Pay-per-call compliance via x402: wallet sanctions, OFAC name, UK + US company verification.
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Average 4.4/5 across 5 of 5 tools scored.
Most tools have distinct purposes: screen_wallet, screen_name, verify_uk_company, verify_us_company are clear. The 'diligence' tool is a combined call that overlaps with screen_wallet and verify_uk_company, but its description explains it runs both in parallel, so agents can distinguish. Slight potential confusion if an agent wants a single screening but picks the combined tool.
Naming is partially consistent: screen_wallet and screen_name follow a screen_ prefix for sanctions, verify_uk_company and verify_us_company follow verify_ for company lookups. However, 'diligence' uses a different pattern (no prefix), breaking the verb_noun convention. Mixed but still readable.
Five tools is ideal for this domain: covers the key compliance functions (wallet screening, name screening, UK company KYB, US company verification) with a combined call for convenience. No unnecessary tools, and each adds value.
Covers the stated purpose of on-chain and off-chain due diligence for UK and US entities. Missing: other jurisdictions (EU companies), and the combined tool explicitly notes no verified link between wallet and company, which is a minor gap. Overall, core workflows are complete.
diligenceACombined counterparty due diligence in one call: runs sanctions screening on a crypto wallet (Chainalysis oracle — OFAC SDN, EU, UN) AND a UK Companies House KYB lookup (status, type, PSC / beneficial owners) in parallel. Built for compliance agents vetting a counterparty that has both an on-chain wallet and a UK company. Returns both independent results, plus an explicit disclaimer that no verified link between the wallet and the company is established by the data.
| Name | Required | Description | Default |
|---|---|---|---|
| wallet | Yes | EVM wallet address (0x + 40 hex) to sanctions-screen | |
| company | Yes | UK Companies House registration number to verify |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses parallel execution, independent results, and a disclaimer about no verified link. Adds value beyond readOnly and openWorld annotations.
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?
Single concise paragraph, no wasted words, effectively front-loaded with the main function.
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?
Adequately describes the combined function and use case, but lacks details on result structure since no output schema exists.
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 clear descriptions. Description adds no additional detail beyond what's in the schema.
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?
Description clearly states it combines sanctions screening on a crypto wallet and UK Companies House KYB lookup. It distinguishes from sibling tools like screen_wallet and verify_uk_company by offering a combined call.
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?
Explicitly states it's built for compliance agents vetting a counterparty with both an on-chain wallet and a UK company. Implies not to use if only one check is needed, but lacks explicit exclusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
screen_nameAOFAC name screening: fuzzy-match a person or company name against the official US Treasury OFAC Specially Designated Nationals (SDN) list (primary names + strong aliases). Returns scored candidate matches with the matched name, SDN type, and program. SCOPE: this is a screening aid for AML / KYC / sanctions compliance — a match is a candidate to investigate with secondary identifiers (DOB, nationality, ID), NOT a determination. Weak AKAs are not screened, per OFAC guidance.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Person or company name to screen against the OFAC SDN list | |
| threshold | No | Optional match confidence cutoff 0.5–1.0 (default 0.85). Lower = more candidates, more false positives. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description transparently discloses the output format (scored candidate matches with matched name, SDN type, program), the scope (screening aid, not determination), and the limitation that weak AKAs are excluded. No contradictions with annotations.
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 concise at three sentences, front-loading the main purpose. It is well-structured: first the action, then output, then scope/limitations. Minor improvement could be breaking into bullet points for readability, but overall efficient.
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?
Given no output schema, the description adequately explains the return format (scored candidates with matched name, SDN type, program). It covers important constraints (weak AKAs excluded, need for secondary identifiers). For a screening tool with simple parameters, this is fully complete.
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% for both parameters, so baseline is 3. The description does not add significant new meaning beyond the schema's descriptions for 'name' and 'threshold'. The schema already explains the threshold range and default. The description's context aligns but does not enhance parameter semantics.
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 'fuzzy-match' and the resource 'person or company name against the OFAC SDN list'. It specifies it screens primary names and strong aliases, distinguishes from weak AKAs, and clarifies it is a screening aid, not a determination. The purpose is distinct from sibling tools like 'screen_wallet' or 'verify_uk_company'.
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 explicitly states when to use: for AML/KYC/sanctions compliance. It provides clear exclusions: weak AKAs are not screened, and a match is not a final determination, requiring secondary identifiers. However, it does not explicitly compare to sibling tools or state when not to use this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
screen_walletASanctions screening for a crypto wallet address. Checks an EVM address against the Chainalysis on-chain sanctions oracle, which covers OFAC SDN, EU, and UN designated addresses (including Tornado Cash and other sanctioned protocols). Returns a clear sanctioned / not-sanctioned result with the matching program. Use for AML compliance, counterparty due diligence, and payment screening before sending USDC or any funds to an address.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | EVM wallet address (0x + 40 hex) to sanctions-screen |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint and openWorldHint, indicating safe read operation and variable results. The description adds behavioral details: the oracle used, lists covered, and output format (sanctioned/not-sanctioned with program). It complements annotations without contradiction and adds meaningful context beyond them.
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 four sentences, front-loading the core purpose, then providing details and use cases. Every sentence adds value, and there is no wasted text. Ideal conciseness for agent consumption.
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 tool with one input and no output schema, the description is complete. It explains the screening process, the oracle, covered lists, output format, and use cases. An agent can fully understand when and how to use the tool.
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 a clear description for the single parameter 'address'. The description reiterates the field but does not add new semantic meaning beyond confirming it's an EVM address. Baseline 3 is appropriate as the schema does the heavy lifting.
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 tool screens a crypto wallet address against sanctions using the Chainalysis on-chain oracle, covering OFAC SDN, EU, and UN lists. It distinguishes from siblings like screen_name (which screens names) and verification tools, by specifying the exact use case for EVM addresses.
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 explicitly states use cases: AML compliance, counterparty due diligence, and payment screening before sending funds. It implies when to use this tool (before transactions) but does not explicitly mention when not to use or alternatives. However, the context is clear and sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_uk_companyAUK company verification and KYB (know-your-business) lookup via the official Companies House register. Given a UK company registration number, returns legal status (active / dissolved), company type, incorporation date, registered office address, and the people with significant control (PSC / beneficial owners). Use for KYB onboarding, supplier and counterparty due diligence, and confirming a UK business is real, active, and who controls it. Authoritative UK government open data.
| Name | Required | Description | Default |
|---|---|---|---|
| companyNumber | Yes | UK Companies House registration number to verify, e.g. 00000006 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by noting it is 'authoritative UK government open data' and specifying the returned data types (legal status, PSC, etc.). No contradiction with annotations, and the description enhances understanding of the tool's behavior.
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 five sentences, efficiently covering purpose, returned data, use cases, and authority. It is well-structured and front-loaded. Minor room for further conciseness, but overall very good.
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?
Given the tool's simplicity (1 parameter, no output schema), the description adequately lists the types of data returned (legal status, company type, incorporation date, address, PSC). It does not cover error handling or output format, but for a read-only lookup, it provides sufficient context.
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%, with the parameter companyNumber fully described. The description restates 'given a UK company registration number' but does not add significant new meaning beyond the schema's description and example. Baseline 3 is appropriate.
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 it performs UK company verification and KYB lookup via Companies House, specifying the exact returned fields (legal status, type, incorporation date, address, PSC). It distinguishes itself from the sibling verify_us_company by being UK-specific and provides a distinct set of data.
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 explicitly lists use cases: 'KYB onboarding, supplier and counterparty due diligence, and confirming a UK business is real, active, and who controls it.' It does not explicitly state when not to use, nor does it compare to siblings like screen_name or diligence, but the context is clear enough for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_us_companyAUS public company verification via the SEC EDGAR system. Given a ticker, SEC CIK, or company name, returns the registered entity name, CIK, industry (SIC code), state of incorporation, listed exchanges and tickers, business address, and most recent SEC filing. SCOPE: EDGAR covers SEC-registered PUBLIC companies and funds only — NOT private US companies, which register at the state level. Use for KYB and counterparty due diligence on listed US entities. Authoritative US government open data.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | US public company ticker, SEC CIK, or company name — e.g. "AAPL", "0000320193", or "Apple Inc" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds context about the authoritative government source and return fields, but does not mention rate limits or performance considerations.
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 sentences with front-loaded purpose, no redundancy. Every sentence adds value: function, return data, scope/usage.
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?
Given one parameter, no output schema, and informative annotations, the description fully covers purpose, input format, behavior, and limitations for confident agent invocation.
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 a single 'query' parameter. The description adds concrete examples (AAPL, 0000320193, Apple Inc) beyond the schema, aiding agent understanding.
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 it verifies US public companies via SEC EDGAR, listing specific return fields. It explicitly distinguishes from private US companies and sibling tools like verify_uk_company.
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?
Provides explicit use case ('KYB and counterparty due diligence on listed US entities') and scope limitations ('NOT private US companies'). Also gives example query formats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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