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

Annotations already cover readOnly=true, destructive=false and closed-world, so the safety profile is free; the description earns credit by adding what annotations cannot: determinism, the hash return value, and an explicit x402 pricing model ($0.002 USDC per successful call, failures not charged) that affects an agent's willingness to retry. It stops short of explaining idempotency guarantees or size limits.

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 dense sentences, front-loaded with the transformation list before the return value and pricing. Every clause carries unique information; nothing is repeated from the name or title.

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?

Output is well covered (stable hash) and pricing is disclosed, which matters for a paid tool. But the input channel is entirely unexplained against an empty parameter schema, so an agent knows what it gets back yet not how to supply the text.

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 zero parameters, the baseline is 4; there is nothing in the schema to annotate. The description does not, however, explain how the input text reaches the tool, which is the one semantic question an empty `{type: object}` schema leaves open.

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?

Names a specific verb (normalize) and enumerates the exact transformations performed (NFKC, zero-width/bidi stripping, quote/dash folding, whitespace collapse, case folding) plus the return value (stable content hash). That pipeline differentiates it from neighbors like hash, slugify, dedupe, and diff without the agent needing to open any 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 phrase 'so two texts can be compared for exact equality' implies the canonical use case but never states when to pick this over `diff`, `dedupe`, or `hash`, which are the obvious alternatives. Usage is inferable but not routed.

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