get_customs_friction_baseline

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

No annotations, so description carries burden. It discloses scoring weights, country coverage, score direction, and optional parameter behavior. However, it mentions an optional country parameter not present in the input schema, which could mislead an agent about tool capabilities.

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?

Three concise, well-front-loaded sentences. Each provides distinct value: purpose, data composition, and use audience. 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?

Covers what is returned (composite score, components, history), coverage scope (21 countries/regions), and intended users. Lacks explicit output format for multi-country queries and parameter syntax for the claimed optional country filter, but sufficient for a high-level understanding.

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 has zero parameters, baseline 4, but description claims an optional country parameter. This is a schema contradiction. The description adds misleading information about a parameter that does not exist in the schema, so it fails to provide accurate semantic guidance.

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?

States clearly it retrieves customs friction baseline scores by country, with explicit composite scoring methodology (55% port congestion, 45% policy events), distinguishing it from related tools like get_customs_trade_events and get_port_congestion_trends.

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?

Targets trade compliance, procurement, and logistics audiences and explains the score's meaning (higher = more friction), implying use cases. Does not explicitly contrast with alternatives or state when not to use, but provides sufficient context.

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