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

Annotations already establish read-only, idempotent, closed-world behavior, but the description adds substantive context: deterministic computation from sourced dated inputs, named scenarios, arithmetic shown, custom scenarios, and null totals for quote-only inputs rather than fabricated numbers. It could go further on response structure, but the key behavioral caveats are disclosed.

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 front-loaded with the core purpose and then adds scenario, null-handling, and custom-scenario details. It is appropriately sized for the complexity, though minor marketing language like 'REAL' and the closing restatement keep it from being maximally tight.

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?

Given no output schema and three simple parameters, the description provides enough for an agent to invoke it correctly: where the topic slug comes from, what the cost model includes, what scenarios mean, how custom scenarios work, and how quote-only inputs are handled.

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%, so the schema already documents topic, agents, and resolutions. The description adds only a light layer by tying agents/resolutions to a custom scenario and repeating that topic is a slug from list_cost_decoders; with full schema coverage, 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 states a specific verb/resource: retrieving all-in monthly cost per vendor for a decoder topic. It distinguishes the output as scenario-based arithmetic from sourced inputs and explicitly names list_cost_decoders as the source of the slug, so an agent can tell what it returns versus a generic pricing lookup.

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?

It gives clear usage context: use a decoder slug from list_cost_decoders, optionally provide agents and resolutions for a custom scenario, and it answers 'what does <AI tool> actually cost'. It does not explicitly exclude alternatives such as get_normalized_pricing or compare, so it stops short of full when/when-not guidance.

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