get_usage_analytics

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

With no annotations available, the description carries the behavioral disclosure burden. It clearly communicates what the tool returns (automatic call rate, paramerer hallucination rate, per-tool breakdown, etc.) and explicitly frames it as a development/evaluation tool. It does not explicitly state 'read-only' or side-effect behavior, but the 'Get...Returns metrics...' framing strongly implies a non-mutating analytic operation.

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 well-organized with clear section headers, automatic triggers, return metrics, and parameter explanations. It is thorough without wasted words; each bullet adds useful information for an agent deciding whether and how to invoke the tool.

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 simple analytics tool with no output schema and no annotations, the description covers purpose, usage context, parameter meaning, metric output, and exclusions. An agent receives all important information needed to decide whether to call it and how to set the two optional parameters.

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 0%, so the description must compensation for the schema. It provides meaningful semantics for both parameters: 'days: Look back N days (default: 7)' and 'tool_name: Filter by specific tool (optional)'. This adds real value beyond the raw type/default information in the input 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 opens with 'Get tool usage analytics and optimization metrics', stating a specific verb and resource. It clearly distinguishes itself as a development/evaluation tool, which sets it apart from the many session, memory, and knowledge tools in the sibling list.

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 contains an explicit 'AUTOMATIC TRIGGERS' section with concrete call scenarios, such as measuring optimization effectiveness and tracking automatic vs explicit call rates. It further states that this is a development/evaluation tool and 'not needed for normal usage', which provides clear when-to-use and when-not-to-use guidance.

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