dv-overview
Skill: Overview — What to Use and When
This skill provides cross-cutting context that no individual skill owns: tool capabilities, UX principles, and the skill index. Per-task routing is handled by each skill's WHEN/DO NOT USE WHEN frontmatter triggers — not duplicated here.
Hard Rules — Read These First
These rules are non-negotiable. Violating any of them means the task is going off-rails.
0. Check Init State Before Anything Else
Before writing ANY code or creating ANY files, check if the workspace is initialized:
ls .env scripts/auth.py 2>/dev/null
- If BOTH exist: workspace is initialized. Proceed to the relevant task.
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dv-connect
One-step setup for a Dataverse environment — installs tools, authenticates, registers the MCP server, and writes `.env`. Use when starting a new project, switching environments, fixing authentication, or troubleshooting an MCP connection that won't come up.
17dv-solution
Dataverse solution lifecycle — create, export, import, promote across environments, and validate deployments. Use when the user wants to package customizations, deploy to another environment, or move work between dev / test / prod.
16dv-metadata
Dataverse schema authoring via the Python SDK and Web API — tables, columns, relationships, forms, and views. Use when the user wants to define or evolve the data model — add a column, create a table, set up a lookup, customize a form, or build a view.
15dv-data
Record-level CRUD and bulk operations via the Python SDK — create, update, delete, upsert, CSV import, multi-table foreign-key loads, AI-generated sample data. Use when the user wants to write, modify, seed, or import data records into Dataverse tables.
10dv-query
Bulk reads, multi-page iteration, and analytics over Dataverse data via the Python SDK and Web API. Use when the user wants to read, list, filter, aggregate, group, join, or analyze records — including pandas DataFrame workflows and notebook exploration.
10dv-admin
Environment-level Dataverse administration — bulk delete, retention/archival, organization settings, OrgDB settings, recycle bin, audit, and the 37 allowlisted PPAC toggles. Use when the user wants to clean up data at scale, configure audit, change environment settings, or manage retention policies.
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