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

With no annotations, the description carries the full disclosure burden, and it does well: it specifies the per-pillar payload (score, trend direction, driving data points), states that an unmeasured pillar is reported as 'unavailable with the reason', and documents the composite-withholding rule when fewer than three pillars exist. It omits any note on staleness/cadence of the underlying data or whether this is a pure read.

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 is front-loaded in the first sentence and each following sentence carries distinct content: pillar contents, per-pillar output shape, intended user question, and edge-case handling. It is slightly long — the pillar enumeration could be tightened — but no sentence is pure 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?

For a zero-parameter tool with no output schema and no annotations, the description supplies the return structure (per-pillar score, trend, driving data points), plus the two behavioral edge cases (unavailable pillar with reason, composite withheld below three pillars). An agent has everything needed to call it and interpret the response.

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 has zero parameters, so per the rules the baseline is 4. The description correctly implies the tool takes no inputs (it is a category breakdown for the current cycle), and there are no parameter names or formats it could add meaning to.

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 ('Get detailed breakdown of supply chain disruption risk by category') and enumerates exactly what is returned (Transportation, Energy, Materials, Macro pillars). This makes the tool's scope identifiable, but it never names or contrasts a sibling such as supply_chain_risk_assessment or get_gdi_trend_analysis, so differentiation is left to inference.

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?

'Essential for supply chain managers who need to diagnose which risk category is elevated and why' gives a clear context of use and a concrete question the tool answers. It does not, however, state exclusions or point an agent to an alternative when a different question (e.g. trend over time) is asked, which the large sibling set would warrant.

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