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

No annotations provided. Description fails to disclose key behaviors: whether inputs are parsed and pretty-printed before diffing, handling of key ordering, or whitespace normalization. Lack of detail for a mutation tool.

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?

Single sentence is concise but excessive brevity sacrifices essential details. Could include a second sentence on behavior or output without losing compactness.

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?

Lacks description of return value (unified diff as string) and does not clarify whether the tool pretty-prints inputs. Incomplete for a tool with no output schema and no annotation context.

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 coverage is 0% and description omits any mention of parameters 'a' and 'b', leaving their roles totally unspecified. Does not add semantic meaning beyond the raw schema.

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?

Clearly states the tool computes a unified diff of two JSON documents, with 'pretty-printed' hinting at normalization. Distinguishable from siblings like text_diff and json_equal, but could be more precise about output format.

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?

No explicit guidance on when to use this tool versus siblings like text_diff or json_equal. Missing context about prerequisites or ideal use cases.

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