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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so safety is covered. The description adds meaningful value beyond that: it discloses that results come from PerfuMate's own scent model (not raw data), mirrors the app's scent profile sheet, includes a confidence value on the wear line, and samples the drydown at fixed hours (0/1/4/8/24). That is useful behavioral context, though the label is essentially a read-only lookup.

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?

It is a single front-loaded sentence that opens with the trigger condition before enumerating the output, which is the right ordering. It is dense with output detail but every clause earns its place; only the sheer length of the colon-list keeps it from 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 carries the return-value burden and does so thoroughly (families, sub-notes, drydown, wear line plus confidence, genre, pyramid, how accords are counted). Combined with annotations that fully cover the safety profile, an agent has enough to call it correctly; only minor gaps like pagination/format shape remain.

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 schema already documents the single 'formula' parameter (id from list_formulas or exact name). The description adds no additional parameter semantics, so the baseline 3 for well-covered schemas 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 names a specific resource (a formula's scent profile) and a specific action (retrieve/derive it from PerfuMate's scent model), and it enumerates exactly what the profile contains — families, sub-notes, drydown timeline, wear line, genre, note pyramid. This clearly distinguishes it from siblings like get_formula (the formula itself) and check_formula, letting an agent pick it without opening the 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?

It gives an explicit trigger: 'Use this when the user asks what a formula of theirs will smell like, how it evolves or how long it lasts.' That is clear contextual guidance covering the main use cases. It stops short of naming a specific alternative tool or when NOT to use it, so it falls just below the top bar.

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