enable-tables-offline

Use when the user needs to enable the per-table prerequisites (Can be taken offline, Track changes) before a Dataverse table can be added to a Mobile Offline…

npx skills add https://github.com/microsoft/power-platform-skills --skill enable-tables-offline

Shared instructions: shared-instructions.md — read first.

References:

Enable Tables Offline

Flip IsAvailableOffline=true AND ChangeTrackingEnabled=true on the EntityMetadata of one or more Dataverse tables, then publish customizations. This is the prerequisite shown in Image 4 of the maker portal ("Can be taken offline" + "Track changes") — without both, a table CANNOT be added to a Mobile Offline Profile.

Sequential (Dataverse metadata lock) and idempotent: re-running on an already-enabled table is a no-op.

Workflow

  1. Verify project & auth → 2. Resolve table list → 3. Inspect current state → Gate → 4. PUT EntityMetadata per table → 5. Publish → 6. Verify → 7. Summary

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 from the resolver for <envUrl>. STOP if not authenticated.

Step 2 — Resolve table list

Tables to enable come from one of (in order):

SourceUsed when
$ARGUMENTSUser passed a comma- or space-separated list of logical names (e.g. /enable-tables-offline cr123_note,cr123_visit)
.datamodel-manifest.jsonDefault — read tables[].logicalName for every Dataverse-backed table in the app
AskUserQuestionOnly if both above are absent. Show the table list from src/generated/services/*Service.ts filenames and let the user pick.

If the resolved list is empty, STOP with: "No Dataverse tables found in this project. Run /add-dataverse first."

Step 3 — Inspect current state

Print before starting:

"→ Querying current IsAvailableOffline + ChangeTrackingEnabled for table(s)…"

For each table, in sequence:

node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions(LogicalName='<table>')?\$select=LogicalName,DisplayName,IsAvailableOffline,ChangeTrackingEnabled,IsCustomizable"

Build a status table:

| Table              | IsAvailableOffline | ChangeTrackingEnabled | IsCustomizable | Needs change? |
|--------------------|--------------------|-----------------------|----------------|---------------|
| cr123_note         | false              | false                 | true           | YES (both)    |
| cr123_visit        | true               | false                 | true           | YES (track)   |
| contact            | true               | true                  | true           | NO            |

Hard rule: if IsCustomizable.Value=false on any table, that table CANNOT be modified. Drop it from the change set and flag in DONE_WITH_CONCERNS — system-managed tables (most OOB) require an admin solution patch path the skill does not handle.

Gate — Approval before mutation

Enter plan mode with the status table from Step 3 plus the planned operation per table. Wait for user ExitPlanMode before proceeding.

Plan body:

The following EntityMetadata changes will be PUT in sequence:

cr123_note   → set IsAvailableOffline=true, ChangeTrackingEnabled=true
cr123_visit  → set ChangeTrackingEnabled=true (IsAvailableOffline already true)

After all updates, a single PublishAllXml request will commit the changes.

Tables already in the desired state are skipped (no API call).

If the user rejects, STOP. If they approve, proceed.

Step 4 — PUT EntityMetadata per table

Print before starting:

"→ Updating EntityMetadata for table(s) sequentially (Dataverse serializes metadata writes)…"

⚠️ Concurrency rule — do not violate. Metadata writes hold an exclusive lock per org. Issue one PUT, wait for 2xx, then the next. No batching, no parallel calls. Same rule as /add-dataverse Step 5.

For each table needing change (skip ones already in target state):

node "${PLUGIN_ROOT}/scripts/update-entity-offline-flags.js" <envUrl> \
  --table <table> \
  --offline true \
  --tracking true

The helper:

  • Re-reads EntityMetadata to pick up the current MetadataId + SchemaName (both required in the PUT body — Dataverse rejects PUT without them).
  • Sends MSCRM.MergeLabels: true so display labels are preserved (the alternative wipes labels — never use false).
  • Returns { "status": 200, "noop": true, ... } if the table is already in the target state (skip silently).
  • Returns { "status": 200, "skipped": "uncustomizable", ... } for tables whose IsCustomizable.Value=false (system-managed; you must surface as DONE_WITH_CONCERNS).
  • Returns { "status": 204, ... } on successful update.
  • Handles 401 token refresh and 429 back-off automatically.

If the helper returns status 403 PrivilegeCheckFailed: the user lacks "Customize System" privilege. Print the table name and which privilege is missing, then STOP.

If status 400 with ChangeTrackingEnabled cannot be disabled: ignore — that path only triggers when going from true to false, which we never do.

Print ✓ <table> after each 204; print ↷ <table> (already enabled) for no-ops; print ⚠ <table> (uncustomizable) for skips.

Step 5 — Publish customizations (targeted PublishXml, with PublishAllXml fallback)

Print before starting:

"→ Publishing customizations (targeted PublishXml on the entities just edited)…"

Use targeted PublishXml scoped to the entities that were actually modified — avoids the org-wide rate-limit storms (0x80071151 "concurrent PublishAll already running") observed on shared envs. Empirical 2026-05-25.

# Build the <entities> XML body from the list of tables modified in Step 4
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST \
  "PublishXml" --body '{
    "ParameterXml": "<importexportxml><entities><entity>cr720_fcbflag</entity><entity>cr720_rolloutevent</entity></entities></importexportxml>"
  }'

Substitute <entity>...</entity> lines for every table the helper PUT'd flags on in Step 4. Tables that were no-ops or uncustomizable are omitted.

On 204: success — continue to Step 6.

On 429 / 0x80071151 ("concurrent publish already running"): back off automatically via dataverse-request.js's retry logic. If still failing after 4 retries, return DONE_WITH_CONCERNS: publish bottlenecked on shared env; metadata changes are committed but maker portal will not refresh until next publish. The downstream skill (/setup-offline-profile) can proceed — metadata-level writes are durable.

Fallback to PublishAllXml (only when the targeted call returns a non-rate-limit error like 0x80048d19 malformed body):

node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST \
  "PublishAllXml" --body '{}'

Same timeout-but-success handling as /setup-offline-profile Step 8: if the client times out but a follow-up GET on the table's EntityMetadata shows the flags are set, treat as success.

Step 6 — Verify

Print before starting:

"→ Re-querying EntityMetadata to confirm flags are set…"

Re-run the Step 3 query for each modified table. Assert IsAvailableOffline=true and ChangeTrackingEnabled=true on every changed row. If any disagree, BLOCKED — something rejected the PUT silently (extremely unlikely; usually an indication of a managed-solution layer that's masking the unmanaged change).

Step 7 — Summary

Print:

✓ Offline prerequisites enabled on <N> table(s):
  - cr123_note    (IsAvailableOffline + ChangeTrackingEnabled set)
  - cr123_visit   (ChangeTrackingEnabled set; IsAvailableOffline already on)

Skipped (already enabled): contact

Next: run /setup-offline-profile to design the offline profile that uses these tables.

Update memory-bank.md under ## Offline profile with the timestamp and table list.

Status code

Final line of the skill's response is one of:

  • DONE — all requested tables now have both flags set
  • DONE_WITH_CONCERNS: <list> — some tables skipped (uncustomizable, publish warning, etc.)
  • NEEDS_CONTEXT: <missing> — couldn't resolve table list and user didn't provide
  • BLOCKED: <reason> — auth failure, privilege check failed, or post-PUT verification disagreed

More skills from microsoft

oss-growth
microsoft
OSS growth hacker persona
agent-framework-azure-ai-py
microsoft
Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
development
airunway-aks-setup
microsoft
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
devops
appinsights-instrumentation
microsoft
Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
devops
applicationinsights-web-ts
microsoft
Instrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.
devops
azure-ai-anomalydetector-java
microsoft
Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
development
azure-ai-language-conversations-py
microsoft
Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines. Triggers: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
development