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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it's safe and idempotent. The description adds behavioral context: it fetches the page, extracts title/description/key links, and outputs standard markdown. This is valuable beyond annotations, though it could mention additional traits like rate limits or handling of large pages.

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 sentences: purpose, process, use cases. No redundant or unnecessary words. Every sentence earns its place, making it highly efficient and easy to scan.

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, annotations present), the description is fairly complete. It explains the output format (text blob for site-root/llms.txt) and lists use cases. It doesn't cover error scenarios or invalid URLs, but overall enough for an agent to use 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 the schema already documents both parameters well. The description reiterates that 'url' is the full URL and 'max_links' has a default of 25 max 50, but adds no new semantic information beyond the schema. Baseline 3 is appropriate.

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 starts with a clear verb 'Generate' and specifies the resource 'llms.txt file for any URL'. It further details the process (fetches, extracts, emits) and distinguishes from sibling tools like ai_visibility_check and scan_competitor_ai_presence by focusing specifically on the standard 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?

The description explicitly lists three use cases: getting a client's site indexed, drafting for own project, and auditing competitor visibility. This provides strong context for when to use. While it doesn't explicitly state when not to use, the use cases are well-defined and differentiate from other tools.

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