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

With no annotations, the description carries the transparency burden and meets it: it discloses the deterministic salience scoring, states that the caller cannot influence the lead choice, guarantees unit consistency for trade_intensity_pct, and explicitly documents why sub-contracting is omitted. It also reveals the return envelope, including the available/reason fallback signals.

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 the purpose, keeps the key behavioral caveats in a logical order, and ends with the return envelope. No sentence is wasted; the length is justified by the tool's algorithmic complexity.

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?

Given the rich output schema and the extensive sibling context, the description covers purpose, internal decision logic, data-consistency guarantees, exclusions, and the returned object envelope. It leaves no significant ambiguity about what the tool returns or how it arrives at the narrative.

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 already provides full descriptions of every parameter inside the query object (100% coverage), so the description need not repeat them. The only added semantic context is that the request body is identical to every other tradedashboard.eu analytical endpoint, which is useful but marginal; hence baseline 3.

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 by positioning the tool as the 'Autonomy & vulnerability' report-section helper and names the exact headline metric (net import reliance) plus the two computed metrics. It distinguishes this summary tool from the individual sibling tools (get_net_import_reliance, get_trade_intensity, get_export_propensity) by explaining that it decides which metric leads the narrative.

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 clearly identifies when to use the tool (as the report-section helper) and explicitly excludes sub-contracting as an unrelated topic. It names the underlying metric tools, but it does not explicitly formulate alternative conditions such as 'use get_trade_intensity when you only need that series,' so guidance is strong but not fully exhaustive.

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