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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the output structure and even derives agent_share, which is transparent about what is returned. However, it does not mention any side effects, authentication requirements, rate limits, or potential limitations (e.g., date range constraints). For a tool with no annotations, this leaves some behavioral gaps.

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 concise, consisting of two short paragraphs. The first paragraph delivers the core purpose and output summary upfront, while the second adds filter details. There is no redundant fluff, and every sentence earns its place. It is well-structured but could use bullet points for the output list.

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 tool with 5 optional parameters and no output schema, the description covers the key aspects an agent needs: what the tool returns (totals, counts, breakdowns) and how to filter (all parameters explained). It does not specify the exact JSON response shape, but the field listing is sufficient for most use cases. Minor omissions like pagination or result limits are not addressed, but the core calling contract is clear.

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 schema has 0% description coverage, so the description must compensate. It does so by explaining each filter parameter: site_id ('one integration'), settled ('human' or 'agent'), page_path, and since/until as ISO 8601 times. It even clarifies agent_share's calculation. This provides meaningful semantics beyond the bare schema, though it could offer more detail on default behavior.

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 ('Summarise') and resource ('who is visiting a website'), clearly indicating the tool's analytics purpose. It lists the exact output dimensions (totals, counts per visitor class, breakdowns) and states a use case, but does not explicitly distinguish itself from sibling tools like agent_detection_get_session or agent_detection_list_sessions, which prevents a perfect score.

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 a direct usage instruction: 'Use this to show how much traffic comes from agents and which pages they use.' This provides clear context for when to call it. However, it does not mention when not to use it or direct to alternative tools, so it lacks explicit exclusion guidance.

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