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

With no annotations, the description carries the full burden. It discloses that the result is constrained to the label set, the multi-label option, and an approximate cost. Lacks details on output format or error behaviors, but for a paid tool, cost transparency is valued.

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, each earning its place: core functionality and cost. No wasted words, front-loaded.

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?

Covers main functionality, parameter behavior, and cost. For a simple tool with 3 parameters and no output schema, it is mostly complete. Lacks details on edge cases like too many labels or text length limits.

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 coverage is 0% with no parameter descriptions. The description adds meaning: 'text' is input text, 'labels' is the label set (2-32), 'multi' enables multiple labels. This explains constraints and behavior beyond the schema's type/name.

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?

Clearly states it classifies text into one or multiple labels using a constrained label set (2-32 labels). The verb 'classify' and resource 'text' are clear, but it does not differentiate from sibling tools like 'generate' or 'extract'.

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?

Provides guidance on the 'multi' parameter for single vs. multi-label classification and mentions cost. However, it does not specify when to use this tool versus alternatives, nor does it give prerequisites or when-not-to-use.

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