Skip to main content
Glama

parasite_risk

Detect parasite SEO risks by scanning URL paths for sponsored, affiliate, partner, editorial, and commerce patterns under Google's site-reputation policy, without HTTP fetches.

Instructions

Scan URL paths for parasite SEO patterns matching Google's 2024-11-19 site-reputation policy.

Pure URL analysis, no HTTP fetches. Detects sponsored/affiliate/partner path segments, commercial product sections (/best-deals/, /top-picks/), known editorial domain patterns (Forbes Advisor /advisor/, CNN Underscored /underscored/, /select/, /commerce/), and affiliate query parameters (?ref=, ?aff=, ?partner=).

site_risk is the maximum risk level across all URLs. Verdicts: clean | at_risk | high_risk. No Google API calls. No authentication required. Adapted from claude-seo parasite_risk.py (agricidaniel, MIT).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYes
urlsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and largely succeeds: it discloses that no HTTP fetches occur, no Google API calls are made, and no auth is required, and it enumerates the verdict values (clean | at_risk | high_risk). It omits any limit on how many URLs may be passed and does not explain what the risk levels mean beyond their names.

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-loads the core purpose, then efficiently layers scope, detected patterns, and output verdicts in short standalone lines. The attribution line adds little for an agent, but overall it is tight and scannable.

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?

An output schema exists, yet the description helpfully explains the verdict vocabulary and that site_risk is the max across URLs. Combined with the no-fetch/no-auth disclosures, an agent has enough to invoke it correctly; the missing pieces are the "site" parameter meaning and any input-size limits.

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% for both parameters, so the description must compensate. It implies the nature of the "urls" input ("Scan URL paths") but never defines the "site" parameter's role or the expected URL format, leaving the required parameter undocumented.

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?

States a specific verb ("Scan") plus resource ("URL paths") plus the exact target ("parasite SEO patterns matching Google's 2024-11-19 site-reputation policy"). It also enumerates the concrete signals it detects, so an agent can distinguish it from every sibling SEO tool, none of which performs parasite/site-reputation analysis.

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

Usage Guidelines4/5

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

The description gives clear operational context ("Pure URL analysis, no HTTP fetches", "No Google API calls", "No authentication required") that tells an agent when this cheap offline check is appropriate. However, it never names an alternative sibling or states explicit when-not conditions, so it stops short of full routing guidance.

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