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

With no annotations, the description must disclose behavioral traits, but it only states the general conversion capability. It does not mention return format, edge cases (e.g., temperature offset conversions), or unit string normalization, leaving the agent with incomplete behavioral context.

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 description is a single sentence and immediately states the tool's purpose. It is front-loaded and contains no redundant words, earning top marks for conciseness.

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?

The description lacks a list of supported unit abbreviations or an explanation of return values. Given that there is no output schema, the agent would need to guess valid unit strings (partial examples exist in the schema) and is not told what the converted result looks like, making the contextual information incomplete.

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?

The input schema already describes all three parameters (value, from, to) with full coverage, so the description adds no new parameter-level information. The category list (length, mass, etc.) gives high-level context but does not map to specific parameter behavior.

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 clearly states the tool's verb ('Convert') and resource ('numeric value between units'), and enumerates six unit categories, which distinguishes it from the sibling utility tools (e.g., base64_codec, json_to_ts). This gives the agent a precise understanding of what the tool does.

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?

The description implies usage when a conversion between these unit types is needed, but it does not explicitly state when to use it over alternatives, nor does it provide exclusions. Since no sibling tool performs unit conversion, alternative guidance is unnecessary, but explicit 'use when' phrasing is absent.

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