get_feedback_analytics

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds behavioral context: enterprise-gating and 403 response, which are beyond annotations. It does not contradict annotations.

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 sentences with no filler: first states purpose, second gives usage alternatives, third mentions enterprise-gating and error. Front-loaded and efficient.

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?

Given the tool has 29 parameters, 2 required, and an output schema exists, the description provides a high-level overview (time-series, summary, per-bucket counts) and error condition. It covers essential context without needing to detail all parameters, as the schema handles that. Slightly more could be added about optional filtering, but it's sufficient.

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 schema already documents all parameters sufficiently. The description adds no additional parameter-specific meaning beyond what the schema provides, resulting in a baseline score of 3.

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 'Get' and identifies the resource as 'feedback-submission time-series data' with outputs 'summary totals and per-bucket counts'. It also distinguishes this tool from siblings by naming specific alternatives for breakdowns, ensuring clear differentiation.

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?

Explicitly states when to use this tool ('top-level feedback trend view') and when to use alternatives ('get_feedback_models_analytics, get_feedback_scores_analytics, or get_feedback_weighted_analytics for breakdowns'). Also notes enterprise-gating and 403 error for non-Enterprise plans, providing clear usage context.

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