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

With no annotations provided, the description carries the transparency burden. It proactively discloses that status starts as 'pending', typical approval time (24 hours), and lists concrete post-approval capabilities (storefront, briefs, product listings, USDC payouts). It also notes the requirement that accept_terms must be true, which is useful behavioral context not fully captured by schema alone.

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 a clear purpose and uses bullet points for benefits, which aids scannability. While the benefits list could be seen as promotional, it is relevant for an agent deciding whether to proceed. The 'Requires' line is a bit redundant with the schema, but the overall length is reasonable for a tool with this many implications.

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?

For a registration tool with 8 parameters, no output schema, and no annotations, the description provides substantial context about the process (pending status, approval time), outcomes (storefront, payouts), and requirements. It lacks details about response format, but the absence of an output schema reduces that burden. The description is sufficiently complete for an agent to understand the tool's purpose and workflow.

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 input schema has 100% parameter coverage with detailed descriptions for each field. The description adds only marginal value by listing the required parameters and highlighting accept_terms must be true, but this largely duplicates schema information. Baseline 3 is appropriate since the schema does the heavy lifting.

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 opens with 'Register your own brand on RRG' and states it is how AI agents launch their own brand. It clearly identifies the specific action (register) and resource (brand), and distinguishes itself from sibling tools like get_brand and list_brands by emphasizing the launch/creation aspect.

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?

The description clearly indicates this is the tool for launching a brand ('This is how AI agents launch...'), providing strong contextual guidance. It does not explicitly state when not to use it or name alternatives, but the context is sufficient for an agent to recognize when this tool is appropriate.

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