Look up any Legal Entity Identifier (LEI) for company information lookup and counterparty / know-your-business (KYB) identity against the official GLEIF global registry — returns legal name, status, jurisdiction, legal form and registered address, real-time, worldwide coverage. Price: $0.01 per call (x402 payment, USDC on Base mainnet).
| Name | Required | Description | Default |
|---|---|---|---|
| lei | Yes | 20-character LEI, e.g. '529900T8BM49AURSDO55' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals the output fields, real-time nature, worldwide coverage, and pricing/payment details ($0.01 per call via x402). It does not mention failure modes or status codes, but for a lookup tool the disclosed context is substantial.
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 sentences, front-loaded with purpose, then returns and pricing. Every clause adds value—no filler or redundancy.
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?
Despite lacking an output schema, the description enumerates the key return fields (legal name, status, jurisdiction, legal form, registered address) and adds real-time/coverage/price context. For a single-parameter lookup, this is sufficient for an agent to understand expected behavior.
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 100% with the 'lei' parameter already described (20-character format and example). The tool description adds no extra parameter-level nuance beyond restating that it looks up an LEI, so it meets the baseline without exceeding it.
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 states the verb ('Look up') and the specific resource ('Legal Entity Identifier (LEI)') against the official GLEIF registry. It lists the returned fields (legal name, status, jurisdiction, etc.) and explicitly positions it for KYB/company lookup, which distinguishes it from siblings focused on crypto/trading/sanctions.
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 provides a clear context for use: 'for company information lookup and counterparty / know-your-business (KYB) identity.' It does not explicitly name alternatives or exclusions, but the sibling tools are thematically different, making the intended use unambiguous.
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.
There is notable overlap between crypto_pre_trade_verdict and solana_pre_trade, both providing pre-trade decisions for Solana. The agent_rank_check and agent_visibility_audit are also similar in purpose but differentiated by depth. However, descriptions are detailed enough to clarify the intended use, so ambiguity is moderate.
Tool names consistently use snake_case and often include domain prefixes like crypto_, solana_, and agent_. Minor deviations exist, such as solana_pre_trade lacking the 'verdict' suffix seen in crypto_pre_trade_verdict, and standalone names like gleif_lei and polymarket_odds that don't follow a domain-prefix pattern. Overall, the style is predictable and readable.
With 10 tools, the server is well-scoped within the ideal 3-15 range. Each tool serves a distinct purpose or tier (e.g., quick check vs. deep audit), and the count feels appropriate for a multi-purpose utility server without being overwhelming or sparse.
The server covers several domains, but each has gaps. For example, there is no dedicated wallet address sanctions screening tool (only fused into crypto_pre_trade_verdict), no token price or market data tool outside of the dossier, and no agent search or listing functionality. However, the core risk-check workflows (token safety, pre-trade, agent visibility) are reasonably well-covered with both quick and detailed tiers.