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

With no annotations at all, the description carries the full load. It usefully discloses the return content (added/removed lines and words, similarity score) and the x402 pricing model, which is genuinely behavioral context. However, it says nothing about input size limits, whether the operation is pure/stateless, or latency, leaving gaps for a fully unannotated 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?

Two tightly packed sentences with the capability front-loaded and pricing second; no filler or 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?

No output schema exists, but the description tells the agent what is returned (diffs plus a similarity score) and how payment works, which covers most of what's needed. Missing only edge-case context like maximum text size or failure behavior, a minor gap for a stateless compute tool.

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 100%, and the paymentProof parameter already documents the full 402 payment flow in the schema. The description restates the 'two versions of a text' framing of a and b but adds no format or constraint detail beyond the schema, so the baseline 3 applies.

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 — shows added and removed lines and words between two text versions — plus a return detail (similarity score). This clearly distinguishes it from neighboring text utilities like text_stats or ai_rewrite, so an agent can select it without opening the schema.

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 comparison purpose implies when to use it (comparing two versions of a text), but there are no explicit when/when-not conditions and no sibling alternative is named. Usage guidance is inferred rather than stated.

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