mcp-seo-audit

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool 'shows true organic SEO growth,' implying a read-only analytical function, but doesn't specify data sources (e.g., Google Search Console), permissions required, rate limits, or output format. For a tool with 3 parameters and no annotations, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and concise: two sentences explain the purpose and benefit, followed by a clear 'Args' section listing parameters. Every sentence earns its place, with no redundant or vague language, making it easy to scan and understand.

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

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

Given 3 parameters, no annotations, and an output schema (which reduces the need to describe return values), the description is moderately complete. It covers the purpose and parameters but lacks behavioral details like data sources, error handling, or usage context. This is adequate for a basic tool but has clear gaps in transparency.

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

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

The description includes an 'Args' section that documents all 3 parameters with brief explanations and an example for 'brand_name'. Since schema description coverage is 0%, this adds substantial value beyond the bare schema. However, it doesn't detail formats (e.g., URL structure for 'site_url') or constraints (e.g., range for 'days'), keeping it from a perfect score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Split search performance into branded vs non-branded queries' and explains the benefit: 'Shows true organic SEO growth by separating brand searches.' It specifies the verb ('split'), resource ('search performance'), and scope ('branded vs non-branded'), but doesn't explicitly differentiate from sibling tools like 'get_search_analytics' or 'compare_search_periods' that might also handle search data.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_search_analytics' or 'compare_search_periods' that might overlap in functionality, nor does it specify prerequisites or exclusions. The context is implied (SEO analysis) but not explicitly stated.

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