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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds real value beyond that: the three data sources used, the rating taxonomy (Close / Approximate / Not supported by the numbers), and the confidence-tag legend returned in responses. Return-format detail overlaps with the output schema, keeping this from 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 purpose and input examples are front-loaded in the first sentence, and the enumeration of data sources follows logically. It is dense and citation-heavy (Topic 32 §32.9, Topic 29), but each sentence carries substantive information rather than 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?

For a five-parameter, read-only cross-reference tool with an output schema already defined, the description supplies everything an agent needs: what it does, when to use it, the inputs it accepts, the sources consulted, and the meaning of the confidence tags it returns.

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%, so all five parameters (product, substrate, target_maker, limit, include_discontinued) are already documented in the schema. The description echoes product examples but adds no syntax, default, or behavioral detail beyond what the schema provides; baseline 3 applies.

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 opens with a specific verb+resource ('Given a glass coating/product ... return equivalents from other makers with a match rating'), immediately distinguishing it from siblings like lookup_glass_performance or search_glazing_knowledge. It also enumerates concrete input examples, leaving no ambiguity about what the tool returns.

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?

It states the use case explicitly ('Use for "or-equal" and substitution screening') and gives a sample query ('SNX 62/27 Vitro equivalent'). It stops short of naming sibling tools or stating when NOT to use it, so it is clear context without explicit exclusions.

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