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

Beyond the annotations (which already cover readOnly/idempotent/non-destructive), the description discloses the full return payload, the fuzzy-match fallback ('without an exact match it returns the closest catalog names'), and an important semantic caveat that the limit is a regulatory ceiling, not a recommended dose. That is meaningful behavioral context the structured fields do not carry.

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?

Front-loaded with the use case, then return contents, caveat, and the sibling alternative in a logical order, with no filler sentences. It is a dense single paragraph that could be broken up for scanability, which keeps it just short of a 5.

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?

There is no output schema, so the description correctly compensates by listing what is returned, and it covers the mismatch/fallback case plus the IFRA limit interpretation. For a single-parameter read tool with rich annotations, nothing an agent needs to call it correctly is missing.

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% and the single 'name' parameter already documents that canonical names, synonyms and CAS numbers are accepted, so the schema does the heavy lifting. The description adds only a small amount beyond that, namely that inexact input degrades to nearest catalog names rather than failing. Baseline 3 is appropriate.

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 names a specific verb (show/return) and resource (one perfumery material) and enumerates the exact user questions it answers: odour, usage, strength/longevity, IFRA limit. It explicitly distinguishes itself from check_formula, so an agent can separate it from siblings like search_materials without opening schemas.

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 gives an explicit when-to-use trigger ('when the user asks what one perfumery material smells like... how much of it IFRA allows') and names the alternative tool plus the condition that selects it ('To check a whole formula use check_formula'). Nothing about routing is left to inference.

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