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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds real behavioral context beyond them: a 30-day default window and a hard 90-day maximum range, plus the default of listing thumbs_down answers. It does not mention pagination or result-size limits for the rated-answer list.

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?

One dense sentence that front-loads the core purpose and the time-window constraint before enumerating outputs. The metric list is long but each item earns its place since no output schema exists; slightly heavy as a single sentence.

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?

With no output schema, the description correctly carries the burden of describing what comes back, and it does so exhaustively (messages, conversations, thumbs, active users, leads, weekly trend, channels, locations, rated answers). The main gap is absence of any guidance on distinguishing this from get_usage or on result volume for the rated-answer list.

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 coverage is 100%, so every parameter is already documented in the schema. The description adds only the period defaults and the 90-day cap, which frame startDate/endDate semantics, but it adds nothing about feedback filtering or chatbotId resolution beyond what the schema states. Baseline 3 is appropriate.

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?

Specific verb+resource ('Get a chatbot's usage and feedback over a period') followed by an enumeration of the exact metrics returned. It clearly distinguishes itself from review_conversations by noting the conversationId is provided for that tool, but it never contrasts itself with the closely-named sibling get_usage, which an agent would likely confuse it with.

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?

Implies usage through the default window (last 30 days) and the 90-day cap, and points to review_conversations as the follow-up for inspecting rated answers. However, it gives no explicit when-to-use guidance versus get_usage or search_knowledge_base, so tool selection against siblings is left to inference.

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