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

With no annotations, the description carries the full burden. It usefully discloses output behavior ('report the first differing position') and a per-call price with payment chain ($0.003 per call, USDC on Base), which is uncommon and valuable context, but it says nothing about error conditions, pure-function guarantees, or how payment is authorized.

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 front-loaded sentence: operation, options, output, and cost. Nothing is redundant and nothing buries the lead.

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 text utility with no output schema, the description covers the operation, the option set, one aspect of the return value, and pricing. It stops short of describing the full response shape, but that is a minor gap for a simple transformation 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 coverage is only 50% and the schema itself has no enum for 'form' — the description supplies the concrete valid values (NFC, NFD, NFKC, NFKD), which is real added meaning. 'text' remains undocumented but is self-evident from the description's 'Normalize text'.

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?

The description states a precise verb and resource ('Normalize text') and enumerates the four normalization forms, plus what it reports back. It does not explicitly name or distinguish itself from siblings like tk_homoglyphFold or tk_slugify, but the operation is unambiguous.

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?

There is no guidance on when to choose this tool versus alternatives such as tk_homoglyphFold or tk_slugify, and no guidance on which of the four forms to pick or when not to use it. Usage must be inferred 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.