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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is handled. The description adds valuable context beyond these annotations: it explains that low scores mean acute stress, describes the normalization methodology, and states the weekly update cadence since 1975. This sets clear expectations and does not contradict the annotations.

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 with clear structure: output and methodology, use cases, and update frequency. The use-case keyword list is long but directly actionable for an AI agent. Every sentence earns its place; no filler or 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 simple read-only tool with one optional parameter, the description covers what is returned, when to use it, how the score is computed, and what low/high scores mean. It names the output fields (continuity_score, freight_trend, confidence) even though no output schema exists, adding value. The only minor gap is that it doesn't itself mention the daily history behavior, but the schema fully covers that.

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 only parameter 'days' is fully described in the schema (100% coverage), including the Gold tier requirement. The description itself does not discuss the parameter, but the schema carries the full semantic burden. Given the high schema coverage, a baseline of 3 is appropriate.

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 with a specific verb and resource: it 'Returns a 0-100 global supply chain continuity score' and concretely names the constituent indices (Freightos FBX, Drewry WCI, NY Fed GSCPI) as well as output fields. This clearly distinguishes it from generic adw siblings and communicates its exact function.

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 gives an explicit 'Call when' list covering user intents (supply chain stress, container shipping costs, ocean freight rates, etc.) and business decisions (timing purchase orders, safety-stock buffers, alternate suppliers). It does not mention exclusions or alternative tools, but the triggers are far more specific than typical descriptions.

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