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

Annotations already declare read-only, idempotent, non-destructive, open-world behavior. The description adds valuable context beyond annotations: the pricing model ($0.001 USDC per successful call via x402 on Solana) and an HTTPS endpoint for the same operation.

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 front-loaded with the core operation and rule, followed by examples, domain, and payment details. The multiple example mappings are slightly redundant but still useful for validation, and no sentence is wasted.

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 simple one-parameter tool with rich annotations and no output schema, the description covers the operation, input domain, examples, pricing, and alternate endpoint. It lightly implies the return value through examples but does not explicitly state that the output is an integer.

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 0%, so the description must carry parameter meaning. It states the valid domain for n (1 to 1,000,000) and illustrates input-output behavior with examples, compensating well for a single integer parameter, though it could explicitly name n as the parameter.

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 specific operation (one Collatz step) and defines the rule precisely, including worked examples for even, odd, and edge inputs. However, it does not differentiate itself from close siblings such as collatz_step and collatz_steps, leaving ambiguity about which to choose.

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?

It implies usage by defining a single-step computation but gives no explicit when-to-use guidance, prerequisites, or alternatives. With many Collatz-related siblings, the absence of routing guidance is a meaningful gap.

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