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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so safety is covered. The description adds genuinely new behavioral context: the catalog is admin-set and mutable, and an existing subscription retains the values it was bought with. That snapshot/mutability nuance is exactly the kind of detail annotations cannot carry.

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?

Lead sentence front-loads the core resource list, and the usage instruction comes last, which is the right order. The nested parenthetical describing plans and credit_packs is dense and slightly hard to parse, but every clause carries information and nothing is padding.

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?

There is no output schema, so the description must explain the return shape, and it does: the selectable categories, the credit table, and the two sale objects (plans with price/credits/limits/features/highlight, credit_packs with credits/price). Combined with the mutability caveat, an agent has enough to call it and interpret the response.

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?

The tool takes zero parameters, so there is nothing to disambiguate and the baseline is 4. The description does add value by naming units ('price in cents') and the highlighted-recommendation flag, which help interpret the result even though no inputs exist.

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 enumerates exactly what the tool returns: video types, look categories, background sources, formats, credit prices, plans and credit packs. That enumeration makes it clearly distinct from sibling listers like list_looks or show_songs. It reads more as a noun inventory than a verb phrase, but an agent can tell what the tool is for without opening the schema.

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?

"Use it to pick a category or source and to explain prices" gives explicit triggering conditions tied to real tasks (choosing an enum value, explaining cost). It does not name when not to use it or point to alternatives such as search_stock, but the usage context is unambiguous.

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