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zainsive

seo-analytics-mcp

by zainsive

gsc_compare_periods

Read-only

Compare two consecutive Search Console periods and see the biggest movers in clicks, impressions, CTR, or position. Answers 'what changed' in one call, with direction-aware insights for position.

Instructions

Compare two consecutive Search Console periods and return the biggest movers in both directions - the 'what changed' question in one call.

period_days is the length of each window; the current window ends offset_days before the freshest available data, and the comparison window is the period_days immediately before it. metric is clicks, impressions, ctr or position. For position, a DECREASE is an improvement, and the response says so. dimension is usually page or query; query rows are anonymised by Google and will not sum to totals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNo
metricNoclicks
site_urlNo
dimensionNopage
offset_daysNo
period_daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses concrete behavioral details: window anchoring via offset_days, the direction caveat for position, and the fact that query rows are anonymized and will not sum to totals. This materially helps the agent interpret results correctly.

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?

Three focused sentences convey purpose, window mechanics, and the key metric/dimension caveats without repetition or filler. The most important behavioral details are front-loaded.

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?

Given the annotations, existing output schema, and the description's coverage of window semantics and special cases, an agent has enough information to select and invoke the tool correctly. The remaining implicit parameters are minor and inferable.

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 0% schema coverage, the description compensates well by explaining period_days, offset_days, metric values, and dimension caveats. top_n and site_url are left implicit, but their titles and defaults make them reasonably self-explanatory.

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 verb and resource: compare two consecutive Search Console periods and return the biggest movers in both directions. The 'what changed' framing clearly distinguishes it from siblings like gsc_search_analytics, which does not compare periods.

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 explicitly frames this tool as answering the 'what changed' question, giving a clear use case. It does not name specific alternatives or exclusions, but the intended context is clear relative to the sibling tools.

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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