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

Annotations already cover read-only, idempotent, non-destructive, closed-world, so the description's job is to add context — and it does: lexical matching semantics, empty list on no match, no generative filling of gaps, and the structure of empty-result suggestions. These are behaviors an agent cannot get from the annotations or 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?

Four tight sentences with no filler: purpose, when-to-use, query strategy, then return behavior. The most decision-relevant content (what it is and when to use it) is front-loaded.

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 an output schema present, the description needn't explain return values, yet it usefully covers the empty-result case and suggestion payload. Given four parameters and full schema coverage, little is missing; only the alternative-search-tool routing is absent.

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; the description earns an increment by advising how to shape the query ('use specific terms — names, standards, numbers'), which adds operational meaning beyond the schema's bare 'Search terms'. Language filtering is only gestured at ('any ... language').

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 specific verb ('Search') and a specific resource ('sourced knowledge records and open questions'), plus scope ('any subject and language'). It does not explicitly contrast with siblings like browse_knowledge or get_knowledge, so the agent must infer the term-based search boundary, but the lexical-search framing distinguishes it reasonably.

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?

Gives an explicit use case: verifiable facts, definitions, dates, rules or standards with sources, and verifying a claim before stating it. It stops short of naming alternatives (e.g. browse_knowledge for exploration, ask_question when no record exists) or stating when not to use it.

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