databrickslabs / databrickslabs/coding-agents-databricks-apps
Bundle 25 Databricks skills as coda-databricks-skills plugin
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 40
- Forks
- 11
- Avg merge
- 1m
- Merged PRs (30d)
- 1
Description
Summary
Bundles the field-engineering Databricks skill set as a CODA plugin, auto-loaded at startup via the marketplace. Pure addition — no production code changes. Migrating from datasciencemonkey PR #141.
25 skill domains synced from databricks-solutions/ai-dev-kit:
Agent Bricks, AI Functions, AI/BI Dashboards, Apps (Python), Asset Bundles, BDD Testing, Config, DBSQL, Docs, Execution Compute, Genie, Iceberg, Jobs, Lakebase (Autoscale + Provisioned), Metric Views, MLflow Evaluation, Model Serving, Python SDK, Spark SDP, Spark Structured Streaming, Synthetic Data Gen, Unity Catalog, Unstructured PDF, Vector Search, ZeroBus Ingest, Python Data Source.
Dependency
Depends on the plugin loader landing first (the sibling coda-essentials-plugin issue). Without that, this plugin doesn't get loaded.
Branch
feat/coda-databricks-skills — about to be pushed.
Diff scope
+51071 / 0, 156 files. 100% markdown + one plugin.json. No production code touched.
Open question
Vendor these skills here, or keep them refreshable from databricks-solutions/ai-dev-kit via a CI sync? Current design is "vendored at PR-merge time" — refreshes need a new PR. Worth deciding before merge.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the plugin loader dependency from the sibling coda-essentials-plugin issue, then inspect the planned feat/coda-databricks-skills branch and plugin.json. Verify that the 156 markdown files are bundled and auto-loaded through the marketplace. Before merge, resolve whether skills remain vendored from databricks-solutions/ai-dev-kit or use a CI refresh flow.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- json, markdown
- Domain
- documentation, tooling
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100