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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states the mathematical definition but says nothing about input format, output format, determinism, error handling, or whether it is a pure computation. For a computation-only tool this is less critical, but the omission is still a gap.

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 front-loaded sentence that efficiently states the core concept. It slightly repeats 'aliquot sum' but otherwise contains no wasted words.

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?

With no output schema and no annotations, the description should clarify input requirements (e.g., that a positive integer is expected) and what is returned (the sum). It also does not resolve the ambiguity of two string parameters, leaving the agent unsure which one to populate. For a simple math tool, more context would be valuable.

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 100%, so the baseline is 3 even though the description adds no parameter-specific information. The schema descriptions ('N to process', 'Value to process') are themselves vague and do not clarify which parameter is the integer input, but per the rule, the high coverage keeps this at the 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?

The description names a specific mathematical function: the aliquot sum, defined as the sum of proper divisors. It is distinguishable from siblings like x402-aliquot-sequence (which returns a sequence) and x402-is-abundant (which tests a condition). However, it does not explicitly state that it takes an integer and returns its aliquot sum, and it does not name any sibling tool for contrast.

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 use this tool versus alternatives. The description does not mention related tools (e.g., x402-aliquot-sequence for sequences, x402-is-perfect or x402-is-abundant for classification), nor does it state prerequisites or typical use cases.

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