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

Annotations already cover read-only, idempotent and closed-world safety. The description adds genuinely new behavior: it returns a definition plus link and will suggest close matches when the exact term misses, which tells the agent how to handle a miss. It does not state what the miss response looks like beyond 'close matches'.

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 compact sentences, front-loaded with the action and scope, followed by return behavior. No filler.

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?

With one parameter, no output schema and strong annotations, the description covers purpose, expected input vocabulary and return shape. The only gap is the fuzzy-match behavior being described but not specified.

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 carry the load. The term examples clarify the expected vocabulary (acronyms, concepts like 'super app'), but nothing is said about casing, exact-match requirements, or multi-word handling.

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?

States a concrete verb and resource ('look up a term in the Digital in Asia glossary'), quantifies scope (103 terms) and gives representative examples (UPI, QRIS, super app). It is unmistakably different from the sibling market/report tools.

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 examples imply the domain where this tool applies, so usage is inferable, but there is no explicit statement of when to prefer it over e.g. search_dia or get_country_profile, and no exclusions.

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