Get logs statistics

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

With no annotations, the description must carry behavioral disclosure; it does reveal hourly aggregation, optional filtering, and a filter syntax example. However, it does not state the output shape, default time window, or how filters behave beyond the one example, leaving important operational behavior unspecified.

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 short sentences with no filler; the core action and scope lead, followed by a practical use case and a concrete example. Every sentence earns its place.

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 one-parameter tool with no output schema and no annotations, the description gives the essential purpose and a filter example, but omits the return format and any default/time-range behavior needed to chart statistics reliably. It is minimally viable rather than complete.

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%, setting a baseline of 3; the description adds value by clarifying that filtering is optional and by giving a concrete filter example ('level = 0'). It does not fully define the filter grammar, but the example plus schema description is enough for basic usage.

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 states a specific action ('Return') and resource ('hourly aggregated log statistics'), and the aggregation qualifier distinguishes it from sibling list_logs/get_log. No ambiguity remains about what this tool produces.

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?

Gives concrete use cases ('chart request volume or error rates') and a filter example, making intended scenarios clear. It does not explicitly say when to prefer it over list_logs or get_log, so it misses the 'when-not/alternatives' bar for a 5.

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