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

No annotations are provided, so the description carries the full burden, and it does disclose the output shape (0–100 score plus improvement suggestions) and the breadth of checks performed, which is genuinely useful. It omits operational traits such as that it performs live network fetches, any rate/timeout behavior, and whether it is purely read-only — gaps that matter for a network-invoking audit tool.

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 purpose front-loaded and the return value appended at the end. Every listed item earns its place as a scope declaration, though the enumeration is packed tightly enough to read as a list rather than prose.

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 no output schema and no annotations, the description usefully compensates by naming the return value (0–100 score and improvement suggestions) and the full scope of inspected artifacts. It is sufficiently complete for an agent to decide and call, with the only real gap being the missing sibling differentiation.

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?

Only one parameter exists and the schema description coverage is 100% ("網站網址或網域"), so the schema already documents the input. The description adds nothing about expected URL format, whether scheme is optional, or how bare domains are handled, so the baseline of 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 verb (檢查/check) and resource (a site's AI-friendliness), and enumerates the concrete artifacts inspected: llms.txt existence/format, llms-full.txt, Markdown pages, robots.txt per AI crawler, and sitemap. However, it never differentiates itself from siblings that cover overlapping ground (validate_llms_txt for llms.txt format, check_ai_crawler_access for crawler rules), so an agent cannot tell apart the composite audit from the narrower validators.

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?

No when-to-use, when-not, or alternative guidance is present despite three closely related siblings. An agent must infer from the field list that this is the broad umbrella check rather than the targeted validate_llms_txt or check_ai_crawler_access call.

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