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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior, so the safety bar is low. The description adds genuinely new context beyond them: the upstream data source (GLEIF), an epistemic caveat that records reflect submissions and are not independent verification, and a payment requirement of $0.0052 USDC via x402 on Base mainnet, which is critical for an agent that must arrange payment before calling.

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 compact sentences front-load what the tool returns, then the caveat, then the cost; each clause carries information an agent needs (scope, trust caveat, payment). The pricing sentence is appended after the caveat rather than up front, which slightly buries a constraint that affects whether the call can succeed.

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 single-parameter lookup with an output schema present, the description need not explain return fields, and it correctly focuses on source, scope, trust caveat, and payment. The main residual gap is that it never explicitly contrasts with the search_lei sibling, which matters given how many entity-lookup siblings exist in this toolset.

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 coverage is 0%, so the description must carry the burden, and it does specify that the LEI must be an exact 20-character identifier, reinforcing and contextualizing the pattern in the schema. With only one parameter and little else to disambiguate, this is sufficient, though it adds no detail on case handling or checksum behavior.

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 opens with a concrete verb and resource: "Retrieve normalized public legal-entity reference data from GLEIF," and constrains it to "an exact 20-character LEI." The word "exact" implicitly separates it from the sibling search_lei, though it never names that sibling, so an agent must infer the distinction.

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?

"Use to resolve a known identifier to its legal name, status, jurisdiction, and public addresses" gives clear when-to-use context that naturally excludes fuzzy/name-based search. It stops short of explicitly stating "if you have a name rather than an LEI, use search_lei," so the routing guidance is implied rather than spelled out.

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