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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a comparison operation but says nothing about whether it is read-only, what it returns, whether any state is mutated, or what permissions are needed.

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 front-loaded phrase with no wasted words. It is structurally clean, though its brevity contributes to gaps in other dimensions rather than being a conciseness problem itself.

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 no annotations, no output schema, and 0% parameter description coverage, the one-line description is far too thin for an agent to invoke the tool correctly. It does not describe the required inputs, the optional context parameter, or the return value.

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 explain the parameters. It loosely implies two outputs (mapping to output_a and output_b) but does not explain them, and it never mentions what the optional 'context' parameter does.

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 ('semantic diff') and resource ('agent outputs'), so the basic operation is clear. However, it does not differentiate this tool from siblings such as agents_contradiction or detect_contradiction, which also compare or analyze text/outputs.

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?

There is no guidance about when to use this tool versus alternatives, nor any preconditions or exclusions. The phrase 'between agent outputs' implies the general context but leaves selection entirely to inference.

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