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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, confirming safe, idempotent, read-only behavior. The description adds valuable context: the process (fetches page, extracts title/description/links), output format (standard markdown, single text blob), and deployment location (site-root/llms.txt). No contradictions.

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 serving a distinct purpose: action definition, process summary, and use cases. No redundant words, front-loaded with key verb and resource.

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?

With 2 non-nested parameters and no output schema, the description fully covers input, process, output format, and usage context. It explains how the output should be used (dropped at site-root/llms.txt) and for whom (AI crawlers). No gaps.

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%, so baseline is 3. The description enhances both parameters: for 'url' it provides an example, for 'max_links' it states default (25) and max (50). These details add practical meaning beyond 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?

The description clearly defines the tool's action (generate), resource (llms.txt file), and target (any URL). It distinguishes from siblings by specifying 'production-ready' and the exact output format, which is unique among sibling tools like 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?

Explicitly lists three practical use cases (client index, own project, competitor audit) that help an agent decide when to invoke. Lacks explicit 'when not to use' or direct alternative tool references, but the use cases are sufficient for guidance.

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