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

Since no annotations are provided, the description carries the full transparency burden. It discloses key non-obvious behaviors: swatches are not sent standalone, they ship at order placement, and the request is capped at 5 codes. This is valuable context beyond the bare 'register' semantics. It does not mention side effects like requiring an existing order, but the main policy is transparent.

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 three sentences, front-loaded with the primary purpose, then key policy, then customer guidance. Every sentence earns its place, with no redundant or vague wording. It is concise yet comprehensive for the core message.

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 tool with 6 parameters and no output schema, the description covers the essential 'what' (register swatches), 'when' (with order placement), and 'how to handle objections' (pre-order asks). It does not explicitly mention required fields, but the schema provides that. It also doesn't describe error conditions, but the description is adequately complete for an AI agent to select and use the tool correctly in most scenarios.

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 67%, which is moderate. The description adds meaning to swatch_codes by specifying the max of 5 and that they ship with the order, which is useful. It does not elaborate on customer_name or customer_email, but those are common fields. Baseline 3 is appropriate because the schema already covers some parameters, and the description adds limited extra parameter-level detail.

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 registers up to 5 colour swatches for dispatch with the customer's order, using a specific verb ('Register') and resource ('colour swatches'). It distinguishes itself from sibling tools by emphasizing the swatch-and-order context, and the 'NOT sent as standalone postal sample' clause differentiates it from any standalone sample request tool. Scope and constraints are explicit.

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 provides clear context on when the tool is appropriate: swatches ship only with order placement, not as standalone samples. It also gives explicit customer-handling guidance for pre-order requests ('explain they ship with the blind and guide them to place their order first'). However, it does not explicitly compare this tool to alternative tools like submit_enquiry, so some exclusion guidance is missing.

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