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

With no annotations, the description carries the full burden and does substantial work: it defines the score range and direction (higher = more risk), names the underlying data scale (200+ variables, 26 ports, 31 commodities), and discloses degraded-result behavior — unavailable pillars are reported with a reason and the composite is withheld below three measured pillars. It stops short of permissions, rate limits, or latency, so not a 5.

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?

Purpose and return value are front-loaded, with supporting data-source detail and the degradation rule following in descending priority. Roughly five sentences, most of which earn their place; the list of four user personas is the one soft spot that could be trimmed.

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?

With no output schema and no annotations, the description must explain what comes back, and it does: a composite index, its range and direction, pillar availability semantics, and the withholding threshold. What is missing is whether pillar-level sub-scores or the underlying variable readings are included in the response, which an agent would want to know before calling.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly adds no parameter noise.

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 a specific verb and resource (assess supply chain disruption risk) and defines the returned artifact precisely: the Global Disruption Index, a 0-100 composite over four named pillars. This implicitly separates it from siblings like risk_pillar_breakdown or get_gdi_trend_analysis, but it never names those alternatives, so an agent must infer the routing.

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 lists audiences (procurement teams, logistics planners, traders) and a goal (real-time visibility and risk monitoring), but audience is not the same as a use condition. There is no when-to-use-this-vs-sibling guidance and no exclusions, so an agent cannot tell why it would pick this over report risk_pillar_breakdown or get_gdi_trend_analysis.

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