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

The description discloses the key behavior: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format.' It also explains the output as a 'single text blob ready to drop at site-root/llms.txt.' The annotations (readOnlyHint, idempotentHint, destructiveHint) cover safety, and the description adds process-level detail without contradicting those 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 concise and front-loaded: the first sentence states the primary purpose, the second summarizes the process and output, and the final clause lists use cases. Every sentence adds value with no redundancy or fluff.

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 the tool's simplicity (2 params, no output schema), the description is sufficiently complete: it explains the input (URL), the process, the output format, and the practical applications. The annotations cover safety and idempotency. No major gaps remain, though it could mention edge cases (e.g., invalid URLs) but that is not critical for this straightforward generator.

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%, with both 'url' and 'max_links' fully documented in the schema (including default and max values). The description adds little param-specific meaning beyond the schema, though it does explain the practical source of links ('extracts title/description/key links'). This meets the baseline for high schema coverage.

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 action ('Generate a production-ready llms.txt file'), the resource ('for any URL'), and the specific output format ('standard llms.txt markdown'). It also lists concrete use cases (getting a client's site indexed, drafting for own project, auditing a competitor) which distinguishes it from sibling tools like ai_visibility_check and scan_competitor_ai_presence.

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 ('Useful for: 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'), giving clear context for when to invoke this tool. It does not explicitly state exclusions or name alternative tools, but the guidance is specific enough for an agent to select it appropriately.

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