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

The description adds important behavioral context beyond the annotations: it reveals that the coverage list is curated and incomplete, and warns that negative detection results may be false negatives due to coverage gaps. This is especially useful given the openWorldHint annotation, since it explains the practical implication of that open-world behavior.

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 two sentences long, front-loads the core purpose, and then adds the essential usage caveat. Every sentence contributes meaning, with 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?

For a parameterless informational tool with rich annotations, the description is complete: it explains what the tool returns, how it is organized, its limitations, and when to consult it. There is no output schema, but the description provides sufficient context for an agent to decide to invoke it.

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 tool has zero parameters and the schema is empty with 100% coverage, so there is no parameter semantics to explain. The description correctly focuses on the tool's output and usage context instead.

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 the tool's purpose: it lists which technologies the website stack detector can recognize, organized by category, and explicitly notes what it cannot see. The phrase 'website stack detector' and the focus on coverage distinguish it from sibling tools like tech_detect, even without naming them directly.

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 gives explicit guidance on when to use the tool: 'Use this before trusting a negative result.' It explains the rationale by noting the detector covers a curated set, so missing technologies may be outside coverage. It does not explicitly state when not to use it or name alternative tools, but the primary use case is clear.

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