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

The description adds useful behavioral details beyond the annotations: it limits to public URLs, enforces 5 scans/minute, caches results for 24h, and returns a 0-100 score plus corrections. The readOnly and idempotent annotations already cover the safety profile.

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 purpose is front-loaded, followed by a compact list of checkscares, then output format, then constraints. It is slightly dense as one long sentence, but every sentence adds relevant information.

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?

For a single-parameter analysis tool with an output schema, the description covers purpose, checked dimensions, output format, rate limits, and caching reuse. Nothing essential for correct invocation is missing.

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?

There is a single url parameter and the schema already documents its type, bounds, and example. The description only reinforces that the URL must be public, which adds minor nuance but does not substantially extend 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 states a specific action and resource: analyzing whether a web page can be read and cited by AI enginescars, and enumerates concrete checks (robots.txt, bots, structured data, extractability). This is clearly distinct from the sibling tools.

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?

It gives clear usage context: analyzing AI-readability/GEO of a public URL. It also adds constraints (public URLs only, rate limit, 24h cache), though it does not explicitly name alternatives or when-not-to-use conditions.

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