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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds that it fetches the page, extracts title/description/key links, and emits standard llms.txt markdown format, which expands understanding beyond annotations. No contradiction with annotations.

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 plus a bullet list of use cases, all front-loaded. Every sentence adds value: first defines the tool, second explains the process and output, third lists practical uses. No unnecessary words.

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 process (fetch, extract, emit), output format (single text blob), and use cases. With two parameters, no output schema, and annotations covering safety, it provides sufficient context for an agent to use the tool correctly. Could mention URL accessibility or error handling, but not critical for this simple tool.

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 baseline is 3. The description does not add parameter-specific details beyond what the schema provides (e.g., 'max_links' controls entry count is implied). No additional parameter explanation is given, but the high schema coverage means the description doesn't need to compensate.

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 an llms.txt file for a URL, specifies the verb (generate) and resource (URL), and lists specific AI crawlers (ChatGPT, Claude, Perplexity) and use cases. It distinguishes from sibling tools by focusing on llms.txt generation, which is unique among siblings.

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 ('getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor'). It does not mention alternatives or when not to use, but the context is clear and no sibling tool overlaps directly.

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