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

Annotations already declare readOnlyHint=true, and the description adds valuable context: data source, scaling method, monthly update frequency, and the historical depth since 1958. It discloses the metric's nature (scaled YoY change) and output fields, which goes beyond the annotation coverage, though it doesn't enumerate all potential caveats.

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 concise yet information-dense: two sentences cover the metric, use cases, and update cadence. Every clause adds value—e.g., data source, output fields, and timing examples—without repetition or filler.

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?

Despite lacking an output schema, the description lists the returned fields, explains the metric's construction, notes monthly updates, and defines appropriate use cases. The parameter schema handles history behavior, making the tool fully understandable for an agent to select and invoke correctly.

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 for the single 'days' parameter is 100%, so the schema already explains its behavior (optional history series, max 1825 days, Gold tier requirement). The description adds no additional parameter semantics, but none are needed; 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?

The description states a specific verb ('Returns') and a well-defined resource ('0-100 global trade-openness score... World Bank world trade as % of GDP'), making the tool's function unambiguous. It also lists exact output fields and gives a precise domain, distinguishing it from generic data tools even without naming siblings.

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?

Provides explicit when-to-use guidance: 'Call when the user asks about globalization, deglobalization, trade expansion or contraction, tariffs, or supply-chain shifts' and includes a rotation strategy context. It also specifies a non-use case ('not PMI sentiment surveys'), giving clear boundaries for invocation.

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