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

Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds the genuinely differentiating traits: it asks questions instead of assigning severity or a quality score, and returns unknown when the comparison is sparse. That tells an agent how to interpret and present results in a way the annotations cannot. It omits what happens when the corpus is broadened via allow_broaden or below min_videos, keeping it short of a 5.

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 short front-loaded sentences with no filler, and the core comparison is stated first. However, for a tool with a nested required plan object and three additional parameters, this brevity crosses into under-specification rather than tight editing. The final sentence is clipped to the point of being cryptic.

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?

An output schema exists, so return values needn't be described, but the description leaves major gaps for a complex input: the meaning of allow_broaden, the role of min_videos, how filters weight the corpus, and what constitutes a usable plan are all unstated. Given zero schema description coverage and nested objects, more guidance is required for an agent to invoke this 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 0% across four parameters, including a deeply nested plan object with scenes and a nine-field filters object, so the description must compensate and largely doesn't. 'Video-weighted corpus distributions' and 'sparse comparisons remain unknown' hint obliquely that filters narrow the corpus and that low sample counts trigger unknown results, which indirectly gestures at min_videos. Nothing explains allow_broaden, bpm, aspect, or how filters like tone and industry weight the comparison.

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 first sentence names a concrete operation, comparing storyboard durations and pacing against video-weighted corpus distributions, which is more specific than a restated title. It does not distinguish itself from nearby siblings such as plan_structure, typical_structure, or compare_to_reference, so an agent can't route between them from the text alone. The verb 'contextualize' is also jargon-heavy, but the resource and comparison target are clear.

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?

'Asks questions, never assigns severity or a quality score' describes output behavior rather than when to call the tool. There is no statement of prerequisites, when to prefer plan_structure or compare_to_reference, or what input conditions make the tool appropriate. Usage is only inferable from the verb 'critique' in the name.

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