| name | gooddata-assessment |
| description | Take inventory of a GoodData Cloud / GoodData.CN estate and produce a migration-readiness readout — workspace, dataset, metric, insight, and dashboard counts; a MAQL-complexity histogram (which metrics use BY / WITHIN / BY ALL / FOR time transforms); an insight visualization-type mix; and per- dashboard AUTO / HINT / MANUAL / UNHANDLED tags scored against the gooddata-to-sigma converter's actual coverage. Use when a user wants to scope a GoodData→Sigma migration, audit estate sprawl, or pick which dashboards to convert first. Read-only, all-free pre-scoping over the declarative workspace export. |
| user-invocable | true |
GoodData assessment
Read-only migration-readiness readout for a GoodData Cloud / .CN estate. Pulls
the declarative layout (no writes) and scores it against what
gooddata-to-sigma can actually convert.
Status: working + live-validated. scripts/assess.py reuses the converter's
own MAQL translator for honest coverage scoring (no guessing) and tags each
dashboard AUTO / HINT / MANUAL / UNHANDLED.
What it reports
- Inventory — workspaces, datasets, metrics, insights, dashboards.
- MAQL complexity — histogram of metrics by construct (plain agg /
WHERE /
BY-WITHIN-BY ALL context / FOR time transforms / ranking), since
context + time intel are the conversion-risk drivers (maql-mapping.md).
- Visualization mix — insight
visualizationUrl histogram, with each type
tagged against viz-type-mapping.md (auto-mappable vs flagged).
- Per-dashboard tag — AUTO (fully mappable), HINT (minor manual), MANUAL
(context MAQL / RLS review), UNHANDLED (exotic widgets / compute-only metrics).
- Shortlist — value/cost-ranked migration order.
Usage
eval "$(../gooddata-to-sigma/scripts/get-token.sh)"
python3 scripts/assess.py --workspace <id>
Usage telemetry (per-dashboard view counts) is the universal weak spot — it is
not in the declarative model; note it as a manual input if needed.
