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

With no annotations, the description must carry behavioral disclosure. It communicates that this is a workflow, specifies its content dimensions, and discloses payment/rate information ('15.0 USDC on Base, pay-per-use'), which is useful context. However, it does not describe side effects, authentication, or what is actually returned beyond the inferred sequence.

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 compact, front-loaded with the tool's type and object, and uses labels ('WORKFLOW', 'input=product', 'B2B') to keep information scannable. It includes the parenthetical detail, audience, and pricing without wasted prose.

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 one-input tool with no output schema, the description gives enough to understand what the tool produces (activation onboarding sequence across channels, timing, messages) and for whom. The main gap is the absence of explicit return-format or output-delivery information, but the low complexity and clear content dimensions keep this from being a serious omission.

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 schema only describes the parameter as 'service input,' so the description's 'input=product' adds meaningful semantics that tell an agent what value to supply. Although schema coverage is 100%, the field name and description are generic, and this guidance materially improves invocation accuracy.

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 frames the tool as a workflow that produces an activation onboarding sequence, specifying the covered dimensions (channels, timing, messages) and the input (product). It is clearly distinguished from generic workflow/pipeline siblings by its onboarding-specific scope, though it lacks an explicit verb such as 'generate' or 'design.'

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 states the target use case ('B2B: PLG teams boost activation') and the required input ('input=product'), giving an agent clear conditions for selection. It does not explicitly mention when not to use it or name alternatives, but the audience and goal narrow the choice among many sibling tools.

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