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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false. The description adds useful context beyond annotations: pricing per successful call, x402/Solana payment, HTTPS endpoint, and the n bounds. It does not specify error behavior, but annotations carry the safety profile.

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 purpose and parameter examples are front-loaded, and the pricing/endpoint details earn their place. There is slight redundancy between the sequence listing and the per-index examples, but the description remains compact and readable.

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 read-only math tool, the description covers purpose, indexing, range, examples, cost, and access. It could explicitly state the return type, but the examples make the integer output clear enough.

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 the parameter meaning—and it does. It explains zero-based indexing, states the range 0 to 10000, and gives concrete mappings like n=0 gives 2, n=5 gives 4, and n=8 gives 6.

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?

States it returns the nth partial quotient of e, starting at n=0, with worked examples and bounds. It clearly names the specific resource, but does not differentiate itself from siblings like e_cf_prefix or e_convergent.

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?

Gives only the valid range and examples; there is no explicit guidance on when to use this versus alternatives such as e_cf_prefix, e_cf_sum, or e_convergent. The agent must infer that this retrieves a single term from the continued fraction.

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