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zhangluka

grain-seo-mcp

by zhangluka

seo_low_ctr_opportunities

Identify queries with low click-through rates despite strong rankings, and prioritize title tag improvements to boost organic traffic.

Instructions

Find queries with low CTR relative to their ranking position. Great for title tag optimization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteUrlYesThe site URL
daysNoNumber of days (Google only, default: 28)
minImpressionsNoMinimum impressions threshold (default: 500)
limitNoMax issues to return (default: 50)
engineNoThe search engine (default: google)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states the function—finding low CTR queries—but does not disclose any side effects, authorization needs, or output characteristics. For a read-only analysis tool, the description is minimally adequate but not rich.

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 just two short sentences, front-loaded with the core action. No wasted words; each sentence earns its place.

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 and the full schema coverage, the description is nearly complete. It could briefly mention data source or output scope, but it sufficiently covers the core purpose and a primary use case.

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?

All 5 parameters have descriptions in the schema (100% coverage), so the description itself adds no additional value about parameters. Baseline 3 is appropriate; the tool description does not need to repeat schema info.

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 verb ('find'), the resource ('queries with low CTR relative to their ranking position'), and even suggests a use case ('title tag optimization'). This differentiates it from sibling tools like seo_low_hanging_fruit or seo_striking_distance.

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 only implies a use case ('Great for title tag optimization') but does not explicitly state when to use this tool vs. alternatives, nor does it provide exclusions or conditions. More explicit guidance would help the AI select it correctly.

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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