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search_console_analytics_query

Query the Search Console Search Analytics API for organic Google Search performance data. Returns raw rows with clicks, impressions, CTR, and position, by dimension like query, page, device, or date.

Instructions

Query the Search Console Search Analytics API for organic Google Search performance data. Returns the raw 'rows' array from the searchAnalytics.query response: [{keys: [], clicks (int), impressions (int), ctr (float 0.0-1.0), position (float, 1-indexed average ranking)}]. Empty array when no data. Read-only. Use dimensions=['query'] for keywords, ['page'] for URLs, ['device'] for device split, ['date'] for a daily trend. For convenience shortcuts use search_console_analytics_top_queries / top_pages / device_breakdown; for before/after comparisons use search_console_analytics_compare_periods.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateYesInclusive end date in 'YYYY-MM-DD' format (e.g. '2026-03-31'). Must be >= start_date. Search Console data lags 2-3 days; requesting the last two days typically returns no rows.
site_urlNoProperty identifier as registered in Search Console. For URL-prefix properties use the full URL including trailing slash (e.g. 'https://example.com/'). For Domain properties use the 'sc-domain:' prefix (e.g. 'sc-domain:example.com'). The property must be verified and accessible to the authenticated Google account.
row_limitNoMaximum rows to return. Default 100. Search Console API caps at 25000 per request; agents that need more should split the call by date range.
dimensionsNoDimensions to group rows by. Allowed: query, page, country, device, date, searchAppearance. Omit for an ungrouped total (clicks/impressions/ctr/position across the window). Each additional dimension multiplies row cardinality — agents should usually pick 1-2.
start_dateYesInclusive start date in 'YYYY-MM-DD' format (e.g. '2026-03-01'). Search Console data typically lags 2-3 days, so 'today' returns no rows. Maximum lookback is 16 months.
dimension_filter_groupsNoOptional Search Console dimensionFilterGroups payload (list of {groupType: 'and', filters: [{dimension, operator ('equals'|'contains'|'notContains'|'notEquals'|'includingRegex'|'excludingRegex'), expression}]}). Passed through verbatim to the REST API.
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explicitly says 'Read-only' and describes the response structure ('raw rows array', 'Empty array when no data'), which are key behavioral traits. It does not mention authentication requirements or potential API errors, but the schema covers property verification. The disclosure is solid but not exhaustive, so a 4 is appropriate.

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 three sentences, front-loaded with the core purpose and response format, followed by read-only status and usage/alternative guidance. Every sentence earns its place without redundancy or fluff.

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 tool is moderately complex with 6 parameters and no output schema, so the description's explanation of the return format is valuable. It covers main use cases and directs to sibling tools. It could mention row_limit or pagination behavior, but the schema already covers row_limit. Overall, complete enough for effective selection and invocation; a 4 fits.

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. The description adds value by giving concrete dimension-use examples ('Use dimensions=['query'] for keywords, ['page'] for URLs' etc.) and by clarifying the output shape's 'keys' field maps to requested dimensions. This goes beyond the schema's field descriptions, warranting a 4.

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 the Search Console Search Analytics API for organic Google Search performance data, with a specific verb ('Query'), resource, and scope. It also differentiates itself from sibling convenience tools by explicitly naming search_console_analytics_top_queries, top_pages, device_breakdown, and compare_periods as alternatives.

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?

The description provides explicit usage guidance: it recommends which dimension to use for keywords, pages, devices, and daily trends, and explicitly points to sibling tools for convenience shortcuts and period comparisons. This clearly tells the agent when to use this raw query tool versus 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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