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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description confirms this with 'Fetches the page, extracts title/description/key links, and emits...' and adds context about the process. No contradictions. Could mention rate limits or error handling but not essential.

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 concise sentences plus a bullet list of use cases. Front-loaded with the primary action. No redundant or unclear phrases.

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?

Given simple parameters, full annotations, and no output schema (but description states 'single text blob'), the description fully covers what the tool does, how it works, and when to use it. No gaps.

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 coverage is 100% with both parameters described. Description adds value by stating 'default 25, max 50' for max_links, which is not in the schema. This helps the agent set appropriate values.

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?

Description clearly states the verb 'Generate' and the specific resource 'production-ready llms.txt file for any URL'. It distinguishes from siblings like 'scan_competitor_ai_presence' by being uniquely focused on llms.txt generation.

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?

Description lists clear use cases: getting a client's site indexed, drafting own project's llms.txt, auditing competitor indexing. While it doesn't explicitly state when not to use, the use cases imply applicability. No sibling tool overlaps enough to require exclusion.

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