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

With strong annotations (read-only, idempotent, non-destructive), the description adds valuable process details: it fetches the page, extracts title/description/key links, and emits standard markdown. It does not mention limits like rate limits or error handling, but the annotations cover safety.

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, front-loaded with the core purpose, followed by process and use cases. Every sentence adds value with no redundant content.

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?

The description explains the output format (single text blob, llms.txt markdown) despite lacking an output schema. It covers intended usage and behavior adequately for a relatively simple tool, but could mention internet access requirements or failure handling.

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?

Both parameters are fully documented in the schema (URL and max_links). The description adds context about 'any URL' and production-ready output, but does not provide new semantic details beyond the schema, so baseline 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 clearly states the tool generates a production-ready llms.txt file for any URL, specifying the action, resource, and outcome. It distinguishes itself from sibling tools by focusing on file generation rather than visibility checking or research.

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 provides explicit use cases (indexing a client's site, drafting for own project, auditing competitors) that signal when to use it. However, it does not mention alternatives or when not to use it, leaving a small gap.

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