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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description usefully adds that results are video-weighted and that the tool will not silently broaden filters — a meaningful behavioral guarantee. However, it omits the hard constraint that min_videos defaults to 8 (minimum 8), which materially affects whether a call can succeed.

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?

A single dense sentence with the method and the scope caveats front-loaded, no filler. It is arguably over-compressed, but nothing written is wasted.

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 tool with nested filter objects, zero schema description coverage and a minimum-sample gate, the description leaves out the mechanics an agent needs: what a group filter accepts, whether groups must be disjoint, and the min_videos requirement. The presence of an output schema excuses explaining return values, but not the input and precondition gaps.

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% against 5 parameters, two of which are 9-field nested filter objects, yet the description explains none of them. It never says group_a/group_b are filter objects, never mentions the role scoping, the max-5 metrics list, or the minimum video count per group, so an agent must reverse-engineer semantics from enum names alone.

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?

States a specific verb (compare) and resource (two explicit groups) plus the method (video-weighted distributions) and the output emphasis (reports overlap). It implicitly distinguishes itself from compare_to_reference by insisting the groups are 'explicit', but never names that sibling or any other, so differentiation is left to inference.

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 clause 'no causal claims, quality scores or silent broadening' constrains what the tool will not do, not when to call it. There is no statement of when this should be preferred over compare_to_reference, corpus_stats, trends, or typical_structure, all of which sit in adjacent territory.

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