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

With no annotations, the description carries the full behavioral burden and does so well: robots.txt compliance, private-host blocking, a five-redirect cap, a 3 MB page cap, and a per-call price of $0.003 USDC (x402) with payment implied. That is exactly the operational context an agent needs before invoking a metered network fetcher.

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?

Three sentences, front-loaded with the purpose before constraints. The enumeration of returned fields is slightly list-like but each clause carries real information; nothing is 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?

With no output schema, the description compensates by naming the returned fields (title, byline, site name, excerpt, word count, body) and the operational limits. It does not describe failure modes such as robots.txt disallow, non-HTML content, or fetch errors, which is a minor remaining gap.

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%, so both parameters are already documented in the schema, including the 200-link cap. The description's mention of links=true largely restates the schema and adds no new syntax, format, or edge-case meaning, so the 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 verb and resource ('Convert any web page into clean, readable Markdown'), then adds the mechanism ('Fetches a public web page and returns clean Markdown'). It is unambiguous and clearly distinct from the gas-price siblings, which share no domain overlap.

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 a clear intended use ('give an AI agent readable text from a URL without writing your own scraper') and the key invocation trigger (links=true for outbound links). It stops short of stating when not to use it or naming alternatives, but the sibling tools are in an unrelated domain so there is little to disambiguate against.

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