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

With no annotations, the description carries the behavioral disclosure burden. It discloses the glossary scope, the two accepted input formats (slug or label), and the fallback behavior for no-match cases. It also mentions locale defaults indirectly through the schema, so the few missing pieces (exact definition of a 'close suggestion', no error-handling detail) are minor for a read-only lookup tool.

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 succinct—two sentences with no filler. The purpose and scope are front-loaded, and the fallback behavior is a compact addition that earns its place. Slight redundancy with the schema's example and the 'slug or label' phrasing could be trimmed, but overall it's efficient.

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 two-parameter, no-output-schema read-only lookup, the description is mostly complete. It provides the glossary scope, input constraints, and the no-match fallback, which is enough for an agent to decide and call correctly. The remaining gap is the lack of error/return-shape details, but that's not required for a lookup tool like this.

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%, and the description adds little beyond the schema's own parameter documentation. Why the description does repeat the 'slug or label' semantics, the locale default and term example are already provided in the schema, so no additional meaning is required or provided.

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 and resource ('Definition of an industrial term from the Capita glossary'), names the glossary scope (90 entries: protocols, OT/IT concepts, industrial AI, energy), and clarifies acceptable inputs (slug or label). It clearly differentiates this from sibling tools like search_knowledge or compare_protocols by focusing on a single-term lookup.

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 implies when to use the tool (when you need a term definition), and it also mentions a key fallback behavior: if no confident match, it returns close suggestions. However, it doesn't explicitly state when not to use it or name alternatives like search_knowledge or list_protocols, so usage guidance is more implicit than explicit.

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