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

Beyond the readOnly and openWorld annotations, the description explains that navigation, ads, footers, and scripts are removed, and that the result includes title, description, language, word count, and token estimate. It also discloses that a site's own markdown may be used, that failed or non-text fetches are not charged, and that access is paid via x402 with a pointer to list_prices. This is unusually rich behavioral context for a simple read 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?

The description is front-loaded with the core operation and output, then adds only high-value details: markdown use, extraction behavior, use cases, billing edge cases, and pricing pointer. Each sentence adds actionable information, and there is no 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?

For a one-parameter read-only tool with no output schema, the description covers the operation, output fields, extraction behavior, use cases, and payment/failure conditions. An agent has enough context to decide whether to call it and what to expect without needing additional documentation.

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 schema already documents the sole url parameter at 100% coverage, including the absolute HTTP/HTTPS requirement and max length. The description adds little parameter-level meaning beyond reinforcing that one URL is fetched. With full schema coverage and one simple parameter, a baseline score of 3 is appropriate.

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 states a specific verb and resource: fetch one URL and convert the page's main content into clean markdown for AI agents. It clearly describes the output shape and removes ambiguity about whether this returns metadata, raw HTML, or extracted content. It does not explicitly differentiate itself from nearby siblings such as link_preview or read_feed, which keeps it just below the top score.

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?

It gives concrete use cases—RAG, summarizing articles, research, and feeding pages to an LLM—so the agent knows when this tool is appropriate. It also clarifies billing edge cases when the page cannot be fetched or is not text. It stops short of explicitly naming alternatives or when-not-to-use cases versus sibling tools.

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