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search_analytics_query

Query Google Search Console traffic data to retrieve clicks, impressions, CTR, and position. Filter and group results by dimensions like country, device, page, and query for targeted analysis.

Instructions

Query search traffic data from Google Search Console. Returns clicks, impressions, CTR, and position data with flexible filtering and grouping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteUrlYesThe site URL
startDateYesStart date in YYYY-MM-DD format
endDateYesEnd date in YYYY-MM-DD format
dimensionsNoDimensions to group by: country, device, page, query, searchAppearance, date, hour (hour requires dataState='hourly_all')
typeNoSearch type filter: web, image, video, news, discover, googleNews (default: web)
dimensionFilterGroupsNoFilter groups to apply to the query
aggregationTypeNoHow data is aggregated (default: auto)
rowLimitNoMaximum number of rows to return (1-25000, default: 1000)
startRowNoZero-based row offset for pagination
dataStateNo'all' includes fresh (possibly incomplete) data, 'final' only finalized data, 'hourly_all' required when using 'hour' dimension
Behavior2/5

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

No annotations are provided, and the description fails to disclose important behavioral traits such as required permissions (must have site access in Search Console), data freshness considerations, potential sampling, or rate limits. The mention of 'flexible filtering' is generic and not actionable.

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?

The description is a single concise sentence covering purpose and output. It could be better structured with more detail, but it is not verbose.

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

Completeness2/5

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

With 10 parameters, no output schema, and no annotations, the description is too brief. It omits crucial context such as pagination behavior, output structure, data staleness implications, and prerequisites for using dimensions like 'hour'.

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 coverage is 100% with detailed parameter descriptions. The description adds only generic phrasing ('flexible filtering and grouping') that does not enhance understanding beyond the schema. Baseline of 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?

The description clearly states the tool queries search traffic data from Google Search Console and returns clicks, impressions, CTR, and position. It effectively distinguishes from sibling tools which deal with indexing, sitemaps, and site management.

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?

The description provides clear context for the tool's purpose in analytics, and sibling tools are distinctly different (indexing, sitemaps, sites), making it easy to choose. However, it does not explicitly mention when not to use it or provide alternatives.

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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