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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful behavior: the response shape (topic numbers, titles, one-line summaries, UNVERIFIED counts) and the confidence-tag vocabulary ([V], [V-mfr], [UNVERIFIED], [inference], [Expert]), which lets the agent interpret results correctly. No auth, rate-limit, or ordering caveats are mentioned, keeping it just under a 5.

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 core instruction is front-loaded and the confidence-tag legend is a compact, high-value final sentence. The long parenthetical enumerating eighteen topic categories is the only excess; it is informative for scope disambiguation but heavier than necessary.

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 need not explain return values, yet it still summarizes them and decodes the confidence tags. It omits the include_sections parameter and any note on response size or pagination, but for a zero-required-parameter listing tool this is close to complete.

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?

There is one optional parameter and schema coverage is 100%, with the schema itself documenting include_sections and its effect ('Also list every section id (e.g. 30.4) per topic'). The description adds nothing about the parameter. Per the high-coverage baseline, 3 is the correct score.

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 and resource ('List the 32 topics in the commercial glass & glazing knowledge base') and enumerates the topical scope in enough breadth that an agent immediately knows what domain this covers. The cardinality (32) and the enumerated categories distinguish it from search_glazing_knowledge and get_topic without opening any schema.

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 a clear selection rule: 'Call this first if you are unsure which topic covers a question.' That is explicit when-to-use guidance. It stops short of naming the alternatives (search_glazing_knowledge, get_topic) or when NOT to use it, so it is strong but not fully routing.

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