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

The description discloses key behavioral traits beyond annotations: it validates inputs, sends an email, returns a pending_id, and imposes a 10-minute requirement. Even though annotations are all false (not read-only, not idempotent), the description aligns and adds meaningful context. It doesn't fully describe what happens on duplicate signups or whether the email is always sent, but the provided details are valuable.

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 two sentences, front-loaded with the main verb and resource ('Begin clariBI account signup'), followed by concise process details and a clear next-step callout. Every sentence earns its place with no redundancy.

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 5-parameter tool with an output schema, the description covers the full flow: validation, email dispatch, pending_id return, and the required follow-up action. It is complete for an AI agent to understand the tool's role, inputs, and outcome without needing to inspect further documentation.

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 description coverage is 100%, so the baseline is 3. The description adds a small amount of semantic meaning by noting validation of 'email + organization name,' which is not explicitly in the schema. However, it doesn't elaborate on the optional fields (first_name, last_name) or further clarify accept_terms, so it stays at the baseline.

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 clearly states the tool's purpose: 'Begin clariBI account signup.' It details the specific actions (validates email + organization, emails verification code, returns pending_id) and distinguishes itself from sibling tools by explicitly referencing the next step, verify_email.

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 provides clear context for when to use the tool ('Begin clariBI account signup') and explicitly instructs the user to 'Call verify_email(pending_id, code) within 10 minutes to finish signup,' which is a clear follow-up action. However, it doesn't explicitly mention when not to use this tool or list alternatives, so it misses the full 'when/when-not/alternatives' guidance.

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