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

Annotations already declare readOnlyHint and idempotentHint, and the description adds valuable behavioral context: it fetches the page, extracts title/description/key links, and emits a single text blob ready for site-root placement. This goes beyond the annotations without contradicting them.

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 appropriately sized: one core sentence, one process sentence, one output sentence, and a short use-case list. It is front-loaded with the main purpose and every sentence earns its place without redundancy.

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?

For a simple read-only utility with clear schema and annotations, the description fully covers what the tool does, how it works, the output format, and when to use it. The standard llms.txt format is known, so no further output explanation is needed.

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?

The input schema already describes both parameters thoroughly (URL and max_links with default/max). The description does not add significant semantic detail beyond the schema, simply referencing 'any URL' and 'key links' without further parameter context. With 100% schema coverage, 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 clearly states a specific verb ('Generate') and resource ('llms.txt file for any URL'), and explains the process (fetches page, extracts metadata, emits markdown). It distinguishes itself from siblings like 'scan_competitor_ai_presence' by focusing on llms.txt generation rather than general AI visibility scanning.

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?

Provides explicit use cases ('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'), which clearly indicate when to use. However, it does not mention when not to use or explicitly compare to alternative sibling tools, so it falls short of a 5.

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