Checked-in instructions can provide shared persistent context beyond one chat session. That principle is applicable when copilot repeatedly suggests unapproved naming and schema conventions after developers open new chat sessions. It does not explain the selected change in the current case, which depends on tool visibility and database identities form separate layers of least-privilege control.

Tenant governance and human validation limit risky generated actions. That principle is applicable when an organization enables code assistance in Fabric notebooks and wants generated database statements to remain under least privilege. It does not explain the selected change in the current case, which depends on tool visibility and database identities form separate layers of least-privilege control.

AI code completion helps draft SQL but does not replace authentication, permissions or testing. That principle is applicable when a SQL team wants contextual AI code suggestions inside its approved repository workflow while retaining human review of generated queries. It does not explain the selected change in the current case, which depends on tool visibility and database identities form separate layers of least-privilege control.

Suggestions align with naming and parameterization conventions during a test prompt. That observation would validate a different requirement: a repository has conventions requiring parameterized queries, predictable object naming and no embedded secrets in generated SQL. Here the required evidence is schema discovery succeeds but a DML tool call is denied.

A security review confirms no live secrets or unauthorized personal data enter prompts. That observation would validate a different requirement: a developer plans to paste production connection strings and customer rows into an external generative coding assistant to debug SQL. Here the required evidence is schema discovery succeeds but a DML tool call is denied.

Security logs identify the principal and metadata-read operation. That observation would validate a different requirement: a team must audit which SQL schemas were exposed through an MCP endpoint to an AI developer tool. Here the required evidence is schema discovery succeeds but a DML tool call is denied.

An MCP server offers structured tools, while the connection policy determines what the assistant can access. Although relevant to a Copilot session must inspect schema metadata from a permitted SQL Server MCP endpoint with least privilege, this action would not correct the recorded production failure: hiding a tool name in the UI alone does not revoke the connected identity's rights. Use the target remedy instead.

Checked-in instructions can provide shared persistent context beyond one chat session. Although relevant to copilot repeatedly suggests unapproved naming and schema conventions after developers open new chat sessions, this action would not correct the recorded production failure: hiding a tool name in the UI alone does not revoke the connected identity's rights. Use the target remedy instead.

Tenant governance and human validation limit risky generated actions. Although relevant to an organization enables code assistance in Fabric notebooks and wants generated database statements to remain under least privilege, this action would not correct the recorded production failure: hiding a tool name in the UI alone does not revoke the connected identity's rights. Use the target remedy instead.

Tool selection and invocation policy control actions the assistant may request. That method solves a different requirement: a developer uses an AI-assisted SQL chat and needs to prevent the model from executing schema-changing operations without consent. The current case instead requires maintain repository instruction files with approved SQL schema and review conventions.

AI code completion helps draft SQL but does not replace authentication, permissions or testing. That method solves a different requirement: a SQL team wants contextual AI code suggestions inside its approved repository workflow while retaining human review of generated queries. The current case instead requires maintain repository instruction files with approved SQL schema and review conventions.

An MCP server offers structured tools, while the connection policy determines what the assistant can access. That method solves a different requirement: a Copilot session must inspect schema metadata from a permitted SQL Server MCP endpoint with least privilege. The current case instead requires maintain repository instruction files with approved SQL schema and review conventions.

Tenant governance and human validation limit risky generated actions. That principle is applicable when an organization enables code assistance in Fabric notebooks and wants generated database statements to remain under least privilege. It does not explain the selected change in the current case, which depends on checked-in instructions can provide shared persistent context beyond one chat session.

Tool visibility and database identities form separate layers of least-privilege control. That principle is applicable when an MCP tool can read production schema and execute writes, but the SQL developer only needs read-only planning support. It does not explain the selected change in the current case, which depends on checked-in instructions can provide shared persistent context beyond one chat session.

MCP server registration does not replace data plane permissions and source governance. That principle is applicable when a Fabric lakehouse MCP server offers data tools but a coding assistant must not query sensitive data outside the approved workspace. It does not explain the selected change in the current case, which depends on checked-in instructions can provide shared persistent context beyond one chat session.

A security review confirms no live secrets or unauthorized personal data enter prompts. That observation would validate a different requirement: a developer plans to paste production connection strings and customer rows into an external generative coding assistant to debug SQL. Here the required evidence is new assistant sessions produce suggestions matching the documented project rules.

A quote-containing input stays data and cannot append additional SQL commands. That observation would validate a different requirement: a developer asks a coding assistant to generate dynamic SQL by interpolating an untrusted customer search string. Here the required evidence is new assistant sessions produce suggestions matching the documented project rules.

Security logs identify the principal and metadata-read operation. That observation would validate a different requirement: a team must audit which SQL schemas were exposed through an MCP endpoint to an AI developer tool. Here the required evidence is new assistant sessions produce suggestions matching the documented project rules.

Generated code must meet the same injection and authorization standards as hand-written code. Although relevant to a developer asks a coding assistant to generate dynamic SQL by interpolating an untrusted customer search string, this action would not correct the recorded production failure: a one-off chat instruction does not reliably govern future contributors. Use the target remedy instead.

AI code completion helps draft SQL but does not replace authentication, permissions or testing. Although relevant to a SQL team wants contextual AI code suggestions inside its approved repository workflow while retaining human review of generated queries, this action would not correct the recorded production failure: a one-off chat instruction does not reliably govern future contributors. Use the target remedy instead.

Tenant governance and human validation limit risky generated actions. Although relevant to an organization enables code assistance in Fabric notebooks and wants generated database statements to remain under least privilege, this action would not correct the recorded production failure: a one-off chat instruction does not reliably govern future contributors. Use the target remedy instead.

Tool visibility and database identities form separate layers of least-privilege control. That method solves a different requirement: an MCP tool can read production schema and execute writes, but the SQL developer only needs read-only planning support. The current case instead requires register only the approved server endpoint with workspace-scoped authorization and minimal accessible tools.

AI code completion helps draft SQL but does not replace authentication, permissions or testing. That method solves a different requirement: a SQL team wants contextual AI code suggestions inside its approved repository workflow while retaining human review of generated queries. The current case instead requires register only the approved server endpoint with workspace-scoped authorization and minimal accessible tools.

Generated code must meet the same injection and authorization standards as hand-written code. That method solves a different requirement: a developer asks a coding assistant to generate dynamic SQL by interpolating an untrusted customer search string. The current case instead requires register only the approved server endpoint with workspace-scoped authorization and minimal accessible tools.

Tool selection and invocation policy control actions the assistant may request. That principle is applicable when a developer uses an AI-assisted SQL chat and needs to prevent the model from executing schema-changing operations without consent. It does not explain the selected change in the current case, which depends on mCP server registration does not replace data plane permissions and source governance.

Tenant governance and human validation limit risky generated actions. That principle is applicable when an organization enables code assistance in Fabric notebooks and wants generated database statements to remain under least privilege. It does not explain the selected change in the current case, which depends on mCP server registration does not replace data plane permissions and source governance.

Checked-in instructions can provide shared persistent context beyond one chat session. That principle is applicable when copilot repeatedly suggests unapproved naming and schema conventions after developers open new chat sessions. It does not explain the selected change in the current case, which depends on mCP server registration does not replace data plane permissions and source governance.

Suggestions align with naming and parameterization conventions during a test prompt. That observation would validate a different requirement: a repository has conventions requiring parameterized queries, predictable object naming and no embedded secrets in generated SQL. Here the required evidence is a workspace-authorized read works and cross-workspace access is denied.

A security review confirms no live secrets or unauthorized personal data enter prompts. That observation would validate a different requirement: a developer plans to paste production connection strings and customer rows into an external generative coding assistant to debug SQL. Here the required evidence is a workspace-authorized read works and cross-workspace access is denied.

Schema discovery succeeds but a DML tool call is denied. That observation would validate a different requirement: an MCP tool can read production schema and execute writes, but the SQL developer only needs read-only planning support. Here the required evidence is a workspace-authorized read works and cross-workspace access is denied.

AI code completion helps draft SQL but does not replace authentication, permissions or testing. Although relevant to a SQL team wants contextual AI code suggestions inside its approved repository workflow while retaining human review of generated queries, this action would not correct the recorded production failure: using a personal full-access token bypasses service-scoped controls. Use the target remedy instead.

Generated code must meet the same injection and authorization standards as hand-written code. Although relevant to a developer asks a coding assistant to generate dynamic SQL by interpolating an untrusted customer search string, this action would not correct the recorded production failure: using a personal full-access token bypasses service-scoped controls. Use the target remedy instead.

Tool selection and invocation policy control actions the assistant may request. Although relevant to a developer uses an AI-assisted SQL chat and needs to prevent the model from executing schema-changing operations without consent, this action would not correct the recorded production failure: using a personal full-access token bypasses service-scoped controls. Use the target remedy instead.