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

With no annotations, the description carries the behavioral disclosure burden. It explains matching behavior ('exact-first, then substring') and the unknown-term fallback ('returns a sample of available terms'), plus what the response includes. It does not cover potential errors or case-sensitivity, but it gives materially useful behavioral detail beyond the schema.

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?

Three sentences with no filler; the purpose, examples, output summary, and matching behavior are all included efficiently. It is front-loaded with the primary action and resource before diving into details.

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 single-parameter lookup with no output schema, the description covers the input semantics, the output contents (definition, section anchor, deep link, version), and edge-case behavior. Nothing critical is missing for an agent to select and invoke the tool correctly.

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 100%, so the baseline is 3, but the description adds meaningful parameter semantics: it gives examples and spells out matching semantics (exact-first, substring, unknown-term sample). This goes beyond the schema's simple 'The term to look up' description.

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 verb ('look up') with a clear resource ('WEO methodology definition') and object ('platform-specific term, field, or concept'), and provides concrete examples. It also differentiates the tool from its data-returning siblings by framing it as the vocabulary resolver for terms other tools return.

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 gives clear context: 'Use to resolve any vocabulary the other tools return,' which tells an agent when this tool is the right choice. It does not explicitly name alternatives or state when not to use it, but the guidance is sufficient for the single-term lookup case.

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