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google-webtools-mcp

find_new_queries

Read-onlyIdempotent

Compare the current Search Console period with the previous one to identify new or rapidly rising search queries, helping you see what people recently started searching for.

Instructions

Find queries that are new or rising fast by diffing this Search Console period against the previous one. Use when the user asks what people started searching recently. Call analyze_query_landscape for the overall mix of intent, and call find_what_to_build_next when they want those queries grouped into topics to write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoPredefined date range periodlast28d
siteUrlYesThe site URL exactly as it appears in Google Search Console (e.g., "https://example.com/" or "sc-domain:example.com")
searchTypeNoSearch type to analyzeweb
minImpressionsNoMinimum impressions in the current period to be included

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.2

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered. The description adds genuinely useful behavioral context by disclosing that results come from a period-over-period diff, which explains why the period parameter matters and why output is comparative. It does not mention rate limits, pagination, or result size.

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?

Two sentences, zero filler, with the purpose and comparison mechanism front-loaded before the routing guidance. Every clause earns its place.

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?

Covers purpose, trigger, and sibling routing for a 4-parameter read tool whose annotations handle safety and whose schema documents all parameters. The one gap is that no output schema exists, so a brief note on what the result set contains (e.g. query strings with change metrics) would have closed the loop.

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% with enums for period and searchType and a documented siteUrl format, so the schema already does the heavy lifting. The description only indirectly touches parameters by referencing the current-vs-previous period diff; it adds no syntax or threshold guidance (e.g. what minImpressions does to results). Baseline 3 is appropriate.

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 (find queries that are new or rising) plus the mechanism (diffing this period against the previous one). This lets an agent distinguish it from get_top_queries or compare_periods without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit trigger ("Use when the user asks what people started searching recently") and routes to two named alternatives with the conditions that select them: analyze_query_landscape for overall intent mix, find_what_to_build_next for topic grouping. Nothing is left to inference.

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