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

Annotations already declare readOnly/idempotent safe operations; description adds the mechanism (fetches the page, extracts title/description/key links) and output format (single text blob), giving the agent a clear model of how the tool behaves without contradicting 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?

Three tightly written sentences: purpose, process, and use cases. Each earns its place and the most critical information is front-loaded.

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?

Despite no output schema, the description tells the agent what to expect (a single text blob in llms.txt format) and covers the full workflow. Combined with robust annotations and schema, the description is sufficiently complete 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 covers 100% of parameters, so the description doesn't need to explain them. It adds only marginal context like 'any URL' and 'standard markdown format,' which doesn't meaningfully enhance parameter understanding beyond the schema.

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?

First sentence clearly states the tool generates a production-ready llms.txt file for any URL, with explicit mention of AI crawlers. This distinguishes it from siblings like ai_visibility_check which focus on checking presence, not generating the file.

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 includes a 'Useful for' section listing three concrete contexts: client site indexing, drafting for own project, and auditing competitors. This provides clear situational guidance, though it does not explicitly name alternative tools for exclusion.

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