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

The annotations already cover safety (readOnly, idempotent, non-destructive). The description adds genuine behavioral context beyond those: the operation is deterministic, costs $0.001 USDC, and runs on Base or Solana. No contradiction exists with the annotations.

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?

The description is a single sentence with no filler, and it front-loads the cost and network scope. However, it is so terse that some required semantic context is 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?

For a two-parameter tool with strong annotations, the description is acceptable but not complete. It omits the expected return format, normalization rules, and how the payment on Base or Solana is expected to be made, which an agent would need for fully reliable invocation.

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?

With 0% schema description coverage, the description needed to compensate by explaining parameters like separator and the default behavior. It only says 'slug generation' and never clarifies how text is transformed or how the optional separator affects output.

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 names the operation as 'deterministic slug generation' and adds the payment/network context, which distinguishes it from the encoding, hashing, and parsing siblings. It is reasonably clear, though it never explicitly says 'convert text to a URL-friendly slug.'

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 over siblings like hash_encode, url_parse, or json_normalize, and no mention of prerequisites. The only conditional hint is the paid nature of the tool, which is not enough to steer an agent's selection.

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