validate_leiLegal Entity Identifier checksum validation. $0.002 per call.
| Name | Required | Description | Default |
|---|---|---|---|
| lei | Yes | 20-character Legal Entity Identifier (ISO 17442), e.g. 5299000J2N45DDNE4Y28 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is well-covered. The description adds the cost of '$0.002 per call' and scopes behavior to 'checksum validation,' which communicates that full LEI registry verification is not performed. This is useful contextual information beyond what annotations provide.
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 two short, front-loaded sentences with no redundant words. The core purpose ('checksum validation') comes first, followed by the only additional behavioral detail (cost). Every word earns its place, and the structure is easy to parse quickly.
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?
The tool has no output schema, so the description carries the burden of explaining what the caller can expect in return, but it does not specify the return type (e.g., boolean, status object, error behavior). It also omits any note about edge cases, such as what happens with a malformed LEI. For a single-param, read-only tool with annotations, the gaps are moderate but noticeable.
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% and the 'lei' parameter already clearly documents length, format, and an example. The tool description adds no additional parameter-level detail. With full schema coverage, a baseline score of 3 is appropriate, as the description does not need to compensate.
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 clearly identifies the operation as 'checksum validation' and the resource as 'Legal Entity Identifier (ISO 17442)', which is specific and informative. It does not explicitly contrast with sibling validators like validate_iban or validate_isin, but the identifier type alone is sufficient to disambiguate. It falls slightly short of a 5 because it never states that it should be used only for LEI and not other identifiers.
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?
The description implies that the tool is used when a 20-character LEI needs to be checked, but it gives no explicit guidance on when to choose this tool over validate_bic, validate_iban, validate_isin, or validate_vat. There are no exclusion conditions or mention of prerequisites such as 'only for checksum verification, not registry lookup.' Usage context is implied by the resource name rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are cleanly separated by domain prefix (data_, security_, validate_, verify_) and describe distinct outputs. A couple of pairs like token_verdict vs verify_token or data_portfolio vs wallet_dossier could be confused until descriptions are read, but the descriptions resolve the ambiguity.
The majority of tools follow a predictable prefix_subject pattern, e.g. data_block, security_tls, validate_iban, verify_payment. A few outliers like html_to_markdown, text_diff, wallet_dossier, and token_verdict use different conventions, but the overall system remains readable.
20 tools is on the heavy side for the typical MCP server and sits in the 16–25 'feels heavy' zone. Most tools have a legitimate purpose, but the five validate_* identifier tools plus two generic utilities could feel like surface area bloat.
The server covers a broad and coherent read/validation domain: chain data, token safety, payments, security checks, and identifier validators. Minor gaps exist, such as lack of detailed historical transaction/activity data and no general network/domain security scan beyond email, TLS, and typosquat.