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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the returned fields, the 'where known' qualifier on cost per clip (incomplete coverage), and a verification date that signals data freshness — genuinely useful behavioral context. It does not describe failure behavior for unrecognized tool names.

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?

It is a single sentence, front-loaded with the core purpose ('Today's plans and prices for one AI tool') before the field inventory. The long field list borders on a dump but every item is meaningful return content, so nothing 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?

With one required parameter and no output schema, the description carries the burden of describing return values, and it does so thoroughly. The remaining gap is edge-case behavior — unknown tool names, aliases, or partial price availability — which is minor for a read-only lookup of this complexity.

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% and the single 'tool' parameter is already documented with examples. The description reinforces valid inputs by listing several product names (Runway, Kling, Midjourney, ElevenLabs, Suno, HeyGen), but this barely exceeds what the schema already supplies and adds no matching or aliasing rules. 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?

The description uses a specific verb-and-resource framing: it returns today's plans and prices for a single named AI tool, and it enumerates the concrete data points returned (monthly price, yearly price per month, credits, cost per clip, hidden costs, verification date). Saying 'one AI tool' implicitly separates it from multi-tool siblings like compare_tools, but no sibling is named explicitly.

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?

Usage is only implied: the 'one AI tool' scoping suggests this is the single-tool lookup rather than a comparison or ranking call, which nudges an agent toward it for a known tool. There is no explicit when-to-use statement, no guidance on when to prefer compare_tools or find_cheapest, and no note about what happens if the tool name is unknown or misspelled.

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