Add Dataverse logo

Add Dataverse

Organization
microsoft
add-dataverse

Use when the user wants to add Dataverse tables (existing or new) to a Power Apps mobile app, extend an existing Dataverse table with new columns, or apply an approved data model plan.

Overview

Publishermicrosoft
Repositorypower-platform-skills
Skill nameadd-dataverse
Stars
895
Forks
182
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Add Dataverse AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/power-platform-skills.git /tmp/power-platform-skills
mkdir -p .claude/skills
cp -r /tmp/power-platform-skills/plugins/mobile-apps/skills/add-dataverse .claude/skills/add-dataverse
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Add Dataverse in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Add Dataverse on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Add Dataverse is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Add Dataverse

Two paths:

  • Existing tables only — skip to Step 5 (just runs npx power-apps add-data-source per table)
  • New / extended tables — full workflow with Web API mutations in dependency order

Workflow

  1. Verify project & auth → 2. Resolve plan/operation manifest → 3. Setup Dataverse Web API auth → 4. Validate manifest or reconcile live metadata → 5. Execute sequential metadata phases → 6. Add data sources → 6b. Publish fallback customizations → 6c. Verify tables → 6d. Write manifest → 7. Inspect generated files → 8. Type-check → 8.5. Offline profile reconciliation → 9. Summary

Step 1 — Verify project & auth

Confirm Power Apps mobile app:

bash
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 (https://orgXXX.crm.dynamics.com), environment ID, and tenant ID from resolve-environment.js — needed for Step 3. If only the environment URL is available, pass that URL instead of the ID.

Step 2 — Resolve plan

Telemetry checkpoint: resolve_dataverse_schema_plan

Look for native-app-plan.md in the project root:

bash
test -f native-app-plan.md

Before reading plan content, inspect $ARGUMENTS for the five fast-path artifact flags in Step 2a. When all are present, only confirm native-app-plan.md exists for hash validation; do not parse its Data Model section or build operations/service lists from Markdown.

If present and <operation_manifest_mode> = fallback: read the ## Data Model section. Extract:

  • The target reconciliation table (reuse / extend / create / adapt / defer decisions and evidence)
  • The Mermaid ER diagram (informational)
  • The "Creation Order" tier list
  • Every table referenced by ## Screens, identity resolution, related-entity fields, forms, dashboards, or shared hooks, including standard reused tables such as systemuser, contact, and account

Build SERVICE_REQUIRED_TABLES as the union of:

  1. every non-deferred row in Target Reconciliation (reuse, extend, create, or adapt);
  2. every table in Creation Order;
  3. every table named by screen/hook data requirements.

Hard rule: reuse means "do not mutate schema"; it does not mean "skip generated service." If app code reads or writes a reused table, that table must be in SERVICE_REQUIRED_TABLES.

Carry forward any adapt (auto-renamed) and defer (out-of-scope this run) decisions with their recorded reasons, and apply the alias map to every name you use. A data-modelling conflict never halts this skill — it resolves to adapt or defer and is reported in Step 9.

If absent: check $ARGUMENTS for diagram hints (*.png, *.jpg, *.jpeg filename, erDiagram keyword, ||--o{ cardinality syntax).

  • Diagram hint present → Path A (Step 2.5).

  • No hint AND $ARGUMENTS describes what the app does (the typical case) → silently take Path B (Step 2.6 — spawn architect). No prompt.

  • No hint AND $ARGUMENTS is empty / non-descriptive → only then prompt with AskUserQuestion:

    "How would you like to define the data model? (a) I have an existing ER diagram to upload (PNG/JPG path, Mermaid syntax, or text description) (b) Let the data-model-architect agent analyze and propose one (default) (c) Cancel — I'll plan it elsewhere first"

    Default the answer to (b) so empty/cancel input auto-proceeds. The 99% case (user gave a description but no diagram) skips this prompt entirely.

Step 2a — Approved operation-manifest fast path

When $ARGUMENTS supplies all five paths below, record <operation_manifest_mode> = candidate:

  • --schema-contract <working_dir>/.tmp/dataverse-schema-contract.json
  • --approval-receipt <working_dir>/.tmp/mobile-plan-status.json
  • --execution-reconciliation <working_dir>/.tmp/dataverse-execution-reconciliation.json
  • --operation-manifest <working_dir>/.tmp/dataverse-operation-manifest.json
  • --publish-checkpoint <working_dir>/.tmp/dataverse-publish-pending.json

Do not reconstruct tables, columns, relationships, keys, payloads, tiers, or service requirements from Markdown on this path. The gate-owned approval receipt binds the exact structured contract content/hash, final plan hash, and final screen/service dependency list; native-app-plan.md remains the human review artifact.

An entirely absent fast-path handoff means <operation_manifest_mode> = fallback and preserves the standalone workflow below, beginning with Step 2 initialization. A partially supplied handoff, or a supplied manifest/contract/reconciliation/checkpoint that is malformed, stale, incomplete, or bound to different context/files, must fail closed: print the exact validation errors and return control to the orchestrator. Never jump to Step 4 without Step 2 initialization, partially trust a candidate, or mix its operations with agent-derived operations.

Step 2.5 — Path A: Parse user-provided diagram

Used when the user has an existing diagram from another tool (Visio, dbdiagram.io, screenshot, hand-drawn).

Accept three input formats:

FormatHow
Image path (*.png / *.jpg / *.jpeg)Use Read on the file path. The vision-capable model extracts entities, columns, relationships.
Mermaid syntaxUser pastes a erDiagram block in chat. Parse the entities, columns, and ||--o{ cardinalities directly.
Text descriptionUser types a structured description ("Account has many ServiceVisits; each ServiceVisit has many WorkItems and Photos"). Spawn data-model-architect agent in parse-only mode with the text as input.

Whichever format, normalize into the same structure used by the planner agent:

yaml
publisherPrefix: <from detected publisher prefix or user>
tables:
  - logicalName: contoso_servicevisit
    displayName: Service Visit
    status: new   # new | extend | reuse
    columns: [...]
    relationships: [...]

Then:

  1. Query existing Dataverse (Step 4 logic) to mark each table as new, modified, or reused.
  2. Generate a Mermaid ER diagram from the parsed structure for visual confirmation.
  3. Present back to the user via EnterPlanMode for approval.
  4. On ExitPlanMode, write the approved data model into native-app-plan.md ## Data Model section (creating the file if it doesn't exist).
  5. Continue to Step 3.

Step 2.6 — Path B: Spawn architect agent

If the user picked Path B (or the user-provided diagram parse failed), spawn the mobile-app:data-model-architect agent via Task (the mobile-app: plugin-name prefix is required) with the user's high-level requirements as input. The agent returns _dm_section.md. Embed it in native-app-plan.md, present via EnterPlanMode for approval, then continue to Step 3.

If they need new tables and refuse both paths, recommend they run /setup-datamodel (alias of this skill) explicitly, or native-app-planner for a full app-level plan. STOP if neither.

Step 3 — Setup Dataverse Web API auth

Required only if creating or extending tables. Skip to Step 5 for read-only add-data-source.

Step 3a — Environment consistency check

npx power-apps and az authenticate independently — they can point to different accounts. Verify power.config.json resolves and az can token for the target tenant before making any Dataverse API calls:

bash
ENV_JSON=$(node "${PLUGIN_ROOT}/scripts/resolve-environment.js" "$(node -e \"console.log(require('./power.config.json').environmentId)\")")
echo "$ENV_JSON"
az account show --query "{user: user.name, tenant: tenantId}" -o json

Compare the resolved environment URL with <envUrl> captured in Step 1. If they differ, STOP and warn:

"⚠️ Environment mismatch detected:

  • resolver reports: <resolved_env_url>
  • This project targets: <envUrl>

The Dataverse API token comes from az, which must target the same tenant as the selected environment. Run:

bash
az login --tenant <tenant-id>      # switch az to the right tenant

Then re-run /add-dataverse."

Do NOT proceed with table creation if environments don't match — you'll create tables in the wrong org.

Step 3b — Acquire token
bash
az account show --query "user.name" -o tsv

If empty, instruct az login and stop.

Script invocation contract — read this once, all subsequent calls in this skill follow it:

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> <METHOD> <apiPath> \
  [--body '<json>'] [--include-headers] \
  --tenant-id '<tenantId-from-resolve-environment>'
  • Three positional args, in order: <envUrl>, <METHOD> (GET / POST / PATCH / DELETE), <apiPath> (everything after /api/data/v9.2/).
  • Body is a flag, not positional. --body '<json>' — required for POST/PATCH, never for GET/DELETE. Forgetting --body and passing the JSON as a 4th positional arg returns a usage error.
  • --include-headers adds response headers (needed for OData-EntityId after a record create).
  • Output is JSON: { "status": <code>, "data": <body> }. Token refresh on 401 and back-off on 429 are automatic — never wrap with manual retry.

Pass the resolved tenant explicitly (HARD — saves discovery and survives fresh shells). resolve-environment.js already returned tenantId in Step 1. Substitute that literal value into every --tenant-id argument; do not rely on an exported or shell-local variable because separate tool executions may use fresh shells.

If the tenant is unknown, omit --tenant-id — discovery still works, it is just slower.

Acquire a Dataverse access token and verify connectivity:

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET WhoAmI \
  --tenant-id '<tenantId-from-resolve-environment>'

The explicit tenant is also reused for token refresh after a 401 and takes priority over shell environment variables and Azure account discovery.

WhoAmI is the Dataverse identity endpoint — capital W/A/I (case-sensitive). The response gives UserId, BusinessUnitId, OrganizationId but does NOT include the publisher prefix. To get the publisher prefix, query the solution's publisher (defaults to Default; pass a different solution name if the env uses a custom solution):

bash
node "${PLUGIN_ROOT}/scripts/detect-publisher-prefix.js" <envUrl> [solutionName] \
  --tenant-id '<tenantId-from-resolve-environment>'
# solutionName defaults to "Default" if omitted

This runs the OData query: /api/data/v9.2/solutions?$select=uniquename&$expand=publisherid($select=customizationprefix)&$filter=uniquename eq '<solutionName>'

Capture customizationprefix from the solution's publisher (typical value: cr123 → schema names like cr123_jobsite). Also capture the solution uniquename — needed for the --solution flag on every Step 5 / 5b POST so artifacts land in our solution rather than landing wherever Dataverse defaults. Write both to memory-bank.md Power Platform context block.

Requires the user to hold System Administrator or System Customizer in this environment.

When <operation_manifest_mode> = candidate, validate the manifest now against the resolved environment, tenant (when available), publisher, solution, current plan bytes, structured-schema bytes, and fresh reconciliation bytes:

bash
node "${PLUGIN_ROOT}/scripts/build-dataverse-operation-manifest.js" \
  --validate "<operation-manifest-path>" \
  --contract "<schema-contract-path>" \
  --approval-receipt "<approval-receipt-path>" \
  --reconciliation "<execution-reconciliation-path>" \
  --plan "<working_dir>/native-app-plan.md" \
  --environment-id "<environmentId>" \
  --env-url "<envUrl>" \
  --tenant-id "<tenantId>" \
  --publisher-prefix "<customizationprefix>" \
  --solution "<solution-uniquename>" \
  --publish-checkpoint "<publish-checkpoint-path>" \
  --require-executable

Validation deterministically rebuilds the expected manifest from the bound structured schema, fresh reconciliation, plan, context, and pending-publish checkpoint, then compares the complete decisions, services, aliases, phases, API paths, and bodies. If validation fails, print every reported mismatch and fail closed to the orchestrator. Do not execute or salvage individual operations and do not switch a supplied candidate to the standalone fallback.

Validate with --require-executable. Step 8 already performed the one fresh bounded reconciliation for every approved exact table and all of its columns/relationships/keys, including the child/parent/M:N relationship capability managed properties. Missing capability evidence fails closed. If the manifest remains non-executable, report its verification conflicts to the orchestrator. Do not add another read loop, change an approved decision, or enter fallback mode. A non-executable candidate authorizes no metadata write.

If validation with --require-executable succeeds, set <operation_manifest_mode> = valid and continue directly to Step 5's manifest execution branch. This is the fast-v2 path: it skips the repeated agent-driven full reconciliation, not any safety check.

Step 4 — Reconcile every planned table and column against the target

Telemetry checkpoint: reconcile_dataverse_schema

If <operation_manifest_mode> = valid, print:

✓ Approved operation manifest validated — complete fresh reconciliation and derived metadata coverage are bound to this environment.

Use its decisions as the reconciliation matrix and skip the remainder of Step 4/4a. Continue to Step 5. A valid manifest has no unverified items; its explicit reuse, adapt, and defer rows remain visible in the final summary.

Print before starting:

"→ Reconciling every planned table and column against live target metadata before any write…"

Do not use the custom-table list as the source of truth, and do not issue one request per table. Fetch every plan entry (Reuse, Extend, or Create) — including standard and managed dependencies — in a single filtered query that also expands their columns:

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions?\$select=MetadataId,LogicalName,SchemaName,IsCustomEntity,IsManaged,IsCustomizable,CanCreateAttributes,PrimaryIdAttribute,PrimaryNameAttribute&\$filter=LogicalName eq '<table1>' or LogicalName eq '<table2>'&\$expand=Attributes(\$select=MetadataId,LogicalName,AttributeType,AttributeTypeName,RequiredLevel,IsManaged,IsCustomizable,IsPrimaryId,IsPrimaryName,SourceType,SourceTypeMask)" \
  --tenant-id '<tenantId-from-resolve-environment>'

Build the $filter by OR-ing every planned logical name. This is the documented way to query multiple table definitions at once, and it replaces 2N requests (one entity GET plus one attributes GET per table) with one. Keep the $expand $select list to base AttributeMetadata properties only — a single query cannot cast to a derived column type, so fetch OptionSet details separately for the rare column that needs them.

Read the results as follows:

  • A planned name present in value[] — the table exists. Cache its expanded Attributes as that table's attribute snapshot for Steps 5a and 5b.
  • A planned name absent from value[] — the table does not exist. This is the equivalent of a 404 in the matrix below.
  • Interpret IsCustomizable and CanCreateAttributes as managed properties and read their .Value fields.

If the batched query itself fails (non-2xx), retry it once; if it fails again, split it into per-table queries so one unreadable name cannot hide the rest. Any name still unreadable after that is unverified: STOP before writes for that reconciliation scope. Authentication, permission, timeout, and malformed-response failures are not evidence that a name is free. If the URL would exceed a practical length with very many tables, split it into a few filtered queries — still far fewer than one request per table.

Only if the plan contains alternate keys or M:N relationships, add the matching expands so Steps 5b and 5d never need their own per-item probes. EntityDefinitions also supports expanding Keys, ManyToManyRelationships, ManyToOneRelationships, and OneToManyRelationships:

text
&$expand=Attributes($select=...),Keys($select=SchemaName,KeyAttributes,EntityKeyIndexStatus),ManyToManyRelationships($select=SchemaName)

Do not add these expands when the plan has no keys or M:N relationships — they enlarge the response for no benefit, and standard tables carry many of both.

Step 4a — Targeted derived-metadata barrier

The base attribute snapshot is sufficient for ordinary columns, but it cannot prove that a same-named lookup, choice, Boolean, or computed column has the same semantics. Before classifying any such existing column as compatible:

  1. Write the planned derived-column contract to <working_dir>/.tmp/derived-metadata-expected.json. Each row contains: table, logicalName, kind, type, sourceType, plus:

    • lookupTarget for lookups;
    • exact integer/label options for Choice, MultiSelect Choice, and Boolean;
    • exact sourceTypeMask and serialized formulaDefinition for an explicitly approved, maker-created computed dependency.
  2. Build one BATCH-METADATA GET operation list for the affected existing tables only. Reuse one process/token and query:

    • ManyToOneRelationships once per child table containing planned lookups;
    • the applicable derived attribute collections (PicklistAttributeMetadata, MultiSelectPicklistAttributeMetadata, BooleanAttributeMetadata) once per table/type, expanding OptionSet;
    • the applicable typed attribute collection once per table/type for any explicitly reused computed column, selecting LogicalName,SourceType,SourceTypeMask,FormulaDefinition.

    Do not issue one process per column and do not scan every customizable table. The exact planned names from Step 4 are the scope. Write the operation array to <working_dir>/.tmp/derived-metadata-operations.json, then run:

    bash
    node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> \
      BATCH-METADATA derived-reconciliation \
      --operations "$(cat <working_dir>/.tmp/derived-metadata-operations.json)" \
      --tenant-id '<tenantId-from-resolve-environment>'

    Do not pass --continue-on-error; the first unreadable required metadata collection must stop the barrier.

  3. Any non-2xx response, missing result slot, malformed option metadata, absent lookup target, or unavailable FormulaDefinition makes that scope unverified. STOP before writes. Authentication, throttling, permission, and parse failures are never compatibility evidence.

  4. Normalize the live results into <working_dir>/.tmp/derived-metadata-live.json. Each row uses: table, logicalName, type, sourceType, sourceTypeMask, lookupTargets, options: [{ value, label }], and formulaDefinition. Lookup target arrays must contain exactly the approved target. Choice mappings must be non-empty with unique integer values and non-empty labels; Boolean mappings must contain exactly values 0 and 1. Then run:

    bash
    node "${PLUGIN_ROOT}/scripts/validate-derived-metadata.js" \
      --expected "<working_dir>/.tmp/derived-metadata-expected.json" \
      --actual "<working_dir>/.tmp/derived-metadata-live.json"
  5. A lookup is compatible only when its complete target set matches. Planned choice values must exist with the same labels; extra live values are allowed. Ordinary planned columns require SourceType 0. A maker-created computed dependency is reusable only when its source type, source-type mask, and exact FormulaDefinition match the approved artifact; the Invalid mask bit always blocks reuse.

This phase is read-only and uses the V2 long-lived executor. It must not add per-column child-process/token overhead back into the fast path.

Build and print a reconciliation matrix before Step 5:

Target resultTable decisionColumn decisionsAction
Present; all planned base and derived metadata compatiblereuseexisting columns reuseNo schema write.
Present; custom columns missing; table customizable and can create attributesextendcompatible reuse; absent custom createQueue missing ordinary columns for sequential creation; relationships remain Pass 2.
Absent; plan says Create; logical name uses the verified publisher prefixcreateordinary columns create inline; lookups deferredCreate once after the complete-payload self-check.
Absent; plan says Reuse/Extend or dependency is standard/managed/required-existingdeferdependent columns deferNever recreate a standard or managed table. Drop the dependent lookups/columns from this run, continue with everything else, and list them under Deferred in Step 9.
Present; same-name column has incompatible AttributeType / AttributeTypeName.Valueextendincompatible column adaptAuto-rename the planned column via the probe sequence below, record it in the alias map, and create it alongside the existing one. Never modify or delete the existing column.
Present; columns missing but IsCustomizable.Value=false or CanCreateAttributes.Value=falsereusemissing columns deferThe target cannot be extended by this workflow. Reuse the columns that do exist, drop the rest from this run, and list them under Deferred in Step 9.
Batched query failed (non-2xx) after retry and per-table splitunverifiedunknownSTOP before writes for the affected reconciliation scope and surface the concrete environment/auth/permission error.

replace is not an automatic state in this workflow. Replacing a table or column requires an explicitly approved migration with dependency analysis and data movement, so a conflict resolves to adapt (rename beside it) or defer (leave it out) instead — both of which leave existing data untouched.

Decide-before-write barrier (HARD): finish reconciliation for every table and column before the first metadata write. Every item must come out of Step 4 as reuse, extend, create, adapt, or defer — never as an unresolved conflict. Deciding renames up front is what keeps relationships, screens, and sample data pointing at the same names.

No dead ends (HARD): a data-modelling conflict must never stop the run. Adapt it (rename beside the existing object) or defer it (drop it from this run), then keep going and report it in Step 9. Only environment faults stop this skill — failed auth, an environment mismatch, or a target the user has no privilege to write to. Those are not data-modelling problems and the user cannot resolve them by editing the plan.

Idempotency criterion (HARD): re-running this skill against an already-applied plan MUST perform zero metadata writes. Every table, column, relationship, key, and calc column resolves to reuse or an "already exists, skipped" outcome from the Step 4 snapshot. If a re-run issues any POST, the reconciliation missed something — report it rather than writing. Use this as the acceptance check after any change to Steps 4, 5, or 5a–5d.

Step 5 — Create / extend tables

Telemetry checkpoint: apply_dataverse_schema_changes

Valid operation-manifest execution branch

When <operation_manifest_mode> = valid, do not have an agent rebuild request bodies. Read execution.phases in this fixed order:

  1. tableCreates — dependency-tier table creates with all ordinary columns inline;
  2. extensions — missing ordinary columns on existing tables;
  3. relationships — lookups/1:N and M:N after both endpoints exist;
  4. alternateKeys — after target tables and columns exist;
  5. publish — one PublishXml operation only when earlier phases contain writes or a bound publish-pending checkpoint requires retry.

For each non-empty phase, write just that phase's operations array to <working_dir>/.tmp/dataverse-operation-phase-<name>.json. Read integritySha256 and binding.reconciliationSha256 from the validated manifest, then execute every phase with the same project-local atomic journal:

bash
EXECUTION_JOURNAL="<working_dir>/.tmp/dataverse-metadata-execution-journal.json"
ALL_MANIFEST_OPERATIONS="<working_dir>/.tmp/dataverse-operation-all.json"
# Write the flattened operations from every manifest phase to ALL_MANIFEST_OPERATIONS once.

node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> \
  BATCH-METADATA "manifest-<phase-name>" \
  --operations "$(cat <working_dir>/.tmp/dataverse-operation-phase-<name>.json)" \
  --solution "<solution-uniquename>" \
  --tenant-id "<tenantId>" \
  --journal "$EXECUTION_JOURNAL" \
  --manifest-file "$OPERATION_MANIFEST" \
  --manifest-hash "<manifest.integritySha256>" \
  --reconciliation-hash "<manifest.binding.reconciliationSha256>" \
  --manifest-operations "$(cat "$ALL_MANIFEST_OPERATIONS")"

Wait for the entire phase to finish before starting the next. This executor is not OData $batch; it sends one request at a time, reuses one token, preserves manifest order, and stops on the first non-2xx response. Never pass --continue-on-error, never parallelize phases or operations, and never execute service.requiredTables through BATCH-METADATA. The runner verifies the manifest file's integrity hash, requires the supplied operation array to equal one complete manifest phase byte-for-byte, and rejects that phase until every operation in preceding phases is journal-complete.

The runner atomically writes inFlight before each request and records each successful operation before moving to the next. Completed fingerprints are based on stable request identity, not the positional index; the complete manifest's unique zero-based order is validated separately. Completed fingerprints are skipped on an exact resume. If a process may have exited after Dataverse accepted a request but before the journal completion write, the runner fails with UNCERTAIN_METADATA_OPERATION; do not replay the old operation array. Transport loss during a metadata mutation is immediately uncertain and is never retried in-process; reads may retain transport retry behavior. Perform a new bounded exact reconciliation, rebuild and revalidate the full manifest, then resume with both new hashes. The runner mechanically treats an uncertain operation omitted by the new manifest as already applied/superseded, or retries it only when the fresh reconciliation proves it is still required.

If summary.metadataOperationCount is zero, issue zero metadata POSTs and print ↻ Dataverse schema already fully applied — zero metadata writes. This is the required idempotent rerun behavior after successful publish. A manifest with zero schema operations but one checkpoint-driven PublishXml operation must run that publish retry; it is not a zero-write completion.

The manifest builder writes <working_dir>/.tmp/dataverse-publish-pending.json before any schema POST when publish will be required. Leave this checkpoint in place after any schema or publish failure. Delete it only after the validated publish phase returns success. The next build validates its environment/solution/plan/contract binding and integrity, merges its table list into the publish phase, and therefore retries PublishXml even when every schema create is now idempotently skipped.

On a hidden POST-time name collision, stop at the failed operation and discard all not-yet-run phase arrays. The execution script must not choose Adapt or a rename. Return to the existing planning revision path so the structured schema artifact carries the approved Adapt names. Then perform a fresh bounded reconciliation and regenerate the complete aliases, downstream relationship and key bodies, service-required names, phases, manifest hashes, and phase files. Revalidate before resuming through the journal. Never continue an old array after a rename. Any non-collision failure stops the metadata path with its exact result.

Before overwriting the old manifest, preserve its path. After the revised plan and structured schema are approved through the existing flow, the top-level planner/orchestrator must refresh the structured service dependencies and mobile-plan-status.json receipt. This skill cannot create or restamp it. Bind the contract through that pre-existing receipt, then roll the existing publish checkpoint forward:

bash
node "${PLUGIN_ROOT}/scripts/build-dataverse-operation-manifest.js" \
  --roll-forward-checkpoint "$PUBLISH_CHECKPOINT" \
  --previous-manifest "$OPERATION_MANIFEST" \
  --journal "$EXECUTION_JOURNAL" \
  --contract "$SCHEMA_CONTRACT" \
  --approval-receipt "$APPROVAL_RECEIPT" \
  --plan "<working_dir>/native-app-plan.md" \
  --output "$PUBLISH_CHECKPOINT" \
  --environment-id "<environmentId>" \
  --env-url "<envUrl>" \
  --tenant-id "<tenantId>" \
  --publisher-prefix "<customizationprefix>" \
  --solution "<solution-uniquename>"

This retains prior checkpoint bindings/tables as integrity-protected history, keeps earlier successful tables publication-pending, and maps only the journal-proven failed collision table to its revised in-contract alias. It fails closed if a completed write would disappear from the revised contract or change definition: completed tables/inline columns, extension columns, relationships (including cascade behavior), and alternate keys must each map to an equivalent revised structured component. It also rejects any unrelated out-of-contract publish target. Only after this succeeds may Step 8 overwrite the operation manifest.

The manifest builder never emits calculated/rollup/formula creation. Reused computed dependencies have already crossed the exact derived-metadata barrier; unsupported projections are explicit defer rows. After the publish phase succeeds, delete the publish checkpoint and continue to Step 6. When there were zero writes and no checkpoint, continue without deleting anything. Skip the fallback mutation instructions in Steps 5a–5d and skip Step 6b because publish was already part of the validated phase order.

Print before starting:

"→ Creating/extending tables in tier order (sequential — Dataverse serializes metadata writes). For each: pre-flight check, then 'Creating …' before the POST and '✓ ' on 2xx response."

⚠️ Concurrency rule — do not violate. All Dataverse metadata operations in Steps 5, 6, and 6b are strictly sequential: issue one HTTP request, wait for a 2xx response, then issue the next. Do NOT parallelize or use OData $batch. Dataverse serializes metadata writes via an exclusive lock; parallel calls return 429 TooManyRequests, MetadataLockHeldException, or 404 EntityNotFound for lookups whose parent hasn't committed yet.

Specifically:

  • Within a tier: create tables one at a time.
  • Across tiers: Tier 0 fully done (all tables + all columns committed) before any Tier 1 POST.
  • Lookups: POST to /RelationshipDefinitions only after both endpoint tables exist and have returned 2xx.
  • Extensions: column POSTs to an existing table are also serial — same lock applies.

For multiple already-reconciled operations, prefer the local BATCH-METADATA executor. It is not OData $batch: one Node process reuses one token and issues requests strictly one at a time in array order, stopping on the first non-2xx response by default.

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> \
  BATCH-METADATA schema-writes \
  --operations '<ordered-json-array>' \
  --solution '<solution-uniquename-from-memory-bank>' \
  --tenant-id '<tenantId-from-resolve-environment>'

Each operation is { "index", "method", "apiPath", "body" }; an operation may override the command-level solution. Build the array only after the full metadata snapshot and desired/live diff. Preserve dependency order: new tables with ordinary columns inline, extension columns, relationships, projections, then alternate keys. Never pass --continue-on-error for schema creation. The result includes per-operation status and durationMs; after a failure, reconcile that component and resume with only the remaining operations.

Step 5a — Pre-flight collision check (from the Step 4 snapshot)

Before each create, confirm the target name is actually free: name-prefix collisions from stale solutions, reserved system names, and soft-deleted tombstones all fail the POST, and Dataverse takes ~1 minute to return the conflict error. A failure here can leave Tier 0 partially created and make a Tier 1 lookup fail on a phantom parent. Step 4 already collected this evidence for every planned name, so this step reads it rather than re-querying.

For every Create entry, resolve its target state from the Step 4 batch — do not re-query per table. Step 4 already fetched every planned logical name, so reuse that result:

Step 4 result for this nameMeaningAction
Absent from value[]Name is freeProceed with POST.
Present + IsCustomEntity: true + MetadataId matches memory-bankWe created this earlier — idempotent re-runSkip the POST, mark as created, continue.
Present + IsCustomEntity: true + MetadataId not in memory-bankForeign collisionReconcile live columns and customization properties below; never auto-extend an uncustomizable target.
Present + IsCustomEntity: falseReserved system table nameAuto-recover via rename (see below).

Only re-probe a single name when Step 4's batch did not cover it (for example a rename candidate generated later in this step):

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions(LogicalName='<prefix>_<table>')?\$select=MetadataId,LogicalName,IsCustomEntity,IsManaged,IsCustomizable,CanCreateAttributes" \
  --tenant-id '<tenantId-from-resolve-environment>'

Tombstones and hidden collisions are not reliably visible to either form — Dataverse can report a name as free and still reject the POST minutes later. Those are caught by the POST-time collision rescue below, which is the real safety net:

POST responseMeaningAction
5xx with 0x80060890 or message "object with same name exists in solution"Tombstone (soft-deleted, ~30 min purge TTL)Auto-recover via rename (see below).
400 with 0x80044363, "schema name ... is not unique", or "same name already exists"Hidden Dataverse collision / recent-delete tombstoneAuto-recover via rename (see below), then retry the POST once.

Important: treat a POST-time collision as a recoverable name conflict, not a data-model failure — the schema name can stay reserved internally after a delete even when metadata reports it as free.

Auto-recovery — reuse/extend first, rename as last resort

Priority order when Step 5a hits a name collision:

  1. Adopt as Extend (preferred) — only if the existing table is the same concept, every same-name column is type-compatible, planned missing columns are custom additions, and live IsCustomizable.Value plus CanCreateAttributes.Value both permit extension. Add only the missing columns via Step 5b and log → Extending existing <original> with <N> missing columns.
  2. Adopt as Reuse — if the existing table's schema already covers all planned columns: skip Step 5b for this entry, keep it in Step 6 for service generation. No prompt. Log → Reusing existing <original> (all required columns present).
  3. Rename and Create (last resort) — only when the existing table is a fundamentally different entity (e.g., planned table is an inspection log but existing <original> is a payroll record — incompatible concept, incompatible columns). Prompt the user before proceeding.

When to auto-decide vs. prompt:

SituationAction
Foreign collision + compatible concept/schema + extension allowedAuto-Extend (no prompt)
Foreign collision + all planned columns presentAuto-Reuse (no prompt)
Foreign collision + incompatible column or extension forbiddenAuto-rename the conflicting column beside it, or defer it (no prompt)
Foreign collision + incompatible conceptPrompt (see below)
Reserved system nameAuto-rename (no prompt)
Tombstone (0x80060890 / same-name-exists)Auto-rename (no prompt)

For the incompatible-concept case only — prompt via AskUserQuestion:

| Option | What it means |
|---|---|
| Rename and Create (default) | Use a free custom logical name for the genuinely different entity. Existing table stays untouched. |
| Reuse existing as-is | Point the generated services at the existing table and skip the planned columns it lacks. |

Never offer Extend for an incompatible concept or column shape. This prompt is a preference, not a gate: an empty, skipped, or unanswered response defaults to Rename and Create so the run always proceeds.

Maintain a run-level logical-name alias map for every auto-rename. Example:

json
{ "cr3e9_aircraft": "cr3e9_aircraftv2" }

Before building any later table, column, lookup relationship, sample-data payload, service-reference text, or screen data spec, resolve logical names through this map. A rename that only changes the table POST but leaves relationships/screens/sample data pointing at the old name is a bug.

Auto-rename probe sequence (cap at 4 probes — only used for reserved/tombstone cases):

<original>v2  →  <original>v3  →  <original>2  →  <original>copy

For each candidate in order, GET EntityDefinitions(LogicalName='<candidate>')?$select=MetadataId,IsCustomEntity:

  • 404 → free, take it, stop probing.
  • 200 or 5xx (collision) → next candidate.

If all 4 collide, keep probing <original>3, <original>4, … through <original>20. This sequence is designed never to dead-end: if even those collide, use <original><4-char run token>, which is unique to this run. Never abandon a table for want of a free name.

On a successful auto-rename, do these in order BEFORE the POST:

  1. Update native-app-plan.mdEdit with replace_all: true to swap the old logical name for the new one across the entire ## Data Model section (Mermaid ER, Reuse/Extend/Create table, Creation Order, Notes). This catches downstream relationship POSTs in this same Step 5 too.
  2. Update ## Screens per-screen specs — same replace_all sweep for any service / data-source references using the old name.
  3. Append to memory-bank.md Collision history<original> → <new> with reason (foreign / reserved / tombstone) and timestamp.
  4. Update the run-level alias map — every later metadata payload and plan edit resolves <original> to <new> before use.
  5. Inform the user — single line, no prompt:

    → Collision on <original> (<foreign|reserved|tombstone>). Renamed to <new> and updated plan + memory-bank. Continuing.

Then proceed with the POST using <new>.

Post-create collision rescue — hidden tombstone / recent delete

If the Step 5b table POST fails after a 404 preflight with any Dataverse name-collision signature, do not fail the run:

  • HTTP 400 with code 0x80044363
  • message contains schema name and not unique
  • message contains same name already exists
  • message contains object with same name exists in solution

First attempt auto-Extend: compare the plan against that table's attribute snapshot from Step 4 (re-fetch only if it is absent). If ≥50% overlap, switch to Extend path (add missing columns). Otherwise, run the auto-rename probe sequence, update native-app-plan.md, ## Screens, memory-bank.md, and the run-level alias map, then retry the table POST exactly once with the resolved name. Print:

→ Dataverse still has <original> reserved from a recent delete/hidden collision. Using <new> and continuing.

If the retry also returns a collision signature, continue probing the remaining candidates, then the numeric tail, then the run-token form described above.

On successful POST, immediately re-GET to capture the server-assigned MetadataId and write it to memory-bank (Step 6d updates .datamodel-manifest.json; you also append to memory-bank.md under "Created tables" with the GUID and solution name). This lets future /add-dataverse runs distinguish "we own this" from "name collision."

Step 5b — Create / extend

Run this step in two explicit passes:

  1. Pass 1 — tables + ordinary columns: create every new table with all planned non-lookup columns inline, then extend existing tables with any missing non-lookup columns. Computed formula definitions are never synthesized by this workflow.
  2. Pass 2 — lookups + relationships: only after Pass 1 has succeeded for every tier, create the planned RelationshipDefinitions. A lookup is created by its relationship and must not appear in a table's initial Attributes array.

Both passes remain strictly sequential. Do not use $batch for metadata writes.

For each Create decision, in tier order (Tier 0 → Tier 1 → Tier 2 → …), POST a new EntityDefinition. Skip if Step 5a returned a known-self match (idempotent).

⚠️ Inline ALL planned columns into the Create POST body — do NOT POST columns individually.

Dataverse accepts all non-lookup columns in the initial table's Attributes: [...] array. Inline form: 1 round trip, ~3-8s. Per-column form: N+1 round trips, each ~3-8s. For a 5-column table that's roughly 24s saved on the lock-serialized metadata path. Do not describe this metadata create as transactionally atomic: if the request fails after Dataverse starts processing it, the table or some attributes may remain, which is why the recovery path below exists.

Wrong (N round trips):

json
{ "SchemaName": "...", "Attributes": [{ /* primary only */ }] }
// then 4× POST /Attributes for the rest

Right (1 round trip):

json
{
  "SchemaName": "...",
  "Attributes": [
    { /* primary name */ },
    { /* column 2 */ },
    { /* column 3 */ },
    { /* column 4 */ },
    { /* column 5 */ }
  ]
}

The per-column POST path remains valid for two cases only: (1) Extend on an existing table, (2) retry-after-partial-failure when Step 5a's pre-flight shows the table exists but some columns don't.

Solution targeting (HARD): every Step 5 / 5b POST MUST pass --solution <uniquename> so Dataverse routes the new artifact into our solution rather than the unmanaged default. Read the solution name from memory-bank.md Power Platform context (captured in Step 3b). Without this flag, multi-project environments end up with cross-solution leakage and the foreign-collision class of bug returns. The script translates --solution to the MSCRM.SolutionUniqueName HTTP header.

Scratch files: When writing request body JSON to disk (e.g. table definitions, column metadata, relationship payloads), always write to <working_dir>/.tmp/, never to /tmp/. Keeping request bodies project-local prevents cross-project writes and makes cleanup deterministic. Create the folder if it doesn't exist: mkdir -p <working_dir>/.tmp.

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST EntityDefinitions \
  --body '<json-body-with-all-columns-inline>' \
  --solution '<solution-uniquename-from-memory-bank>' \
  --tenant-id '<tenantId-from-resolve-environment>'

Complete-payload self-check (HARD — do this before the POST, no extra tooling): re-read the body you just built against the plan and confirm all five statements. If any fails, fix the body and re-check; never POST a partial table and repair it with per-column POSTs.

  1. Every planned ordinary column is present — String, Memo, Integer, BigInt, Decimal, Money, DateTime, Boolean, Choice, MultiSelect Choice, Image, and File. Count Attributes[] and compare with the plan's column count for this table.
  2. No lookup metadata is inline — no LookupAttributeMetadata, CustomerAttributeMetadata, or OwnerAttributeMetadata. Those are created by their relationship in Pass 2.
  3. No deferred or server-owned column is inline — no primary-id column and no calculated/rollup column (Step 5c owns those).
  4. Exactly one IsPrimaryName: true attribute exists, and PrimaryNameAttribute matches its SchemaName (lowercased logical form).
  5. No duplicate SchemaName in Attributes[] (compare case-insensitively).

Microsoft documents both halves of this contract: ordinary columns may be included when the table is created, while a lookup is created with its one-to-many relationship. dataverse-request.js stays the only script in this path — it already owns auth, retry, --solution routing, and 401/429 handling.

Body skeleton — all planned columns inline in Attributes: [...] (this example shows primary + 3 additional; expand the array to fit every column from the plan):

⚠️ IsAvailableOffline + ChangeTrackingEnabled MUST be set to true at create time for any table the app intends to make available offline. Without these two flags the table cannot be added to a mobileofflineprofile, and /setup-offline-profile will have to fix them via a separate metadata PUT (the /enable-tables-offline skill handles that, but it doubles the metadata-lock-serialized round trips). Empirically verified 2026-05-18 in the chanel-rm demo: 7 custom tables created without these flags caused 7 prereq-revert drift entries; fixed by post-hoc enablement. Default these to true for all UserOwned tables created by /add-dataverse unless the user has explicitly opted out of offline support. The flags are no-ops at runtime for apps that don't use offline profiles.

json
{
  "@odata.type": "Microsoft.Dynamics.CRM.EntityMetadata",
  "SchemaName": "cr123_jobsite",
  "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "Job Site", "LanguageCode": 1033 }] },
  "DisplayCollectionName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "Job Sites", "LanguageCode": 1033 }] },
  "OwnershipType": "UserOwned",
  "HasActivities": false,
  "HasNotes": false,
  "IsAvailableOffline": true,
  "ChangeTrackingEnabled": true,
  "PrimaryNameAttribute": "cr123_sitename",
  "Attributes": [
    {
      "@odata.type": "Microsoft.Dynamics.CRM.StringAttributeMetadata",
      "SchemaName": "cr123_sitename",
      "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "Site Name", "LanguageCode": 1033 }] },
      "MaxLength": 200,
      "FormatName": { "Value": "Text" },
      "RequiredLevel": { "Value": "ApplicationRequired" },
      "IsPrimaryName": true
    },
    {
      "@odata.type": "Microsoft.Dynamics.CRM.StringAttributeMetadata",
      "SchemaName": "cr123_address",
      "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "Address", "LanguageCode": 1033 }] },
      "MaxLength": 500,
      "FormatName": { "Value": "Text" },
      "RequiredLevel": { "Value": "None" }
    },
    {
      "@odata.type": "Microsoft.Dynamics.CRM.IntegerAttributeMetadata",
      "SchemaName": "cr123_squarefeet",
      "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "Square Feet", "LanguageCode": 1033 }] },
      "RequiredLevel": { "Value": "None" },
      "MinValue": 0,
      "MaxValue": 2147483647,
      "Format": "None"
    },
    {
      "@odata.type": "Microsoft.Dynamics.CRM.BooleanAttributeMetadata",
      "SchemaName": "cr123_active",
      "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "Active", "LanguageCode": 1033 }] },
      "RequiredLevel": { "Value": "None" },
      "DefaultValue": true,
      "OptionSet": {
        "@odata.type": "Microsoft.Dynamics.CRM.BooleanOptionSetMetadata",
        "TrueOption": { "Value": 1, "Label": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "Yes", "LanguageCode": 1033 }] } },
        "FalseOption": { "Value": 0, "Label": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "No", "LanguageCode": 1033 }] } }
      }
    }
  ]
}

For each Extend decision, POST a new column to the existing table.

⚠️ Table-level pre-flight (HARD — required for idempotent re-runs). Reuse the complete attribute snapshot fetched for this table in Step 4. If the table was discovered only during collision recovery, or no current snapshot exists, fetch all attributes exactly once:

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions(LogicalName='<table>')/Attributes?\$select=MetadataId,LogicalName,SchemaName,AttributeType,AttributeTypeName,RequiredLevel,IsManaged,IsCustomizable,IsPrimaryId,IsPrimaryName" \
  --tenant-id '<tenantId-from-resolve-environment>'

Build a local { lowerCaseLogicalName → { AttributeType, AttributeTypeName, IsManaged, IsCustomizable } } map and classify every planned non-lookup column before issuing any POST. Prefer AttributeTypeName.Value when AttributeType is Virtual, so File and Image columns are not incorrectly treated as compatible generic virtual attributes:

Snapshot resultAction
Name exists and AttributeType matchesSkip it and log ↻ <column> (already exists, skipped).
Name exists and AttributeType differsDataverse does not allow column-type changes via API, so auto-rename the planned column using the same probe sequence (<column>v2<column>v3<column>2 → …), add it to the alias map, and create it beside the existing one. Log → <column> exists as <existingType>; created <newName> as <plannedType> instead. Never modify or delete the existing column.
Name is absentAdd it to the ordered missing-column queue.

This single snapshot catches partial creates, corrected re-runs, and network-drop recovery without paying one GET round trip per column.

After the complete comparison passes, POST the missing-column queue one column at a time, sequentially (no $batch; always pass --solution):

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST \
  "EntityDefinitions(LogicalName='<table>')/Attributes" \
  --body '<column-json>' \
  --solution '<solution-uniquename-from-memory-bank>' \
  --tenant-id '<tenantId-from-resolve-environment>'

Recovery after a partial Create: do not re-POST the whole EntityDefinitions body because the table now exists and Dataverse returns 0x80060888. Fetch that table's complete attribute snapshot once, run the same local comparison, and sequentially POST only the missing non-lookup columns. This is the only time a table originally classified as Create should use the per-column path.

Column shapes that have non-obvious gotchas (handle carefully):

  • Pass-2 barrier (HARD) — do not create any lookup or relationship while Pass 1 is still creating or extending tables. Accumulate relationship definitions, wait until every table and ordinary column has returned 2xx, then process the relationships sequentially in dependency order.

  • Lookup — POST to /RelationshipDefinitions, not /Attributes.

    ⚠️ Do NOT improvise the body. Copy the skeleton below verbatim and replace only the placeholders in <> brackets.

    Fields that cause silent failure if added:

    • Do NOT include ReferencingAttribute. Dataverse auto-creates the foreign-key column from Lookup.SchemaName. Including it causes 404: Could not find an attribute with specified name because the column doesn't exist yet at POST time.
    • Do NOT include Lookup.LogicalName. It's read-only metadata; including it returns 400 Bad Request.
    • Do NOT include ReferencedAttribute. Dataverse resolves the primary key of the referenced entity automatically. The reference is optional and omitting it is the correct default.

    Required fields: SchemaName, ReferencedEntity, ReferencingEntity, Lookup.{@odata.type, SchemaName, DisplayName, RequiredLevel}, AssociatedMenuConfiguration, CascadeConfiguration (including RollupView). Anything else is invented — drop it.

    json
    {
      "@odata.type": "Microsoft.Dynamics.CRM.OneToManyRelationshipMetadata",
      "SchemaName": "<prefix>_<Parent>_<Child>",
      "ReferencedEntity": "<parent_table_logical_name>",
      "ReferencingEntity": "<child_table_logical_name>",
      "Lookup": {
        "@odata.type": "Microsoft.Dynamics.CRM.LookupAttributeMetadata",
        "SchemaName": "<Prefix>_<Parent>Id",
        "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "@odata.type": "Microsoft.Dynamics.CRM.LocalizedLabel", "Label": "<Parent Display Name>", "LanguageCode": 1033 }] },
        "RequiredLevel": { "Value": "None" }
      },
      "AssociatedMenuConfiguration": { "Behavior": "UseCollectionName", "Group": "Details", "Order": 10000 },
      "CascadeConfiguration": {
        "Assign": "NoCascade",
        "Delete": "RemoveLink",
        "Merge": "NoCascade",
        "Reparent": "NoCascade",
        "Share": "NoCascade",
        "Unshare": "NoCascade",
        "RollupView": "NoCascade"
      }
    }

    Invocation (apiPath is RelationshipDefinitions, body via --body, always pass --solution):

    bash
    node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST \
      RelationshipDefinitions \
      --body '<json-body-from-skeleton-above>' \
      --solution '<solution-uniquename-from-memory-bank>' \
      --tenant-id '<tenantId-from-resolve-environment>'

    Pre-flight the lookup (HARD — required for idempotent re-runs). A lookup can only pre-exist if the referencing (child) table already existed at Step 4, so when the child was created in this run, skip the probe and POST. Otherwise look for the lookup's foreign-key column — the lowercased Lookup.SchemaName, e.g. <prefix>_<parent>id — in that child table's Step 4 attribute snapshot:

    Snapshot resultAction
    Present with AttributeType: LookupSkip the POST and log ↻ <SchemaName> (relationship already exists, skipped).
    Present with any other AttributeTypeA non-lookup column already owns that name. Auto-rename the lookup's Lookup.SchemaName via the probe sequence, record it in the alias map, and POST the relationship with the new name. Never overwrite the existing column.
    AbsentPOST the relationship.

    This costs no extra round trip: the referencing attribute is an ordinary attribute on the child table, so it is already in the snapshot Step 4 fetched. Without this check a re-run POSTs a duplicate relationship and fails the run mid-Pass-2.

  • Many-to-Many (M:N) — also POST to /RelationshipDefinitions, but with ManyToManyRelationshipMetadata. Dataverse creates an auto-named intersect table.

    ⚠️ Do NOT improvise the body. Required fields: SchemaName, Entity1LogicalName, Entity2LogicalName, IntersectEntityName, and the two AssociatedMenuConfiguration blocks. Do not include lookup or cascade fields — those are 1:N concepts.

    json
    {
      "@odata.type": "Microsoft.Dynamics.CRM.ManyToManyRelationshipMetadata",
      "SchemaName": "<prefix>_<table1>_<table2>",
      "Entity1LogicalName": "<table1_logical_name>",
      "Entity2LogicalName": "<table2_logical_name>",
      "IntersectEntityName": "<prefix>_<table1>_<table2>",
      "Entity1AssociatedMenuConfiguration": {
        "Behavior": "UseLabel",
        "Group": "Details",
        "Label": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "@odata.type": "Microsoft.Dynamics.CRM.LocalizedLabel", "Label": "<Table2 Plural>", "LanguageCode": 1033 }] },
        "Order": 10000
      },
      "Entity2AssociatedMenuConfiguration": {
        "Behavior": "UseLabel",
        "Group": "Details",
        "Label": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "@odata.type": "Microsoft.Dynamics.CRM.LocalizedLabel", "Label": "<Table1 Plural>", "LanguageCode": 1033 }] },
        "Order": 10000
      }
    }

    Pre-flight M:N: a relationship can only pre-exist on a table that already existed at Step 4. If either endpoint was just created in this run, skip the probe — nothing can be there. Otherwise read ManyToManyRelationships from that table's Step 4 snapshot: present → skip (already exists); absent → proceed. Query RelationshipDefinitions(SchemaName='<prefix>_<table1>_<table2>')?$select=SchemaName only when the snapshot did not cover it.

    In the generated service: M:N relationships are queried via the intersect entity name (e.g., cr123_tag_inspection) — the SDK does not expose a direct M:N navigation helper; the screen-builder must query the intersect table directly. Flag this in the Step 7 summary if any M:N relationships are created.

  • Column @odata.type and required fields — reference table (verified against Dataverse OData API):

    Dataverse type@odata.typeRequired extra fields
    Single-line textMicrosoft.Dynamics.CRM.StringAttributeMetadataMaxLength (200), FormatName: { "Value": "Text" } — values: Text, Email, Url, Phone, TextArea
    Multi-line textMicrosoft.Dynamics.CRM.MemoAttributeMetadataMaxLength (10000), Format: "TextArea"
    Whole numberMicrosoft.Dynamics.CRM.IntegerAttributeMetadataMinValue, MaxValue, Format: "None"
    DecimalMicrosoft.Dynamics.CRM.DecimalAttributeMetadataMinValue, MaxValue, Precision (2)
    Currency (Money)Microsoft.Dynamics.CRM.MoneyAttributeMetadataMinValue, MaxValue, Precision (2), PrecisionSource (2)
    Date/TimeMicrosoft.Dynamics.CRM.DateTimeAttributeMetadataFormat: "DateAndTime" or "DateOnly", DateTimeBehavior: { "Value": "UserLocal" }
    BooleanMicrosoft.Dynamics.CRM.BooleanAttributeMetadataDefaultValue, OptionSet with TrueOption/FalseOption
    Choice (picklist)Microsoft.Dynamics.CRM.PicklistAttributeMetadataOptionSet with IsGlobal: false, OptionSetType: "Picklist", Options[]option integer values start at 100000000 and increment by 1
    Lookupvia RelationshipDefinitions — see 1:N skeleton above
    ImageMicrosoft.Dynamics.CRM.ImageAttributeMetadataMaxSizeInKB (default 10240), CanStoreFullImage
    FileMicrosoft.Dynamics.CRM.FileAttributeMetadataMaxSizeInKB

    Common mistake: omitting FormatName on String columns and DateTimeBehavior on DateTime columns. Both are required — Dataverse rejects the POST without them.

  • Choice (option set) — set OptionSet.IsGlobal: false for local picklists. Full body (option values start at 100000000 and increment by 1):

    json
    {
      "@odata.type": "Microsoft.Dynamics.CRM.PicklistAttributeMetadata",
      "SchemaName": "<Prefix>_<ColumnName>",
      "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "@odata.type": "Microsoft.Dynamics.CRM.LocalizedLabel", "Label": "<Display Name>", "LanguageCode": 1033 }] },
      "RequiredLevel": { "Value": "None" },
      "OptionSet": {
        "@odata.type": "Microsoft.Dynamics.CRM.OptionSetMetadata",
        "IsGlobal": false,
        "OptionSetType": "Picklist",
        "Options": [
          { "Value": 100000000, "Label": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "@odata.type": "Microsoft.Dynamics.CRM.LocalizedLabel", "Label": "Option 1", "LanguageCode": 1033 }] } },
          { "Value": 100000001, "Label": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "@odata.type": "Microsoft.Dynamics.CRM.LocalizedLabel", "Label": "Option 2", "LanguageCode": 1033 }] } }
        ]
      }
    }
  • Image@odata.type: Microsoft.Dynamics.CRM.ImageAttributeMetadata, MaxSizeInKB and CanStoreFullImage. Dataverse always reports MaxHeight: 144 and MaxWidth: 144 for the generated thumbnail; those values cannot be changed and must not be used as full-image dimensions. Set CanStoreFullImage: true when users must inspect or download the retained full-size image. Updating this setting requires retrieving the complete current ImageAttributeMetadata, changing the writable property, sending a full-definition PUT, and publishing customizations.

  • File@odata.type: Microsoft.Dynamics.CRM.FileAttributeMetadata, MaxSizeInKB required

If the column type is not a simple string/int/boolean, surface a one-line confirmation to the user before posting.

After all mutations, re-run the existing-tables query (Step 4) to confirm everything landed.

Step 5c — Enforce the supported computed-column boundary

Dataverse metadata exposes FormulaDefinition, but Microsoft explicitly does not support defining calculated, rollup, or formula expressions through code. Legacy workflow XAML and generated formula serialization must not be synthesized.

  • Do not invoke create-calculated-column.js; it is a fail-closed guard for legacy callers.
  • Cross-entity fields must use a supported formatted lookup annotation or bounded chained fetch as documented in data-performance.md.
  • For a hot list field that cannot use either path, mark it external-projection-required and omit it from this mutation run. The user may create a formula column in Power Apps or supply another server-owned projection outside this PR, then rerun Step 4a to validate and reuse it.
  • Never create an ordinary copied field without an explicit refresh owner.

Reference: https://learn.microsoft.com/power-apps/developer/data-platform/specialized-columns

Step 5d — Create alternate keys for unique business identifiers

Print before starting:

"→ Creating alternate keys for columns marked unique in the data model (one HTTP call per key). Skip if no unique columns are planned."

Run condition: the ## Data Model section marks a non-primary column as unique / alternate key / natural key. Common examples: QR Code Value, SKU, external ID, employee number, asset tag. Skip primary IDs and skip columns whose type Dataverse cannot index as an alternate key (file/image, memo/long text, multi-select choice, calculated/rollup, customer/owner lookups).

Ordering: run after the target table and target columns exist, and before Step 6b publish. Alternate-key index activation is asynchronous; creation may return success while the key status is Pending.

Do NOT use the CreateEntityKey action route. In practice it can return 404 depending on route shape / environment. The reliable metadata route is POSTing to the table's Keys navigation collection:

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST \
  "EntityDefinitions(LogicalName='<table>')/Keys" \
  --body '<entity-key-json>' \
  --solution '<solution-uniquename-from-memory-bank>' \
  --tenant-id '<tenantId-from-resolve-environment>'

Body skeleton:

json
{
  "@odata.type": "Microsoft.Dynamics.CRM.EntityKeyMetadata",
  "SchemaName": "<prefix>_<table>_<column>_key",
  "DisplayName": { "@odata.type": "Microsoft.Dynamics.CRM.Label", "LocalizedLabels": [{ "Label": "<Column display> Key", "LanguageCode": 1033 }] },
  "KeyAttributes": ["<column_logical_name>"]
}

Pre-flight each key before POST so re-runs are idempotent. A key can only pre-exist on a table that already existed at Step 4, so for a table created in this run, skip straight to the POST. Otherwise read Keys from that table's Step 4 snapshot. Query it directly only when the snapshot did not cover that table:

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions(LogicalName='<table>')?\$select=LogicalName&\$expand=Keys(\$select=SchemaName,KeyAttributes,EntityKeyIndexStatus)" \
  --tenant-id '<tenantId-from-resolve-environment>'
Existing key stateAction
Same SchemaName or same KeyAttributes exists with Active / PendingSkip POST; record the key in .datamodel-manifest.json.
Same SchemaName exists with FailedSurface the failure and stop; Dataverse requires deleting/recreating the key manually or changing the planned key name.
No matching keyPOST to EntityDefinitions(LogicalName='<table>')/Keys.

After POST: a 204 response is success. Re-query the Keys expand above and capture EntityKeyIndexStatus. If it is Pending, continue the scaffold but add a memory-bank follow-up: alternate key <schema> pending index activation. Do not rely on duplicate enforcement in manual tests until the status reaches Active.

Add alternate keys to .datamodel-manifest.json for the table:

json
"alternateKeys": [
  { "schemaName": "cr123_item_code_key", "keyAttributes": ["cr123_code"], "indexStatus": "Pending" }
]

Step 6 — Add data sources

Telemetry checkpoint: generate_dataverse_data_sources

Print before starting:

"→ Generating TypeScript services for tables via npx power-apps add-data-source (sequential). Print '✓ Service.ts' after each."

When <operation_manifest_mode> = valid, set SERVICE_REQUIRED_TABLES from service.requiredTables[].logicalName. Keep the manifest's resolved adapted names and exclude only explicit deferred rows. Service generation remains sequential outside BATCH-METADATA.

For each table in SERVICE_REQUIRED_TABLES (regardless of reuse/extend/create), generate the TS layer from the app root. Do not derive this list from Creation Order alone because reused tables are intentionally absent from creation tiers. The CLI reads the environment ID from power.config.json; pass the environment URL resolved earlier in the skill:

bash
npx power-apps add-data-source --api-id dataverse --org-url <envUrl> --resource-name <table-logical-name>

Run one at a time — sequentially, not in parallel. The Power Apps CLI writes src/generated/connectorSchemas.ts and other generated files non-atomically; concurrent invocations corrupt them.

After generation, verify the output created by npx power-apps add-data-source rather than guessing a JSON path or service filename. The command writes Dataverse configuration under the literal databaseReferences["default.cds"].dataSources key and derives service filenames from each entry's entitySetName, which may differ from the table logical name. The verifier also accepts the legacy nested databaseReferences.default.cds shape:

bash
node "${PLUGIN_ROOT}/scripts/verify-dataverse-services.js" \
  --project-root "<working_dir>" \
  --manifest "$OPERATION_MANIFEST"

For the standalone fallback path without a manifest, pass the resolved service list as --tables "<comma-separated-logical-names>". If any reused or custom table is missing from config, lacks entitySetName, or has no matching generated service, STOP before screen generation:

text
BLOCKED: required Dataverse service missing for <logical-name>. Schema action=<reuse|extend|create>; app usage=<screens/hooks that require it>.

Step 6b — Publish customizations

Telemetry checkpoint: publish_dataverse_customizations

When <operation_manifest_mode> = valid, skip this step: the validated manifest's final publish phase already ran and its pending checkpoint was deleted, or the manifest proved there were zero metadata writes and no pending publish retry.

Print before starting:

"→ Publishing customizations (PublishXml) so new tables/columns become queryable. ~5–20 seconds."

Only after every Step 5 metadata POST and every Step 6 npx power-apps add-data-source has returned successfully, publish so the new tables and columns are available to the runtime. PublishXml takes the same exclusive metadata lock as the create/extend calls — do not run it concurrently with anything from Steps 5 or 6.

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> POST \
  "PublishXml" \
  --body "{\"ParameterXml\":\"<importexportxml><entities><entity>cr123_table1</entity><entity>cr123_table2</entity></entities></importexportxml>\"}" \
  --tenant-id '<tenantId-from-resolve-environment>'

Build the entity list from all tables that were created or extended in Steps 4–5. Skip reused-as-is tables — they don't need republishing.

If the publish call returns a non-2xx status, report the error and stop — do not proceed. The user must resolve before the tables are usable.

Step 6c — Verify tables exist

Telemetry checkpoint: verify_dataverse_schema

Confirm every table in SERVICE_REQUIRED_TABLES, including reused-as-is tables, plus any created or extended table, is queryable after publication when needed. Use the resolved effective names from the approved operation manifest or the standalone path's verified service list, not Creation Order alone. Use one filtered query for the bounded set, not one request per table:

bash
node "${PLUGIN_ROOT}/scripts/dataverse-request.js" <envUrl> GET \
  "EntityDefinitions?\$select=LogicalName,DisplayName&\$filter=LogicalName eq '<table1>' or LogicalName eq '<table2>'" \
  --tenant-id '<tenantId-from-resolve-environment>'
  • Every expected name present in value[] → confirmed.
  • Any expected name missing → schema/service verification is incomplete. Return to the owning reconciliation step; do not mark that table materialized or invent a new table to replace a missing reuse target.

Step 6d — Write .datamodel-manifest.json

After schema verification in Step 6c and generated-service verification in Step 6 both pass, write the manifest to the project root using the Write tool. This is the application's verified table inventory, not a schema-write log; a reuse-only app must still have a populated manifest:

json
{
  "environmentUrl": "<envUrl>",
  "generatedAt": "<ISO timestamp>",
  "tables": [
    {
      "logicalName": "cr123_jobsite",
      "displayName": "Job Site",
      "status": "new",
      "metadataId": "<server-assigned GUID from Step 5a re-GET>",
      "solution": "<solution unique name, e.g. PowerAppsDefault>",
      "columns": [
        { "logicalName": "cr123_sitename", "type": "String" },
        { "logicalName": "cr123_address",  "type": "String" }
      ]
    }
  ]
}

metadataId and solution are required for status: "new" or "extended" entries — they're how Step 5a distinguishes "we own this on a re-run" from "name collision." Reused tables can omit both.

Include every service-required table confirmed in Step 6c, including tables reused with no schema changes, plus verified new/extended tables. Use status: "reused" for unchanged existing tables; retain "new" and "extended" only for their actual outcomes. Preserve effective adapted names, entity-set names, and verified column/relationship/key facts from reconciliation and any post-write metadata reads. Exclude deferred or unverified tables.

Before returning, check that every SERVICE_REQUIRED_TABLES name occurs in the manifest and has verified generated service output. A partial or empty manifest from an earlier run is repaired by repeating Step 6's read-only service verifier and Steps 6c–6d, not by replaying successful schema writes. Recording a reused table does not authorize a metadata POST or republish; the existing sample-data record-count checks and standard-system-table exclusions still apply.

Step 7 — Inspect generated files

text
Glob: src/generated/services/*Service.ts
Glob: src/generated/models/*Model.ts

For each table, check the generated service exposes the expected methods:

text
Grep pattern="async (create|getAll|getById|update|delete|upload|downloadFile|downloadImage)" path="src/generated/services/<Table>Service.ts"

If the table has file or image columns, confirm the service includes upload, downloadFile, downloadImage, deleteFileOrImage — and the model exposes <Table>FileColumnName / <Table>ImageColumnName union types.

File/image column UI controls: When a generated table has File or Image columns, note this in the summary so screen-builders apply the host controls from @microsoft/power-apps-native-host:

  • File columns<FilePicker>; upload bytes separately via the generated service's upload method after the main create/update.
  • Image columns<ImagePicker>; capture PickedImageInfo via onImageChange and persist through generated upload(...) after the main create/update.
  • Read/view flows → use generated downloadFile(...) / downloadImage(...) helpers for existing attachments/previews.

Full usage pattern and the native-wrapper boundary live in /add-native; screen-builder keeps only the concise JSX enforcement rule.

PDF/signature artifact schema guidance: If the approved plan mentions generated PDFs, PDF evidence packets, approvals, signatures, sign-off, ink, or drawings, preserve the storage decision in the Dataverse model instead of defaulting to text fields.

User needDataverse shapeWrite pattern
Generated PDF report that must be retainedFile column on the parent record, or child Evidence/Attachment table with a File columnCreate/update parent row first, then call generated Service.upload(parentId, '<fileColumn>', file)
Generated PDF report that is only transientNo Dataverse column requiredGenerate locally with expo-print only when present; share with expo-sharing only when present; do not route local URI to native PDF viewer
Captured signature/sign-off imageImage column when the latest signature belongs on the parent rowStrip data:image/png;base64, if the generated service expects raw base64, then include image payload in the update body
Multiple signatures, sketches, evidence images, or audit attachmentsChild Evidence/Attachment table with Image/File columns and lookup to parentCreate child row first, then include Image payload or upload File bytes through generated service helpers

Signature image normalization example:

ts
const signatureBase64 = signatureDataUri.replace(/^data:image\/png;base64,/, '');
const result = await Cr123_approvalService.update(approvalId, {
  cr123_signatureimage: signatureBase64,
  cr123_signedat: new Date().toISOString(),
});

if (!result.success) {
  throw new Error(result.error?.message ?? 'Signature image was not saved.');
}

File upload after parent row exists example:

ts
const save = await Cr123_inspectionService.update(inspectionId, {
  cr123_reportgeneratedat: new Date().toISOString(),
});

if (!save.success) {
  throw new Error(save.error?.message ?? 'Inspection was not saved.');
}

const upload = await Cr123_inspectionService.upload(inspectionId, 'cr123_reportfile', reportFile);

if (!upload.success) {
  throw new Error(upload.error?.message ?? 'Inspection report was not uploaded.');
}

Step 8 — Type-check

Telemetry checkpoint: validate_dataverse_integration

Print before starting:

"→ Regenerating connector schemas + running tsc to verify generated services compile (~15–30 seconds)."

npx power-apps add-data-source (Step 5) wrote new files into .power/schemas/<connector>/. The connectorSchemas.ts consumed by app/_layout.tsx is now stale — regenerate it before type-checking, otherwise the new tables won't be wired into the runtime schema map and tsc will pass against an out-of-date snapshot:

bash
npm run generate-schemas
npx tsc --noEmit

Fix any errors. Common: missing peer dependencies — npx expo install <package>.

Step 8.5 — Offline profile reconciliation

A schema change here (new table or new column) can leave an existing Mobile Offline Profile behind — new tables never sync to devices and new columns come down blank. Reconcile the profile with what you just created.

Skip this step entirely when $ARGUMENTS contains --skip-planning (the orchestrator-invoked path). /create-mobile-app, /setup-datamodel, and /edit-app own offline reconciliation in their own flow, so running it here too would double-prompt.

Otherwise (manual /add-dataverse), run the local, no-network delta check:

bash
node "${PLUGIN_ROOT}/scripts/offline-profile-delta.js"

Branch on the JSON status per offline-profile-reconciliation.md:

statusAction
no-manifest / no-profile / in-syncContinue to Step 9 silently. For no-profile (no offline profile exists) do not nag — the app may not use offline.
erroroffline-profile.json is unreadable — the script prints status: error and exits non-zero. Do NOT treat this as an /add-dataverse failure (the tables are already created): surface the error string, skip reconciliation (never drive the update workflows against a corrupt file), and finish with DONE_WITH_CONCERNS telling the user to fix offline-profile.json.
deltaPrompt the user (one AskUserQuestion, default = update now) to add the missing tables / new columns. For missingTables[], read and execute ${PLUGIN_ROOT}/skills/add-table-to-offline-profile/SKILL.md; for tablesWithNewColumns[], read and execute ${PLUGIN_ROOT}/skills/edit-offline-profile/SKILL.md with --table <t> --columns add:<newColumns>. Re-run the delta check; it should read in-sync. Follow the exact prompt + ordering in the reconciliation reference.

Step 9 — Summary

✅ Dataverse added
─────────────────────────────────────────────
Environment   : <envUrl>
Tables reused : <list>
Tables extended: <list (columns added)>
Tables created : <list (in tier order)>
Adapted       : <renamed table/column → new name, and why. Omit the line if none.>
Deferred      : <items left out of this run and why, e.g. "cr123_note (target not customizable)". Omit the line if none.>
Operation manifest: <validated path, operation count, or "standalone fallback">

Generated services:
  src/generated/services/<Table>Service.ts × N
Generated models:
  src/generated/models/<Table>Model.ts × N

Type-check: PASS

Sample usage:

  import { Cr123_jobsiteService } from '../../src/generated/services/Cr123_jobsiteService';

  const result = await Cr123_jobsiteService.getAll({
    select: ['cr123_sitename', 'cr123_address'],
    filter: 'statecode eq 0',
    orderBy: ['cr123_sitename asc'],
    top: 50,
  });
  const sites = result.data ?? [];

⚠️  First call triggers Dataverse OAuth consent via the native player's
    `<scheme>://oauth-callback` deep link.

Next:
  /add-sample-data        # Seed each new table with 5-10 realistic rows so the
                          # app's home screen shows real-looking data on first launch.
─────────────────────────────────────────────

After printing the summary, offer one-click sample-data seeding — but only when invoked manually (not from /create-mobile-app, which handles this in its own Step 8.5).

  • If $ARGUMENTS contains --skip-planning (the orchestrator-invoked path): skip the prompt. The orchestrator invokes /add-sample-data separately.

  • Otherwise (manual invocation), if the manifest contains any tables, ask:

    "Seed tables with sample records so the app shows real-looking data on first launch? (yes / no — default: yes)"

    Default to "yes" so empty input auto-proceeds. On "yes", invoke /add-sample-data. On "no", print "→ Skipped sample data. Run /add-sample-data later to populate." and stop.

Key Rules

  • Always use generated services (e.g., Cr123_jobsiteService.getAll()) — never fetch / axios directly.
  • Result data lives at result.data, not result itself.
  • Don't edit files under src/generated/ — they are regenerated on every npx power-apps add-data-source.
  • Picklist (Choice) fields, virtual fields, lookups, and file/image columns each have non-obvious gotchas. Keep references/dataverse-reference.md aligned with this skill.
  • A valid operation manifest removes repeated agent reconciliation; it does not change Dataverse's serialized metadata-lock latency. Real matched A/B runs remain required before claiming an end-to-end timing range.
  • When a Dataverse Web API behavior is uncertain (lookup write syntax, $expand nav property names, choice column shape, batch semantics, error format), query the microsoft-learn MCP server before guessing. See shared/shared-instructions.md → Microsoft Learn MCP. Guessed Dataverse syntax silently 400s.

Reference

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Add Dataverse AI skill do?

Use when the user wants to add Dataverse tables (existing or new) to a Power Apps mobile app, extend an existing Dataverse table with new columns, or apply an approved data model plan.

Why use Add Dataverse on TypingMind?

Because you install it once and use it with any model. Add Dataverse is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Add Dataverse in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/power-platform-skills/tree/main/plugins/mobile-apps/skills/add-dataverse. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Add Dataverse?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Add Dataverse?

As many as you like. As long as a model supports skills, you can use Add Dataverse with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Add Dataverse AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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