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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety profile is covered. The description adds useful context about the read scope (current team, time window) and the variety of statistics returned, but does not disclose any additional behavioral aspects (e.g., potential latency, data freshness, or auth requirements). Given the annotations cover the main safety concerns, the description adds moderate value.

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 a single, information-dense sentence that front-loads the key action and scope, then uses a colon to introduce a list of the included statistics. While long, each item adds substantive value and there is no redundancy. It is efficiently structured without extraneous filler, but could potentially be split into two sentences for readability without losing meaning.

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?

The description comprehensively lists all the types of statistics returned, states the scoping to the current team and time window, and gives an explicit use-case ('gauge how a quiz is performing'). Given that an output schema exists (which would describe the response shape), the description covers the semantic context well. It does not mention edge cases like empty datasets, but these are unlikely to be required for an agent to invoke the tool correctly.

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% – both parameters ('formId' and 'days') are fully documented in the schema. The description merely references 'over the last N days' without adding any new meaning, and does not clarify parameter syntax or relationships beyond what the schema provides. Baseline of 3 applies per the rubric.

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 clearly states the action ('Read submission statistics for a form') with specific scope ('in the current team over the last N days') and enumerates the exact data dimensions returned (KPIs, daily trend, channels, UTM combos, login types, device breakdown, per-question distributions). It is specific enough to distinguish from related siblings like get_form_funnel or get_form without ambiguity.

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 explicitly says 'Use this to gauge how a quiz is performing and to suggest improvements,' providing clear context for when the tool is appropriate. However, it does not explicitly mention any alternative tool or state when NOT to use it, so it lacks direct comparison with siblings like get_form_funnel. It provides strong guidance but no exclusions.

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