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Restore earlier receptionist settings

restore_ai_setup_version
Destructive

Undoes changes made with update_ai_setup or update_service_area by putting those same settings back to what they were in an earlier published version (version numbers come from get_ai_setup or from an update result). Goes live for callers straight away and is itself saved as a new version. Settings those tools cannot change are left as they are now. A version published from the Nexwin dashboard doesn't record its list of areas, so restoring one leaves the service area as it is; the result says so. Before calling, tell the user which version is being restored and get their explicit yes; then pass confirm: true.

Input Schema

NameRequiredDescriptionDefault
confirmYestrue only after the user has explicitly approved restoring this version in the conversation
versionYesThe published version to go back to

Output Schema

NameRequiredDescriptionDefault
changesYes
messageYes
successYes
versionNo
liveWarningYes
_environmentYesThe Nexwin country and environment that supplied the result
restoredFromNo
previousVersionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes well beyond the destructiveHint/readOnlyHint annotations: it discloses that the change goes live for callers immediately, that the restore is itself saved as a new version, that unmanaged settings are left alone, and that versions published from the dashboard omit their area list so the service area is left untouched and the result reports this. The confirmation protocol is also spelled out.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense paragraph that front-loads what the tool does and what it affects, then the dashboard caveat, then the confirmation requirement. Every clause carries information, though the length sits near the upper bound for a two-parameter tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers the mutation's blast radius, the version-source question, the dashboard-version edge case, and the approval requirement; with an output schema present it need not describe return values, and annotations already carry the safety profile.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: it tells the agent where version numbers originate and that confirm must only be true after explicit user approval, reinforcing the schema's own wording with procedural context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (restore earlier published settings) and frames it as the inverse of two named siblings, update_ai_setup and update_service_area. An agent can distinguish it from get_ai_setup (read) and the update tools (forward mutation) immediately.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains the condition that selects this tool (undoing changes made by the update tools) and where valid version numbers come from (get_ai_setup or an update result), plus an explicit prerequisite to get user approval before calling. It stops short of stating when not to use it, e.g. that settings outside those tools' reach cannot be changed here.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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