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Callers reach the intended business operation through a stable contract with its security boundary explicit. This result validates Custom connector boundary versus plug-in endpoint instead of the component in question. Here the specific acceptance check is: The service accesses only approved rows and forbidden updates fail even when made through a direct Web API call.

The UX extension runs in its intended host, remains maintainable and respects platform permissions. This result validates Choosing client scripts PCF or code apps instead of the component in question. Here the specific acceptance check is: The service accesses only approved rows and forbidden updates fail even when made through a direct Web API call.

The agent executes only permitted actions and produces traceable responses under the invoking user's entitlements. This result validates Agent integration architecture using Copilot Studio instead of the component in question. Here the specific acceptance check is: The service accesses only approved rows and forbidden updates fail even when made through a direct Web API call.

Power Apps and flows call the function with stable typed payloads and receive normalized responses without brittle client parsing. This result validates Azure Function-backed connector transformation instead of the component in question. Here the specific acceptance check is: The connector surfaces callable typed actions that send valid requests to the intended backend.

The business event arrives with enough immutable identifier and operation context for safe downstream handling. This result validates Dataverse IServiceEndpointNotificationService event publish instead of the component in question. Here the specific acceptance check is: The connector surfaces callable typed actions that send valid requests to the intended backend.

Callers authenticate through the intended identity and connector policies modify only approved request fields. This result validates Custom connector OAuth and policy templates instead of the component in question. Here the specific acceptance check is: The connector surfaces callable typed actions that send valid requests to the intended backend.

Inspect environment-variable definition/default/current values, connection-reference binding, deployment settings and secret-storage policy. This step belongs to Environment variables and connection references rather than the complementary pair here. The required action is: Use Microsoft Foundry for custom coded model orchestration requiring extensible agent engineering and integrate through supported Power Platform endpoints when needed. And its evidence is: Check runtime customization needs, agent tools, API authentication, connector or MCP interface, usage monitoring and data access policy.

Select Copilot Studio for an agent integrated into Power Platform and define governed actions, identity, channels and Dataverse access before adding external models. This step belongs to Agent integration architecture using Copilot Studio rather than the complementary pair here. The required action is: Use Microsoft Foundry for custom coded model orchestration requiring extensible agent engineering and integrate through supported Power Platform endpoints when needed. And its evidence is: Check runtime customization needs, agent tools, API authentication, connector or MCP interface, usage monitoring and data access policy.

The managed solution imports into a clean test environment without unexplained missing dependency failures. This step belongs to Solution component dependency management rather than the complementary pair here. The required action is: Use Microsoft Foundry for custom coded model orchestration requiring extensible agent engineering and integrate through supported Power Platform endpoints when needed. And its evidence is: Check runtime customization needs, agent tools, API authentication, connector or MCP interface, usage monitoring and data access policy.

Keep related Dataverse tables, flows, connection references and plug-in registrations in a versioned solution and resolve dependencies before import. That action addresses Solution component dependency management instead. A flow in a solution still requires its connector references and dependent tables to be present in the target. For this case, the targeted action is: Apply Dataverse security roles, teams and business-unit ownership plus application-user permissions to authorize the component at the correct data scope.

Choose a standard Dataverse table for native persistence and offline-style features, and a virtual table when live external rows must remain at their source and provider limitations are accepted. That action addresses Standard versus virtual Dataverse tables instead. Virtual tables surface external data but do not automatically inherit every capability of Dataverse-stored tables. For this case, the targeted action is: Apply Dataverse security roles, teams and business-unit ownership plus application-user permissions to authorize the component at the correct data scope.

Evaluate an elastic table for high-volume partitioned Dataverse workloads only after confirming partition keys, feature limits and transactional requirements. That action addresses Elastic table and high-volume data pattern instead. Elastic tables differ from standard tables; their scale benefits do not eliminate data-model and partition tradeoffs. For this case, the targeted action is: Apply Dataverse security roles, teams and business-unit ownership plus application-user permissions to authorize the component at the correct data scope.

Invalid records are rejected with a clear supported error before unnecessary downstream logic runs. This result validates Dataverse PreValidation plug-in and aborting operations instead of the component in question. Here the specific acceptance check is: The additional value is saved atomically with the original request without an extra update recursion.

The unattended flow continues after an employee leaves and fails safely on permission or data errors. This result validates Dataverse connector service principal and retry policies instead of the component in question. Here the specific acceptance check is: The additional value is saved atomically with the original request without an extra update recursion.

Optional fields do not crash the run and required dates or numbers are validated before updates. This result validates Power Automate expressions null coalesce and safe parsing instead of the component in question. Here the specific acceptance check is: The additional value is saved atomically with the original request without an extra update recursion.

Use supported code-app Dataverse data APIs to perform CRUD and read table metadata with correct logical names, permissions and paging. This step belongs to Code app Dataverse metadata and table operations rather than the complementary pair here. The required action is: Read environment variables via supported Power Platform mechanism and keep endpoints, feature flags and tenant configuration separate from code. And its evidence is: Inspect solution variable current values, environment ownership, deployment settings and fallback behavior.

Inspect event handler properties, passExecutionContext setting, formContext acquisition, loaded form attributes and handler scope. This step belongs to Model-driven formContext from execution context rather than the complementary pair here. The required action is: Read environment variables via supported Power Platform mechanism and keep endpoints, feature flags and tenant configuration separate from code. And its evidence is: Inspect solution variable current values, environment ownership, deployment settings and fallback behavior.

The code app loads necessary resources under restrictive policy and blocks unauthorized third-party script execution. This step belongs to Code app Content Security Policy configuration rather than the complementary pair here. The required action is: Read environment variables via supported Power Platform mechanism and keep endpoints, feature flags and tenant configuration separate from code. And its evidence is: Inspect solution variable current values, environment ownership, deployment settings and fallback behavior.

Configure allowed origins for scripts, styles, connections and frames according to the code app CSP rather than setting a permissive wildcard. That action addresses Code app Content Security Policy configuration instead. A CSP error cannot be reliably fixed by disabling every restriction; precise origins should be justified. For this case, the targeted action is: Use supported code-app Dataverse data APIs to perform CRUD and read table metadata with correct logical names, permissions and paging.

Configure a code app's Power Platform connections and permissions using supported connection references rather than direct embedded API secrets. That action addresses Power Apps code app connectors and environment binding instead. Code apps still require appropriate app and data-source authorization even with a custom React frontend. For this case, the targeted action is: Use supported code-app Dataverse data APIs to perform CRUD and read table metadata with correct logical names, permissions and paging.

Connect a code app to an authorized Copilot Studio agent through a supported client interface while validating user consent and action permissions. That action addresses Code app consuming Copilot Studio agent instead. Agent output is untrusted user-facing content; it cannot override application authorization or approval. For this case, the targeted action is: Use supported code-app Dataverse data APIs to perform CRUD and read table metadata with correct logical names, permissions and paging.

Use Azure Functions to offload expensive work from synchronous Dataverse plug-ins while authenticating separately and tracking completion. This step belongs to Azure Functions for long-running Dataverse work rather than the complementary pair here. The required action is: Configure timer or queue triggers with schedule, delivery guarantees, failure behavior and concurrency suited to the Power Platform job. And its evidence is: Inspect cron schedule timezone, trigger binding, retry policy, poison queue, idempotent key and host instance scaling.

Inspect MCP tool descriptions, allowed identity, read/write separation, approval gates, payload validation and agent run logs. This step belongs to Microsoft Foundry agent tool access via MCP servers rather than the complementary pair here. The required action is: Configure timer or queue triggers with schedule, delivery guarantees, failure behavior and concurrency suited to the Power Platform job. And its evidence is: Inspect cron schedule timezone, trigger binding, retry policy, poison queue, idempotent key and host instance scaling.

The handler reliably detects a value transition even when the incoming Update contains only changed columns. This step belongs to Plug-in preimage postimage and filtering attributes rather than the complementary pair here. The required action is: Configure timer or queue triggers with schedule, delivery guarantees, failure behavior and concurrency suited to the Power Platform job. And its evidence is: Inspect cron schedule timezone, trigger binding, retry policy, poison queue, idempotent key and host instance scaling.

The application presents agent output in the right user session and aborted requests do not execute delayed unintended writes. This result validates Copilot Studio client library consumption instead of the component in question. Here the specific acceptance check is: The unattended flow continues after an employee leaves and fails safely on permission or data errors.

Secrets stay out of ordinary run logs while operations retain auditable success and failure metadata. This result validates Secure inputs outputs Key Vault and secret handling instead of the component in question. Here the specific acceptance check is: The unattended flow continues after an employee leaves and fails safely on permission or data errors.

Long-running processing completes independently of the initiating save and reports its final status later. This result validates Azure Functions for long-running Dataverse work instead of the component in question. Here the specific acceptance check is: The unattended flow continues after an employee leaves and fails safely on permission or data errors.

Compare host form lifecycle, accessibility, reuse, data access, application complexity and deployment requirements. These checks are relevant to Choosing client scripts PCF or code apps, but are not the most discriminating first evidence for this case. Inspect instead: Check data ownership, virtual table provider, supported CRUD behavior, security, auditing and expected query performance.

Inspect environment-variable definition/default/current values, connection-reference binding, deployment settings and secret-storage policy. These checks are relevant to Environment variables and connection references, but are not the most discriminating first evidence for this case. Inspect instead: Check data ownership, virtual table provider, supported CRUD behavior, security, auditing and expected query performance.

Inspect role privileges at access levels, ownership, team membership, row sharing, managed-environment policy and effective caller identity. These checks are relevant to Least-privilege technical authorization design, but are not the most discriminating first evidence for this case. Inspect instead: Check data ownership, virtual table provider, supported CRUD behavior, security, auditing and expected query performance.

Inspect custom API uniqueness, bound/unbound setting, parameters, Execute privilege, registration and returned response shape. These checks are relevant to Dataverse custom API contract and plug-in execution, but are not the most discriminating first evidence for this case. Inspect instead: Check execution stage, message, Target entity, attribute presence, filtering attributes and transaction log.

Inspect request URI, OData filters, prefer header, continuation link, lookup annotation and calling user privileges. These checks are relevant to Dataverse OData Web API select filter and pagination, but are not the most discriminating first evidence for this case. Inspect instead: Check execution stage, message, Target entity, attribute presence, filtering attributes and transaction log.

Inspect batch boundaries, supported message types, transaction failure behavior, service-protection limits and rollback plan. These checks are relevant to ExecuteMultiple transactions and batch scope, but are not the most discriminating first evidence for this case. Inspect instead: Check execution stage, message, Target entity, attribute presence, filtering attributes and transaction log.