approximately_equal

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

No annotations are provided, so the description carries the full burden. It mentions handling 'floating-point precision issues,' which hints at behavior, but doesn't disclose details like the default tolerance value (1e-9 from the schema), how tolerance is applied (e.g., absolute vs. relative), or what the output looks like (e.g., boolean). This leaves significant gaps for a tool with no annotations.

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 very concise and front-loaded, with two sentences that directly state the purpose and key behavior. There is no wasted text, and the domain/category in parentheses is efficiently included without redundancy.

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?

Given no annotations, no output schema, and low schema description coverage (0%), the description is incomplete. It lacks details on behavioral traits (e.g., output format, error handling), parameter usage, and differentiation from siblings. For a comparison tool with three parameters, this is inadequate to guide an AI agent effectively.

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 schema description coverage is 0%, so the description must compensate. It implies parameters 'a' and 'b' as the numbers to compare and 'tolerance' as the threshold, but doesn't explain their semantics beyond 'floating-point numbers' and 'tolerance.' This adds some meaning over the bare schema but doesn't fully clarify usage (e.g., tolerance units or typical values).

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 purpose: 'Check if two floating-point numbers are approximately equal within a tolerance.' It specifies the verb ('check'), resource ('two floating-point numbers'), and scope ('within a tolerance'), though it doesn't explicitly differentiate from sibling tools like 'equal' or 'is_close' beyond mentioning floating-point precision handling.

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 provides minimal guidance, stating it 'Handles floating-point precision issues' and includes a domain/category, but it doesn't specify when to use this tool versus alternatives like 'equal' or 'is_close' (which is a sibling tool). No explicit when/when-not instructions or prerequisites are given.

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