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. The description adds meaningful context beyond annotations: 'pure computation' implies determinism/no side effects, and 'free' communicates no cost or quota concern.

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 front-loaded sentence lists the supported categories and ends with a useful behavioral qualifier. No wasted language.

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 three required string parameters at 0% schema description coverage and no output schema, the description should specify valid unit formats or examples. It does not, so an agent must guess how to populate 'from' and 'to' outside of temperature.

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 0%, so the description must carry parameter semantics. It only partially does: it lists temperature unit codes (c, f, k) but gives no format or examples for length, mass, volume, or data-size units, leaving 'from' and 'to' ambiguous.

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 specific verb and resource: convert units, with explicit supported categories (length, mass, volume, data size, temperature). It clearly distinguishes this from sibling conversion tools like color_convert and timestamp_convert.

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 clear purpose, but there is no explicit guidance on when to use this versus other conversion tools or any exclusions. 'Pure computation, free' gives useful context but not selection criteria.

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