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

Goes well beyond the annotations: discloses pricing ($0.01/call via x402 USDC or card key), that failed calls are free, and explicitly explains why readOnlyHint is false despite the tool only reading. That resolves the one confusing annotation signal an agent would otherwise trip on.

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 what you get back, then mechanism, use cases, example, and cost. Every sentence carries distinct information; nothing is repeated from the schema or annotations.

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, the description correctly specifies the return shape (short summary plus three to six key points) and adds cost and failure behavior. Nothing material 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?

Schema coverage is 100% and the single url parameter is fully documented, so the schema already carries the semantics. The description adds a concrete example URL and reinforces that a single URL is all that is required, giving a small amount of value above baseline 3.

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 concrete verb and resource ('Given a URL... short summary of the page plus three to six key points') and describes the internal pipeline (fetch, strip nav/boilerplate, LLM summarize). It is clearly distinguishable from siblings like extract, pdf_text, or url_meta.

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?

Gives concrete usage contexts: research, news triage, link previews, and deciding whether a page is worth reading in full. It does not explicitly name a sibling alternative or state when not to use it (e.g., use extract for full text), which keeps it below a 5.

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