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Suganthan-Mohanadasan

Google Search Console MCP Server

ctr_opportunities

Find pages with high impressions but low CTR to prioritize title and meta description optimization, boosting organic clicks.

Instructions

Find pages with high impressions but CTR significantly below expected for their position. These are title/meta description optimisation candidates. 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
min_impressionsNoMinimum impressions threshold
Behavior4/5

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

With no annotations, the description carries the full burden. It provides important behavioral constraints: base analysis only on returned data, report exact numbers, avoid speculation, and present results as an interactive dashboard. These add context beyond the basic 'find pages' function, though it does not explicitly state read-only nature or side effects, the 'Find' verb and context suggest it is safe.

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 front-loaded with the core purpose and then clearly separated into IMPORTANT and PRESENTATION sections. It is longer than a minimal one-liner, but each section adds value, especially the behavioral and presentation guidance. The structure makes it scannable, though the presentation instructions could be considered general guidance rather than tool-specific.

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

Completeness3/5

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

With no output schema, the description should clarify what data is returned. It states it finds pages but does not specify the fields or structure of results (e.g., exact metrics, sorting). It also does not differentiate from the sibling ctr_vs_benchmark, which likely offers similar insights. However, the behavioral guidance about reporting exact numbers gives some hint, and the simple two-parameter configuration keeps the gap moderate.

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?

The schema already documents both parameters (days, min_impressions) with descriptions, so the baseline is 3. The description does not add any extra meaning about how these parameters affect thresholds or results beyond what the schema provides.

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's function: finding pages with high impressions but CTR below expected for their position, identifying them as title/meta description optimization candidates. This is a specific verb+resource+condition and is distinct from siblings like traffic_drops or content_gaps.

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

Usage Guidelines3/5

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

The description implies the tool is for identifying optimization candidates, but does not explicitly state when to use it over alternatives like ctr_vs_benchmark or content_recommendations. No explicit exclusions or comparisons with sibling tools are provided, only the implied use case.

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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