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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful internal context: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format,' plus the output placement. There is no contradiction with annotations — fetching and generating is consistent with read-only, idempotent behavior.

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?

Three sentences with the core purpose front-loaded, followed by the internal process and then the use-case list. Every sentence earns its place, the 'Useful for' list is compact, and there is no redundant boilerplate.

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?

With no output schema, the description compensates by specifying the return value: 'Output is a single text blob ready to drop at site-root/llms.txt.' Combined with two fully-documented parameters and complete annotations, the description covers process, output, and use cases. The only gaps are edge-case behaviors like unreachable URLs or error handling, which are minor for a simple read-only fetch 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 the input schema fully documents both url and max_links, including the default (25) and max (50) for max_links. The description's 'any URL' and 'key links' phrasing aligns with the parameters but does not add syntax, constraints, or examples beyond what the schema already provides, so it stays at baseline.

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 precise verb+resource: 'Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly.' It names the downstream consumers and the exact output format ('standard llms.txt markdown format'), making the tool's function unambiguous and distinguishable from siblings like ai_visibility_check.

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 gives three concrete invocation scenarios: '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.' This is clear contextual guidance, but it never names alternatives or states when not to use the tool, leaving the potential overlap with siblings like scan_competitor_ai_presence implicit.

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