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update_wedding_settings

DestructiveIdempotent

Update wedding details like title, date, city, or guest count. Only changed fields are applied; unchanged settings stay intact, with confirmation before saving.

Instructions

Update top-level wedding settings. Provide only the fields you want to change; the rest are preserved. Asks the user to confirm first: a confirmation prompt where the client supports one; otherwise the first call returns a preview and a confirmToken, and only a repeat call with that token proceeds (see MCP_CONFIRM_MODE).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo
slugNoURL slug — appears in the public website URL. Changing it breaks every link and QR code already shared or printed with the old URL
titleNoWedding title (e.g., "Alex & Jordan")
hashtagNoe.g. #alexjordan2026 — empty string clears it
guest_countNo
confirmTokenNoONLY for the two-step confirmation fallback (a client without MCP elicitation). The confirmToken from this same tool's phase-1 "confirmation-required" response, passed back ONLY after the user has seen that preview and explicitly approved it in chat — never on the first call, never invented, never reused. Call again with the same arguments. Ignored when the client supports elicitation.
wedding_dateNoYYYY-MM-DD
state_provinceNo
owner_last_nameNo
owner_first_nameNo
partner_last_nameNo
enable_search_zolaNoAllow Zola search to find the site
partner_first_nameNo
enable_search_engineNoAllow search engines (Google, etc.) to index the site

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.1.4
    • addedInput schema / properties / confirmToken
      Added value: +{
      +  "description": "ONLY for the two-step confirmation fallback (a client without MCP elicitation). The confirmToken from this same tool's phase-1 \"confirmation-required\" response, passed back ONLY after the user has seen that preview and explicitly approved it in chat — never on the first call, never invented, never reused. Call again with the same arguments. Ignored when the client supports elicitation.",
      +  "type": "string"
      +}
  2. Changed2 schema fields changedv2.1.2
    • changedInput schema / properties / hashtag / description
      Previous value: -"e.g. #merchris2026 — empty string clears it"New value: +"e.g. #alexjordan2026 — empty string clears it"
    • changedInput schema / properties / slug / description
      Previous value: -"URL slug — appears in the public website URL"New value: +"URL slug — appears in the public website URL. Changing it breaks every link and QR code already shared or printed with the old URL"
  3. Changed1 schema field changedv2.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  4. First observedv1.4.2

TDQS

A4.6/5.0
Behavior5/5

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

The description goes well beyond the idempotent/destructive annotations by revealing the confirmation workflow: a native prompt when supported, otherwise a preview + confirmToken in phase 1 and a repeated call to commit. It also discloses non-destructive partial update behavior (unspecified fields preserved), which is exactly the kind of behavioral trait an agent needs before invoking a destructive-looking update.

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

Conciseness5/5

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

The description is two dense sentences with no filler: the first front-loads the action and partial-update rule, the second explains the confirmation flow. The reference to MCP_CONFIRM_MODE keeps it compact.

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

Completeness4/5

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

The description covers update semantics, partial preservation, and the full confirmation/fallback path, so an agent can invoke the tool correctly even without an output schema. It does not describe the success response or error cases, but given the schema's rich parameter docs and annotations, this is a minor gap.

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?

With only 50% schema coverage, the description partially compensates by stating that parameters are optional and that omitted values are preserved, which is critical for all 14 parameters. It also reinforces the schema's confirmToken handling for the two-step fallback, though it doesn't add meaning for the 7 undocumented fields.

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?

The description states a specific action ('Update') and a precise resource ('top-level wedding settings'), immediately distinguishing it from page-, event-, vendor-, and FAQ-level update siblings. It also conveys the partial-update model, so an agent knows exactly what operation this tool performs.

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?

It clearly frames when to use the tool: to modify top-level wedding settings, and instructs that only changed fields be supplied, with untouched fields preserved. It doesn't explicitly name when-not-to-use alternatives like update_website_customization or update_page, but the top-level scope makes the context clear.

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