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Save ai search queries

save_ai_search_queries
Destructive

Save up to ten searches for the weekly report to track (three without a watch package). Saves use the expected version. Without a current watch package, an account tracks up to three searches. Uses the shared 240 writes per site and UTC day.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>",
      "version": "<version>",
      "queries": "<queries>"
    },
    "name": "save_ai_search_queries"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesSite owned by this account.
queriesYesOne to ten distinct searches, 1 to 128 characters each.
versionYes0 initially; then the current settings version.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, so safety is covered. The description adds genuinely useful behavioral context beyond them: the shared 240 writes per site per UTC day, the watch-package-dependent limit, and that saves use the expected version (optimistic concurrency). It could have stated what existing saved queries are replaced, but the added quota/versioning detail is substantive.

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

Conciseness3/5

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

The core save constraint is front-loaded, but the three-search limit is stated twice ("three without a watch package" and "Without a current watch package, an account tracks up to three searches"), which is redundant. Otherwise the size is appropriate for the 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?

For a mutation tool with destructive annotations, no output schema needed, and fully-covered parameters, the description supplies the missing operational envelope: quota limits, watch-package dependency, and version-based concurrency. Nothing essential to calling it correctly is absent.

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

Parameters3/5

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

Schema description coverage is 100%, so id, queries, and version are already fully documented (queries length/count, version '0 initially; then the current settings version'). The description corroborates the queries limit and the versioning behavior but adds no new syntax or format beyond the schema, so baseline 3 applies.

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

Purpose4/5

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

The description states a clear verb+resource ("Save up to ten searches") and the reason ("for the weekly report to track"), so an agent understands the mutation immediately. It does not explicitly contrast itself with siblings like weekly_site_report or ai_search_history, so it falls short of full sibling differentiation.

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

Usage Guidelines3/5

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

Quota context (10 vs 3 searches depending on watch package) implies when the tool is useful, but there is no explicit when-to-use vs alternatives routing. No sibling is named and no prerequisites or exclusions are given, leaving usage to inference.

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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