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

With no annotations, the description carries the full behavioral disclosure burden. It adds a key constraint ('equal-length strings') and defines the computed result, but it does not state what happens for unequal lengths, how case sensitivity or Unicode is handled, or what the output format looks like.

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 two sentences long, front-loads the mathematical definition, and then provides the invocation guidance. Every sentence earns its place with no filler or redundancy.

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?

The tool is simple, but the lack of an input schema, output schema, and annotations means the description must be more self-sufficient. It explains the operation and names the input aliases, but omits the return value format and behavior on invalid or unequal-length inputs, leaving minor but real gaps for an agent facing those cases.

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?

The input schema defines zero parameters, so the description is the only source of parameter meaning. It identifies two string inputs and their aliases ('a' or 'text', 'b' or 'other'), which is essential for invocation. It could be more precise about exact parameter names and types, but it compensates well given the empty 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?

The description clearly identifies the operation: calculate the Hamming distance between two equal-length strings, with an explicit definition of the result. It does not explicitly differentiate from nearby siblings like x402-hamming-weight or x402-levenshtein-distance, but the phrase 'between two equal-length strings' makes the core use case clear.

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 description conveys when to use the tool (whenever a Hamming distance between two equal-length strings is needed) and how to supply inputs ('Provide a (or text) and b (or other)'). However, it does not mention alternatives or exclusion criteria, such as when to prefer a different similarity/distance tool.

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