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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety and statefulness profile. The description adds 'stateless' (reinforcing idempotency) and 'no predictive probabilities,' which are useful behavioral clarifications beyond annotations. However, it does not describe what the tool returns, how results are formatted, or any operational caveats, so it adds only modest value.

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 a single sentence with no filler, and the 'Stateless comparison' opener is front-loaded. It is efficient and avoids redundancy, though it is dense and jargon-heavy, which slightly hampers immediate comprehension. Overall, it earns points for conciseness.

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 tool's complexity—three nested objects, no output schema, and no enum constraints—the description is far too brief. It omits any explanation of the return format, how to interpret screening results, or what 'no predictive probabilities' means for actionable output. An agent would struggle to know what to expect or how to validate the response, making this incomplete for correct invocation.

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 description coverage is 0%, so the description must compensate. It mentions 'factory event' (incident), 'reviewed facility-product relationship' (product), and 'dated comparable stock/price/lead-time observations' (observations), giving a high-level mapping. Yet it fails to explain individual fields like event_type, operational_impact, availability, or condition, and does not specify required vs optional inputs. For complex nested objects, this is insufficient to guide correct parameter construction.

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 clearly states the tool performs a 'comparison' of a factory event, facility-product relationship, and dated observations, and explicitly notes it provides no predictive probabilities. This is a specific verb and resource, and the name is unique among siblings. However, it does not explicitly differentiate from potential similar tools, so it misses a perfect score.

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 offers no guidance on when to use this tool versus alternatives, no conditions for use, and no exclusions. It implies it is for screening supply disruptions but does not state when a caller should choose this over a sibling tool or what prerequisites exist. The only hint is 'no predictive probabilities,' which suggests it is not for forecasting but does not frame usage.

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