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

The description goes beyond the readOnlyHint annotation by disclosing concrete evaluation criteria and the output shape: a 0–100 score, findings with severity and line numbers, and Lighthouse status. It is strong but leaves the meaning of 'Lighthouse-Status' somewhat unexplained.

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 one dense, efficient sentence that front-loads the purpose, lists the validation scope, and states the output. Every clause earns its place and there is no filler.

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 no output schema, the description usefully explains return values and validation criteria. It is complete enough to invoke the tool, but it could have clarified the role of expectedHostname relative to external-domain checks and explained the Lighthouse status more fully.

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 parameters are already well documented. The description adds context about what is validated but does not add new meaning to the parameters themselves, which matches the baseline for full schema coverage.

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 names a clear verb and resource: 'Prüft den Inhalt einer llms.txt gegen den Formatvorschlag von llmstxt.org' and enumerates the exact checks performed. It is specific enough to distinguish this from publishing or generating a llms.txt, even though it does not name the sibling tools explicitly.

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 implies that the tool is for validating llms.txt content, but it gives no explicit guidance about when to prefer it over siblings like check_published_llms_txt or generate_llms_txt. No exclusions, prerequisites, or alternative routing are mentioned.

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