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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic action and does not mention return format, pagination, filtering semantics, or default behavior. For a list tool, this leaves uncertainty about what output to expect.

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, front-loaded sentence with no superfluous words. It conveys the core purpose and relevant domain context efficiently.

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 simplicity (two optional parameters, no output schema), the description is minimally adequate. However, it leaves gaps: it does not state what fields are returned, how 'q' matches (partial vs exact), or whether results are sorted. With no annotations, additional context on expected output would improve completeness.

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?

The input schema already describes both parameters with 100% coverage (q as 'Keyword', category as 'Category filter'). The description adds examples of category values (vocabulary, indicators, regimes), which provides some additional meaning beyond the schema, but not enough to raise the score above baseline.

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 ('List') with a clear resource ('glossary terms') and adds domain context ('prediction market vocabulary, indicators, regimes'). This makes it easy to distinguish from sibling tools like get_glossary_term, which implies retrieving a single term.

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?

No guidance is provided about when to use this tool versus alternatives such as get_glossary_term or other list_* tools. There are no exclusions, prerequisites, or preferred use cases, leaving the agent to infer usage from the name alone.

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