read_url

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

The description reveals that the tool strips navigation and boilerplate, returning cleaner content than raw HTTP, and that it uses a service called Lyrenth. Without annotations, it covers core behavior but omits details about error handling, caching (fresh parameter exists in schema but not described), or access restrictions for non-public pages.

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?

The description is two sentences long, front-loaded with the core purpose, and uses clear, active language. Every sentence adds value: the first defines the action and output, the second gives a usage recommendation. 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?

For a 3-parameter tool without an output schema, the description explains the return value (clean Markdown document with title, description, structure) and the preprocessing behavior. However, it does not cover potential issues like inaccessible URLs, rate limiting, or the implications of the 'fresh' parameter, leaving some contextual gaps for an agent.

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?

The input schema has 100% description coverage for all three parameters (url, fresh, max_tokens), so the schema already documents them. The description does not add any parameter-specific context beyond what the schema provides, making the description adequate but not supplementary.

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?

The description clearly states the tool reads a public web page and returns a clean AIDocument with Markdown, title, description, and structure. It distinguishes itself from a raw HTTP fetch, but does not differentiate from sibling tools 'check_usage' and 'read_urls', leaving ambiguity.

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 description advises preferring this tool over a raw HTTP fetch for web content, providing explicit guidance for that alternative. However, it does not mention when not to use it or how it compares to the sibling tools, which are likely alternatives.

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