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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds process transparency ('Fetches the page, extracts title/description/key links') and clarifies the output ('single text blob ready to drop at site-root/llms.txt'), which is meaningful context beyond the annotation defaults. It does not cover edge cases like invalid URLs, but the provided information is sufficient for a read-only generation 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 three concise sentences. The first states the main action and benefit, the second explains the process and output format, and the third lists concrete use cases. Every sentence earns its place with no redundancy or irrelevant details, making it easy to parse quickly.

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 simple tool with 2 parameters and no output schema, the description is complete. It explains the input (any URL), the process (fetch, extract, emit), the output format (standard llms.txt markdown), and the intended use cases. The annotations cover safety and idempotency, so the agent has all necessary context to invoke the tool correctly.

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 description coverage is 100%, so both parameters (url and max_links) are already well-documented with examples and defaults. The description does not add parameter-specific semantics beyond what the schema provides; it mentions 'any URL' but that is implicit in the schema. Baseline 3 is appropriate when the schema carries the parameter documentation burden.

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 opens with a specific action ('Generate a production-ready llms.txt file') and clearly identifies the resource (any URL) and output format (standard llms.txt markdown). It distinguishes itself from sibling tools like scan_competitor_ai_presence by focusing on file generation rather than scanning, and the use cases (client sites, own projects, competitor auditing) clarify the scope.

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 in the 'Useful for' list, which helps an agent decide when to invoke the tool. However, it does not explicitly mention alternatives or when NOT to use it, leaving some ambiguity around the competitor-auditing use case that overlaps with sibling tools like scan_competitor_ai_presence.

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