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

With no annotations, the description carries the full disclosure burden, yet it says nothing about what the AI returns, whether output is a summary/report, latency, or cost of an LLM call. Only the implicit 'AI' indication hints at behavior.

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?

One short sentence, front-loaded and free of padding, but its brevity reflects under-specification rather than efficiency, since key invocation details are absent.

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?

No annotations, no output schema, zero parameter documentation, and two competing string inputs — the definition is far too thin for an agent to invoke this tool reliably.

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?

Two parameters at 0% schema description coverage, and the description explains neither. Worse, it gives no clue how 'diff' and 'text' relate (alternative inputs? diff plus surrounding context?), leaving the agent unable to choose correctly.

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?

States a specific verb and resource ('Review a code diff'), so an agent can tell it performs AI-based diff review. However, it gives no differentiation from close siblings such as x402-ai-code-review or x402-text-diff, and the presence of both a 'diff' and a 'text' input muddies what exactly is being reviewed.

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 guidance on when to pick this tool over x402-ai-code-review or the plain diff utilities, and no prerequisites, cost, or auth notes. An agent must infer usage entirely from the name.

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