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

Beyond the annotations (readOnlyHint, openWorldHint, destructiveHint), the description adds valuable behavioral context: it is purely keyword-based, runs offline, does no reasoning, and has known recall gaps ('misses anything the keyword table does not name'). This goes beyond what annotations provide and sets accurate expectations.

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?

Two sentences, no filler. The core purpose is front-loaded in the first sentence, and the crucial comparison/limitation in the second. Every word contributes value.

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?

The tool is simple (one parameter, output schema present, annotations cover safety). The description sufficiently explains the input's purpose, the matching mechanism, and the flaw. It does not detail the output, but that is covered by the existing output schema; nothing critically missing.

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 100%, so the schema already fully documents the applicationId parameter. The description adds some context by implying the applicationId references an application whose business description is used, but it does not explicitly connect the parameter to the behavior or clarify its role beyond what the schema says. Baseline 3 applies with adequate schema coverage.

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 states a specific action—'proposes Nice classes by keyword-matching the business description'—and immediately distinguishes itself from RecommendClasses by positioning it as the 'offline fallback.' This makes the tool's purpose and differentiation from its sibling explicit, so an agent can reliably tell them apart.

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 names the alternative (RecommendClasses) and frames this tool as its 'offline fallback,' which clearly implies when to use it (when offline or when the primary recommendation path is unavailable). It also states the conditions under which it will be useful ('no network, no reasoning'). However, it does not explicitly say 'when not to use' this tool (e.g., prefer RecommendClasses when network/reasoning is available).

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