Skip to main content
Glama

seo_cannibalization

Detect queries where multiple pages compete for the same ranking slot, measuring click concentration to identify SEO cannibalization.

Instructions

Detect queries where multiple pages compete for the same ranking slot.

Uses the Herfindahl-Hirschman Index (HHI) to measure click concentration across pages. conflict_score = 1 - HHI: values near 1 mean clicks are split evenly across pages (high competition). Filters to queries with at least min_impressions total impressions to exclude noise.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
siteYes
engineNogoogle
min_impressionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • addedInput schema / properties / engine
      Added value: +{
      +  "default": "google",
      +  "title": "Engine",
      +  "type": "string"
      +}
  2. First observedv0.4.1

TDQS

B3.4/5.0
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 and does a decent job: it discloses the HHI methodology, the exact conflict_score = 1 - HHI formula and its interpretation, and the min_impressions noise filter. It does not state whether the operation is read-only or what happens to queries below the threshold query count, but the scoring behavior is unusually well explained.

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?

Front-loaded purpose followed by three short lines covering methodology, score interpretation, and the filtering rule. Each sentence carries information, though the HHI formula line is closer to internal documentation than agent-facing guidance.

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?

An output schema exists, so return values need not be explained, and the scoring semantics are covered. However, three of four input parameters are undocumented with zero schema descriptions and there is no annotation coverage, leaving meaningful gaps for an agent deciding how to invoke it.

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

Parameters2/5

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

Schema description coverage is 0% across 4 parameters, so the description must compensate and largely does not. Only min_impressions gets meaning ('Filters to queries with at least min_impressions total impressions to exclude noise'); days, site, and engine are left completely undefined.

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 opens with a specific verb+resource statement — 'Detect queries where multiple pages compete for the same ranking slot' — which is precise about what is computed. It is clearly distinct from siblings like quick_wins or seo_striking_distance, though it never names or contrasts with any of them.

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?

Usage is only implied: the agent infers you run this when investigating keyword cannibalization. There is no explicit when-to-use statement, no prerequisites, and no routing against adjacent diagnostic tools such as page_health_score or content_quality.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.