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

Goes well beyond the readOnly/idempotent/openWorld annotations: discloses pricing ($0.001/call, 10 free/day, x402 payment-required result), error behavior (isError, not charged), matching semantics (longest match, Allow beats Disallow, wildcards), and the missing-robots.txt default.

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?

Front-loaded with the core question, then capabilities, then semantics, then pricing, then errors. Every sentence carries operational value with no filler.

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?

An output schema exists, so return values need no explanation, and the description covers pricing, error behavior, and matching rules. Nothing an agent needs to invoke this correctly 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?

Schema description coverage is 100%, so both parameters are already documented (url as absolute URL, user_agent with default). The description adds the rule-evaluation semantics ("for any user-agent") but no format or syntax detail 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 specific verb+resource: checks a URL against robots.txt, lists sitemaps/crawl-delay, and reports AI-crawler blocking. This is clearly distinguishable from siblings like http_probe, web_meta, or dns_lookup.

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?

"May I crawl this?" frames the usage context precisely and the described capabilities imply when it's the right tool. It does not, however, explicitly name alternatives or state when not to use it (e.g., versus a generic http_probe).

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