interpret_usage_term

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

No annotations are provided, so the description carries the full burden. It describes what the tool returns (meaning, relative value vs base rate, trap to watch), which is helpful behavioral information. Yet it does not mention limitations, edge cases, or that it is a read-only operation.

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, front-loaded with the purpose, and no wasted words. It efficiently conveys the tool's function, input scope, and output.

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 simple tool with one enum parameter and no output schema, the description covers the key aspects: what it does, what inputs it accepts, and the general nature of its output. It could be more detailed about the output format, but it is sufficient for most use cases.

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 lists the term enum values, giving context that these are the acceptable inputs, but it does not explain each term's meaning. This partially compensates but is not exhaustive.

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 uses a specific verb ('Interpret') with a clear resource ('usage/rights term') and lists concrete examples. It distinguishes itself from sibling tools like interpret_pricing_model by focusing on usage/rights terms rather than pricing models.

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 clear context: for briefs or contracts, and enumerates the specific terms it handles. However, it does not explicitly state when not to use it or mention alternatives, so it misses the full 'when/when-not/alternatives' threshold.

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