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

With no annotations, the description carries full burden, and it usefully discloses the paid model ('$0.001 USDC on Base via x402') — significant behavior for cost-aware agents. However it omits failure behavior, the 500k input cap, and any rate/retry context, so disclosure is partial.

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?

Two sentences, both earning their place: the extraction scope is front-loaded and the payment note follows. No filler or redundancy.

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?

No output schema and no annotations, so the description should ideally state the return shape (link objects with href/anchor text, ordering, dedup) and note the 500k input limit. As written, an agent knows what it does and what it costs but not what it gets back.

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 0%, so the schema gives no prose meaning. The description compensates for base_url by explaining it resolves relative URLs, but adds nothing about the html parameter's size ceiling or accepted formats.

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+resource ('Extract links and anchor text from supplied HTML') and clarifies the input form ('supplied HTML'), which separates it from URL-fetching siblings like webpage-links or canonical-web-scrape. It does not name those siblings explicitly, so an agent must infer the distinction.

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 phrase 'from supplied HTML' implies you use this when you already hold the markup rather than a URL, but there is no explicit when-to-use, when-not, or named alternative. Usage is inferable rather than stated.

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