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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds the fetch-extract-emit workflow and output format (markdown blob), providing valuable behavioral context beyond the annotations without contradiction.

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, each adding unique value: what it does ('generate'), how it works ('fetches, extracts, emits'), and when to use it (three use cases). No redundant or filler content.

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?

The description explains the entire workflow and output format. With no output schema, the description adequately covers what the agent gets ('single text blob'). Missing details like rate limits or auth are covered by annotations.

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 coverage is 100% with descriptions for both parameters. The description adds defaults ('default 25, max 50') and examples for 'url', enhancing the schema's meaning. Baseline 3 is exceeded due to this added clarity.

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 uses a specific verb ('generate') and clearly identifies the resource ('llms.txt file'). It distinguishes the tool from siblings like 'ai_visibility_check' by focusing on the specific output format and use cases for AI crawlers.

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 lists three explicit use cases (client's site, own project, competitor audit) but does not state when not to use or alternatives. The sibling list provides context, but direct exclusions would improve clarity.

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