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Dweeb1578

Marketing Analytics MCP Server

by Dweeb1578

gsc_zero_click_pages

Identify pages with high impressions and zero clicks to uncover CTR opportunities. Pinpoint underperforming content in Google Search Console.

Instructions

Pages with high impressions but ~0 clicks (CTR opportunities).

Args: start_date: YYYY-MM-DD (default: 31 days ago) end_date: YYYY-MM-DD (default: 3 days ago) min_impressions: Minimum impressions threshold (default: 200) country: 3-letter country code; empty for global row_limit: Max pages to inspect (default: 100)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNo
end_dateNo
row_limitNo
start_dateNo
min_impressionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not state whether the tool is read-only, destructive, or requires specific permissions. It only describes parameters and defaults, omitting traits like side effects, rate limits, or data freshness.

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 highly concise: a one-line summary followed by a clean list of arguments. No extraneous sentences or fluff. The structure front-loads the core purpose, making it easy for an agent to quickly parse.

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?

Given the tool's simplicity (5 optional parameters, no required fields) and the presence of an output schema, the description adequately explains the input. However, it could be more complete by mentioning the output type or data structure, though the output schema covers that. Overall, it is sufficient for a straightforward data retrieval tool.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It lists all 5 parameters with default values and brief explanations (e.g., 'start_date: YYYY-MM-DD (default: 31 days ago)'). This adds significant meaning beyond the schema's bare property definitions.

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 the tool returns 'Pages with high impressions but ~0 clicks (CTR opportunities),' which clearly identifies the resource and filter. While it lacks an explicit verb like 'list' or 'retrieve,' the tool name and context make the purpose evident. It distinguishes itself from sibling tools like gsc_branded_vs_unbranded or gsc_compare_periods by focusing on zero-click opportunities.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, scenarios, or exclusions, leaving the agent to infer appropriate usage from context. Sibling tools are listed but not compared.

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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