Polish dataset catalog actions
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@@ -2603,3 +2603,32 @@ Limitations:
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Next recommended pass:
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- Continue with Data workspace action polish, especially making QA/export affordances clearer once candidate and reference layers are present.
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## Sprint 69 Data catalog action polish (2026-06-19)
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Changed:
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- Added role-aware recommended action hints to dataset cards.
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- Reworked dataset card actions into compact two-line buttons for Inspect, Map, Export / QA and Metadata.
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- Kept all existing Data workspace handlers and API calls unchanged.
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- Added disabled-action explanation copy for unsupported export/QA and raster metadata refresh cases.
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- Added responsive `.dataset-action-grid` and `.dataset-action-button` CSS.
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- Added `backend/tests/test_sprint69_dataset_action_polish.py`.
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- Updated `frontend/README.md`, `docs/TODO.md` and `CHANGELOG.md`.
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Tested:
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- Red step: `python -m pytest backend/tests/test_sprint69_dataset_action_polish.py -q` failed on missing action hints, action grid and responsive styles.
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- `python -m pytest backend/tests/test_sprint69_dataset_action_polish.py backend/tests/test_sprint68_dataset_catalog_density.py backend/tests/test_sprint29_dataset_components.py -q` (`9 passed`)
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- `cd frontend && npm run typecheck`
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- `cd frontend && npm run build`
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- Local browser check against `http://127.0.0.1:5175` with live API proxy: Data workspace rendered 2 role-aware hints and 8 compact dataset actions across the demo candidate/reference datasets, no console warnings/errors and no horizontal overflow on desktop or mobile.
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- Screenshots captured under `artifacts/sprint69-dataset-action-polish/`.
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- `bash scripts/run_readiness_check.sh` (`246 passed`)
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Open:
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- Run full readiness, redeploy Tower and verify the live Data action polish after deployment.
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Limitations:
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- This is a frontend affordance/readability pass only. It does not add new workflows, change dataset persistence, change API contracts, add migrations, fetch providers or alter AI/model behavior.
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Next recommended pass:
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- Continue with QA/QC workspace handoff polish, especially linking the existing candidate/reference dataset context more clearly to persisted QA results.
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