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

With no annotations, the description carries the full behavioral burden, and it does disclose the return content and the billing cost ('1 credit per call'), which are genuinely useful. It omits input size limits, whether input is sent externally, and any failure behavior for very large texts, so gaps remain.

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?

A single tight sentence front-loads the operation and appends the cost note without padding. Every clause earns its place.

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?

There is no output schema, so the description correctly fills that gap by naming the return fields (added/removed lines, similarity score). For a two-string utility tool with no annotations, this is close to sufficient; only input limit and error behavior are unstated.

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% across the two parameters, but the names 'before' and 'after' are largely self-explanatory and the description's phrase 'diff of two texts' conveys that exactly two string inputs are compared. It adds no detail on ordering semantics or the 100,000-character cap documented in the 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?

States a specific verb and resource ('line-by-line diff of two texts') and even names the output artifacts (added/removed lines, similarity score), so the agent knows exactly what the tool produces. It does not differentiate itself from nearby siblings such as text_utils or multi_model_compare, which keeps it out of 5 territory.

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 parenthetical use cases (contracts, configs, policies) hint at appropriate inputs, but there is no explicit when-to-use statement and no mention of when to prefer an alternative like text_utils. The agent must infer context entirely.

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