acedatacloud_get_pricing

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

With no annotations, the description carries the full burden and does disclose meaningful traits: authentication is not required ('No token required') and the response shape varies by dataset type (contact-only datasets return pricing_mode and reference_quote instead of checkout prices). It omits rate limits or whether the call is purely read-only, but the behavioral disclosure is solid.

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 sentences, front-loaded with what is returned, then the exception case, then the auth note. No filler, though the second sentence is slightly dense with unglossed field names.

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 need not be enumerated, yet the description still flags the conditional fields an agent should expect. Combined with the auth statement, it is adequate for a single-parameter lookup tool.

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 'service' parameter is fully documented in the schema (UUID or alias). The description adds no syntax or format detail beyond that, so baseline 3 applies.

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+resource ('Get billing unit, free amount and display cost rules'), so an agent knows exactly what it retrieves. It does not name or contrast with siblings like acedatacloud_get_service or acedatacloud_get_public_usage_packages, 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?

Adds useful conditional context — public contact-only datasets behave differently and return pricing_mode/reference_quote rather than checkout prices. However, it never says when to pick this over adjacent pricing-related siblings, so usage is implied rather than directed.

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