GEO Scanner

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

With no annotations provided, the description carries full responsibility. It discloses that the tool performs multiple checks (llms.txt, Schema.org, robots.txt, etc.) and returns a score with concrete fixes. This gives good insight into the tool's behavior (read-only scan, non-destructive). However, it does not mention potential resource usage or network requests, which keeps it from a 5.

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 consists of two concise sentences. The first sentence states what the tool does and its output; the second provides usage guidance. Every sentence adds value, no fluff, and the important information is front-loaded. This is an ideal structure for a tool description.

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 the tool's simplicity (one parameter, no output schema, no annotations), the description covers the key aspects: purpose, output format (0-100 score with checks and fixes), and usage context. It is nearly complete but could be slightly improved by mentioning that the URL must be publicly accessible.

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 input schema already covers the sole parameter 'url' with a clear description ('Full URL... including https://'), so schema coverage is 100%. The description adds context about the overall purpose but does not further elaborate on the URL parameter's semantics. Baseline 3 is appropriate as the description adds marginal value beyond the schema.

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 evaluates a website's readability and citability by AI systems, returns a 0-100 score, and lists specific checks. It uses a specific verb ('checks') and resource ('website's AI/GEO visibility'), leaving no ambiguity. Since there are no sibling tools, differentiation is not required, so the purpose is fully clear.

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 explicitly tells when to use the tool: 'whenever someone asks to check, audit, or improve a website's AI/GEO visibility.' This provides clear context. However, it does not specify when not to use the tool or offer alternatives, though no siblings exist. The lack of exclusions slightly limits what would be a perfect 5.

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

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

No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, destructive potential, rate limits, or permissions. It implies a checking operation but lacks explicit safety or behavior information.

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 concise, two sentences, front-loaded with the main purpose. Every sentence adds value with no waste.

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 the complexity of checking structured data with multiple fields, the description covers the scope well. No output schema exists, but the description implies a report of findings; it could briefly mention the return format or behavior. Overall, nearly complete.

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 schema covers 100% of the single parameter 'url' with description. The tool description adds context about what will be checked (fields), but does not add new semantics beyond the schema's parameter description. Baseline 3 is appropriate.

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 checks a website for LocalBusiness Schema.org markup, listing specific required and recommended fields. It distinguishes itself from the sibling tool 'geo_scan' by focusing on structured data audit rather than geographic scanning.

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 explicitly states when to use the tool: 'Use whenever someone asks to check, audit, or improve a local business website's structured data / Rich Results eligibility.' No explicit when-not or alternatives, but sibling tool is clearly different, so context is sufficient.

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