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

With no annotations, the description carries the full burden and does reasonably well: it discloses what is stripped and repaired, that a cleaned string is returned, and adds a non-obvious operational fact (per-call pricing in USDC on Base). It omits idempotency/side-effect notes and any auth context, keeping it out of the top band.

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?

Three short sentences, all load-bearing: the operation first, the trigger condition second, the return value and pricing last. No repetition or filler.

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?

For a two-parameter, no-output-schema tool the description covers the operation, the use case, the return value, and cost. The only residual gap is behavioral nuance around the options parameter, which is minor given full schema coverage.

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 reported at 100%, so the schema already documents the text parameter and its 100000-char limit, making 3 the baseline. The description adds no detail about the options parameter (e.g. what 'digits' modes do) beyond the schema's terse example, so it does not exceed baseline.

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 specific verbs (remove, repair) and the exact resource (Unicode bidi control characters and RTL punctuation spacing), so the agent knows precisely what transformation occurs. It does not differentiate itself from the nearby sibling fa_normalize, which could plausibly overlap, so it falls short of a 5.

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?

Gives a clear triggering condition: 'use it to clean Persian or Arabic text that renders in the wrong order or shows stray markers.' It supplies a use context but names no alternatives or when-not conditions, so it stops short of explicit routing.

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