/add-sample-data

name: add-sample-data
description: Use when the user wants to seed Dataverse tables with realistic sample records so a freshly-scaffolded code app shows real-looking data on first launch. Generates contextually appropriate rows from each table's schema and inserts them in dependency order. Mirrors microsoft/power-platform-skills/power-pages/add-sample-data, adapted for mobile apps.
user-invocable: true
allowed-tools: Read, Edit, Write, Grep, Glob, Bash, AskUserQuestion
model: sonnet

**📋 Shared instructions: [shared-instructions.md](${PLUGIN_ROOT}/shared/shared-instructions.md)** — read first.

Add Sample Data

Populate Dataverse tables with realistic sample records so a freshly-scaffolded code app shows real-looking data on first launch. Generates rows from each table's schema and inserts them in dependency order. Use after `/add-dataverse` (or `/setup-datamodel`) has created the tables.

Core principles

• **Coverage over volume — every table in the manifest gets seeded.** The #1 failure mode of a freshly-scaffolded code app is a home / dashboard / list screen that renders an empty state on first launch because its source table has zero rows. An empty downstream table is **worse than a 3-row table.** Default to minimal-but-complete: small counts everywhere, no table left empty. Volume is a secondary knob — coverage is the contract.
• **Insertion order matters.** Parent / referenced tables must be inserted before child / referencing tables so lookup IDs are available.
• **Contextual data, not Lorem Ipsum.** Generate values that match column names + types. A `cr3e9_sitename` column in an inspection app gets "Westside Construction Site", not "Sample Name 1".
• **Scenario-aware rows.** Read `native-app-plan.md`, especially `### Shared Conventions` and per-screen `Operational pattern` values defined in [screen-templates.md](${PLUGIN_ROOT}/shared/references/screen-templates.md). Seed rows should exercise the app's actual workflow: statuses, dates, relationships, priority/severity, media metadata, and edge cases that make the planned first viewport light up.
• **Fail gracefully.** On insertion failure, log the error and continue with remaining records — never auto-rollback. The user can re-run after fixing the issue.
• **Idempotent re-runs.** If a previous run partially completed, the second run reads `memory-bank.md`'s seeded-data table and skips records already inserted.
• **Solution-scoped inserts.** Always pass `--solution <uniqueName>` so records land in our solution, not the default.

Workflow

1. Verify project + auth → 2. Discover tables → 3. Select tables + count → 4. Generate + preview → 5. Insert → 6. Summary

Prototype Seed Reuse

`--from-seed` is used by `/prototype-to-real-app` after a mock prototype is converted to Dataverse. In this mode, prefer existing prototype seed files before generating new rows:

src/generated/services/*/*.seed.json
src/generated/services/*.seed.json

Map seed objects to Dataverse payloads using `.datamodel-manifest.json`:

• Keep values only for real manifest columns.
• Translate lookup references into exact `<schemaName>@odata.bind` keys from the manifest.
• Keep picklist integers from the manifest; do not invent values from labels.
• Skip local-only prototype fields that have no Dataverse column.
• Preserve dependency-tier insertion order.

If a seed file cannot be mapped safely, fall back to generated contextual sample rows for that table and record `DONE_WITH_CONCERNS` in the summary. `--from-seed` is a preference, not permission to insert malformed data.

---

Step 1 — Verify project & auth

test -f power.config.json && test -f app.config.js
node "${PLUGIN_ROOT}/scripts/resolve-environment.js" "$(node -e \"console.log(require('./power.config.json').environmentId)\")"

Capture the **environment URL** for subsequent script calls. If resolution fails, instruct `az login --tenant <env-tenant>` or ask for the environment URL directly, then stop.

Verify Azure CLI auth (the script needs an Azure CLI token):

az account show --query "user.name" -o tsv

If empty, instruct `az login` and stop.

Step 2 — Discover tables

**Telemetry checkpoint: `discover_dataverse_tables`**

Step 2a — Path A: read `.datamodel-manifest.json` (preferred)

test -f .datamodel-manifest.json

If present, parse the JSON. It already contains `logicalName`, `displayName`, `status` (`new` / `extended` / `reused`), and `columns` for every table the project uses. **This is the preferred path** — fast, no API calls.

cat .datamodel-manifest.json | jq '.tables[] | { logicalName, displayName, columnCount: (.columns | length) }'

Skip Step 2b.

Step 2b — Path B: query OData (fallback)

If `.datamodel-manifest.json` is missing, discover custom tables via the script:

node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions?\$select=LogicalName,DisplayName,EntitySetName&\$filter=IsCustomEntity eq true"

For each table the project uses, fetch its custom columns:

node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions(LogicalName='<table>')/Attributes?\$select=LogicalName,DisplayName,AttributeType,RequiredLevel&\$filter=IsCustomAttribute eq true"

Build the same `{ logicalName, displayName, columns: [...] }` shape the manifest provides.

Step 3 — Select tables + count

All tables from the manifest are evaluated — including reused ones — because a mobile app that surfaces data from a shared table still needs rows to render on first launch. The only exception is standard system tables (e.g. `contact`, `account`, `systemuser`) where seeding is risky in shared production environments.

**Pre-seeding row-count check (HARD — runs for every table before generating any rows):**

For each table, query its current record count using the entity set name from the manifest (or derive it by appending `s` to the logical nam