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Suganthan-Mohanadasan

Google Search Console MCP Server

image_impressions_no_clicks

Identify query-page pairs with high image-search impressions but near-zero clicks. Pinpoints underperforming thumbnails that fail to convert visibility into traffic.

Instructions

Surfaces query and page pairs that earn meaningful image-search impressions but effectively zero clicks. The textbook 'thumbnail is not converting' pattern. Defaults tuned for image search, which runs at much higher impression volumes per page than web. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of days to analyse
row_limitNoMaximum rows to return
max_clicksNoMaximum clicks (filter to pages stuck in the impressions-no-clicks pattern)
min_impressionsNoMinimum impressions threshold
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 of behavioral disclosure. It effectively communicates that the tool analyzes impression-no-click patterns, defaults tuned for image search, and includes instructions on data interpretation (no speculation). However, it does not explicitly state whether the tool is read-only or whether it modifies any data, but the context implies it is analytical (surfacing data). Minor gap: no mention of performance impact or rate limits.

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 well-structured and front-loaded with the core purpose. It includes important context and explicit usage instructions in a few sentences. Some phrasing could be slightly condensed (e.g., the note about 'thumbnail not converting' could be one line), but overall it is efficient without being wasteful.

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 complexity of a tool that identifies zero-click patterns, the description covers purpose, usage boundaries, and presentation expectations. It lacks an output schema, but that is not required per the rubric. The description is complete enough for an AI agent to understand what it does and how to act on results, though a note about output structure (e.g., columns returned) would improve completeness.

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%, meaning all four parameters are described in the input schema. The description does not add additional meaning beyond the schema, but clarifies that defaults are tuned for image search. The schema provides sufficient context for parameters like 'days' and 'row_limit.' Baseline 3 is appropriate since the schema does the heavy lifting and the description adds no new param-specific detail.

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 this tool 'Surfaces query and page pairs that earn meaningful image-search impressions but effectively zero clicks,' using a specific verb ('surface') and resource ('query and page pairs'). It distinguishes itself from siblings like 'image_search_quick_wins' and 'ctr_opportunities' by explicitly naming the image-search context and the 'thumbnail is not converting' pattern, making its unique role evident.

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 guidelines on when to use this tool, emphasizing it is for image search and noting the higher impression volumes. It includes critical usage instructions: 'Base your analysis ONLY on the data returned,' 'Do not speculate about causes,' and guidance on presentation as a dashboard visualization. This clearly differentiates it from siblings by focusing on zero-click patterns in image search.

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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