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

Annotations already establish readOnly, openWorld, idempotent, non-destructive, so the safety bar is low. The description still adds real behavioral context: results are 'read live' (not cached/stale), there is no auth or cost barrier ('Free, no sign-in'), and the response includes concrete remediation lines—details an agent could not infer from the annotations alone.

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?

A single dense sentence with the core subject front-loaded ('Whether each AI's crawlers ... are allowed'), followed by coverage scope and then the remediation detail. It is long but every clause—vendors, bot classes, live read, output lines, free/no sign-in—carries information; only mild cost is that it reads as one run-on.

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?

With an output schema present, the description need not explain return values, yet it usefully previews that results include remediation lines. Combined with the live-read and no-auth notes, an agent has enough to call this correctly; the only missing piece is explicit positioning against the sibling domain-analysis tools.

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?

Schema description coverage is 100% and the single domain parameter is documented in-schema with an example format. The description only implies the input is a site/domain; it adds no syntax, normalization, or edge-case handling beyond the schema, so baseline 3 applies.

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?

States a specific resource (robots.txt AI-crawler permissions) and enumerates the vendors and bot classes covered (OpenAI, Anthropic, Perplexity, Google, Microsoft; search/user/training), so an agent knows exactly what question this answers. It stops short of naming which sibling (e.g. check_domain) it is not, so sibling differentiation is only implicit.

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?

Usage is implied by the enumeration of crawler vendors and the 'exact lines to add when a search crawler is blocked' framing, which hints at a remediation use case. However, there is no explicit when-to-use/when-not guidance and no named alternative among check_domain, domain_rating, or rivals for an agent to route against.

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