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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered and the bar is lower. The description adds genuine value by naming the return fields (tier name, approximate population percentile, casual 1–10 equivalent), which matters because there is no output schema. It doesn't state determinism or rounding/precision behavior, but nothing is contradicted.

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?

A single sentence with zero filler: the operation, the input domain, and the outputs are all front-loaded. Every clause earns its place with no restatement of the tool name or title.

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 one-parameter, no-output-schema conversion tool, the description supplies the essential missing piece by describing what is returned. What is absent is minor edge-case context (rounding of fractional PSL values, invalid-input behavior), which the schema's min/max partly covers.

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% and the range 0–8 is already enforced by minimum/maximum in the schema, so the baseline is 3. The description adds a little meaning by identifying the scale as the 'looksmaxxing face rating scale', but supplies no extra syntax, unit, or precision guidance beyond that.

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 states a precise verb (convert) and resource (a PSL score on the 0–8 looksmaxxing face rating scale) and enumerates the three transformed outputs. An agent can immediately distinguish this from siblings like classify_face_shape, get_face_measurement_tool, and lookup_looksmaxxing_term, which deal with shape, measurement, and terminology respectively rather than numeric conversion.

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?

Usage is implied by the purpose: call it when you hold a PSL value and need its tier/percentile/1–10 mapping. However, there is no explicit when-to-use framing, no mention of the potentially overlapping lookup_looksmaxxing_term sibling, and no note on out-of-range or non-integer inputs. Adequate but with clear routing gaps.

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