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

With no annotations, the description carries the full burden, and it discloses meaningful operational context: a Personal+ account requirement and a pay-per-call fallback ($0.01 USDC on Base or Solana via x402, with the payment placed in _meta['x402/payment']). It does not mention pagination, rate limits, or error behavior, but the auth/payment disclosure is substantive.

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 with zero filler: return values first, then prerequisite, then auth/payment. Every sentence earns its place and the payload is front-loaded.

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 2-param read tool with no output schema, the description covers what is returned, how to resolve inputs, the account tier, and the payment path. It is nearly complete; only the meaning of the domain abbreviations (RI/RIS/HRI) and ID format are unstated.

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 compensate: it clarifies that subject_id/subject_type derive from search_subjects and that the subject is a research topic/keyword/sector, which loosely maps to the enum. It still doesn't state the expected ID format or the distinction between 'keyword' and 'sector' beyond naming them, leaving a real gap.

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 a specific verb ('Get') and enumerates the exact metrics returned (RI, RIS, HRI, paper count) for a research topic/keyword/sector. This is far more specific than the title/name alone, though it doesn't explicitly contrast itself with siblings like get_element_ri or get_subject_papers.

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 an explicit prerequisite chain: 'call search_subjects first to resolve subject_type/subject_id', naming the sibling to use and why. It also flags the account/payment conditions. It stops short of saying when to prefer this over get_subject_papers or get_subject_history, which share the same subject vocabulary.

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