Lithuanian company due diligence and KYC identification, attested by an attorney-at-law.
Scored across 9 tools
Each tool targets a distinct resource or lifecycle step: registry profile, participants, beneficial owners, court cases, property, seizures, and KYC order create/poll. The aggregate report is clearly framed as a combined view, so it does not create ambiguity with the individual getters.
Tool names are almost uniformly verb_noun with snake_case: get_beneficial_owners, get_court_cases, get_seizures, create_kyc_package. The only notable deviation is lookup_company, which uses 'lookup' instead of the otherwise dominant 'get' pattern, but the style remains consistent and readable.
Nine tools is well-scoped for a Lithuanian due-diligence domain. Each tool covers a meaningful data source or lifecycle action, and none feel redundant or ornamental.
The surface covers company profile, ownership, KYC ordering, litigation, property, and seizures, with an aggregate report tying them together. Minor gaps exist, such as no company search by name and no direct evidence-container retrieval, but the described workflow is otherwise functional.
Order a QES-signed identification package for a role-holder of a Lithuanian legal entity. The register says who holds the role; the person proves they are that person by signing a dossier with their own qualified electronic signature, and an attorney-at-law attests the verified correspondence. Returns immediately with an order id and a ceremony URL to give the subject; the outcome arrives later. Poll with get_kyc_package. Billed only when a package is delivered.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). | |
| purpose | Yes | Purpose of processing; logged per call. Required for beneficial-owner data. | |
| subjectRole | Yes | Which role the subject is claimed to hold in the entity. | |
| subjectEmail | No | Optional. When given, Tvarka emails the ceremony link to the subject; otherwise the link is returned for you to deliver. | |
| idempotencyKey | No | Reuse for retries of the same create request. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description fully discloses asynchronous behavior (returns immediately, outcome later), billing semantics (only when delivered), and processing transparency (purpose logged per call). Idempotency key is also mentioned for retries.
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?
Description is largely succinct but contains slight redundancy with the phrase 'The register says... signing a dossier...' and the repeated 'Returns immediately... later.' Minor extra context that does not hinder understanding.
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?
Provides a complete picture: creation flow, asynchronous outcome, polling target, delivery options, billing conditions, and a special requirement for beneficial-owner data. No output schema is present, but the description sufficiently explains what is returned.
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 descriptions cover 100% of parameters. All five parameters are explicitly explained, including the optional subjectEmail behavior and the idempotencyKey purpose. Enums are self-explanatory within context.
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?
Clearly states the action (order), the resource (QES-signed identification package), and the subject (role-holder of a Lithuanian legal entity). Differentiates from sibling get_kyc_package by focusing on creation vs. retrieval.
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 instructs to poll with get_kyc_package for the outcome, mentions immediate return of order id and ceremony URL, and notes billing only on delivery. Also mentions purpose required for beneficial-owner data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Declared beneficial owners of a Lithuanian legal entity, with ownership percentages and control basis. Served under the legitimate-interest regime; a purpose is required and is logged.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). | |
| purpose | Yes | Purpose of processing; logged per call. Required for beneficial-owner data. | |
| interpret | No | Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the legitimate-interest regime and that purpose is logged, adding behavioral context. However, it does not mention the output format, potential fees (such as the interpret parameter), or error conditions, leaving significant gaps.
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 and front-loads the key resource and output details. It could be phrased more directly (e.g., starting with 'Returns...'), but it avoids fluff and is efficiently structured.
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 absence of an output schema and annotations, the description reasonably covers the resource, key output fields, and legal regime. The parameters are fully documented in the schema, so the description need not repeat them. However, some behavioral details (fees, response format) are absent, preventing a 5.
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%, so the baseline is 3. The description's mention that 'a purpose is required and is logged' mirrors the schema's existing parameter description, adding no new semantic value. The interpret parameter is not mentioned in the description, but the schema fully documents 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 identifies the resource (beneficial owners of a Lithuanian legal entity) and the key output fields (ownership percentages, control basis), distinguishing it from siblings like court cases or real estate. However, it lacks an explicit action verb like 'Get' or 'List,' relying on the noun phrase 'Declared beneficial owners.'
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 states that the tool operates under the legitimate-interest regime and requires a purpose, which implies when use is appropriate. It does not explicitly name alternatives or state when not to use this tool, leaving the boundary with get_participants or lookup_company unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Court hearings where the Lithuanian legal entity appears as a party.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the core behavioral scope (returns hearings where the entity appears as a party), which is useful. However, it does not mention potential limitations, data source, or handling of edge cases like no results, leaving some behavioral details unspecified.
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?
A single, focused sentence that front-loads the essential purpose without any filler. Every word contributes meaning and the structure is immediately parsable.
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—one required parameter, no annotations, and no output schema—the description provides adequate context for an agent to understand what the tool does. However, it could be enhanced by noting any return format or caveats, though not strictly necessary for such a direct query 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?
The input schema already provides a full description of the single 'code' parameter, including its pattern and meaning. The tool description adds no additional semantic information about this parameter, so the schema carries the load and the baseline score of 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 the tool returns court hearings where the entity is a party, making the resource and scope unambiguous. It distinguishes from sibling tools by focusing on court cases rather than ownership, real estate, seizures, etc. Though phrased as a noun phrase rather than a verb, the purpose is effectively conveyed.
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 intended use is implied by the description (i.e., retrieve court cases involving a Lithuanian entity), but no explicit guidance is given on when to use this tool versus alternatives. There are no exclusions or references to sibling tools, so the guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
One call returning the whole picture: profile, participants, beneficial owners, real property, seizure acts and court cases. Cheaper than the parts bought separately. A purpose is required because the report contains beneficial-owner data.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). | |
| purpose | Yes | Purpose of processing; logged per call. Required for beneficial-owner data. | |
| interpret | No | Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden but only partially discloses behavior. It mentions the purpose requirement and cost advantage, but does not mention the interpret fee, potential side effects, or output format. This is a moderate disclosure for a report retrieval tool.
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 three sentences, front-loaded with the core function and immediately followed by cost and requirement context. Every sentence adds value without 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?
Given the detailed parameter schema and the listed report components, the description is fairly complete for selecting this tool. It covers what the report contains and the purpose requirement, though it omits output structure details that are not covered elsewhere.
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 descriptions for all parameters. The description adds no additional parameter details beyond the schema, confirming the baseline score of 3.
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 explicitly states the tool returns a full due-diligence report including profile, participants, beneficial owners, real property, seizure acts, and court cases. This clearly distinguishes it from sibling tools that fetch individual components, so the purpose is clear and specific.
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 when to use this tool by highlighting that it is cheaper than buying parts separately and that a purpose is required for beneficial-owner data. It does not explicitly name alternatives or exclusions, but the value proposition guides selection for comprehensive due-diligence needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Current state of a KYC package order: whether the subject has signed, the cross-check outcome, and the evidence container digest once delivered. The container bytes are fetched over REST, not through this tool.
| Name | Required | Description | Default |
|---|---|---|---|
| orderId | Yes | The order id returned by create_kyc_package. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses what the tool returns (signed status, cross-check outcome, digest) and adds timing context ('once delivered') as well as the REST routing note for container bytes. It doesn't explicitly state read-only, but 'current state' implies no mutation, and no side-effect or error details are given.
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 tight sentences, front-loaded with the core purpose and followed by a single important limitation. Every word earns its place; no filler or repetition of the tool name.
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 one-parameter status tool with no output schema, the description explains what information is available, adds a timing nuance, and clarifies what the tool does not do (container bytes). It doesn't cover return formatting or error behavior, but the information provided is sufficient for most use cases.
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?
The input schema already fully describes the single parameter (orderId from create_kyc_package). The description adds no additional parameter-level detail, but schema coverage is 100%, so the baseline of 3 applies; the description's reference to 'order' aligns with 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?
The description clearly states the tool reports the current state of a KYC package order, listing specific elements: signing status, cross-check outcome, and evidence container digest. This distinguishes it from sibling tools by focusing on the KYC package lifecycle rather than beneficial owners, court cases, etc.
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 this is the check-status tool for a KYC package order, and it explicitly excludes fetching container bytes via this tool (noting they come over REST). This provides a useful when-not boundary, though it doesn't name alternatives or describe the typical create-then-check flow explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Current participants (shareholders, members) of a Lithuanian legal entity.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries the full burden. It only adds the adjective 'current' to indicate a snapshot, but does not disclose whether the operation is read-only, any access requirements, rate limits, or response characteristics. This is insufficient behavioral disclosure.
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 a single, concise sentence with no redundant content. It is well-structured and easy to parse immediately.
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 simple schema and lack of output schema, the description still feels incomplete. It does not explain what data will be returned (e.g., names, percentages), when to choose this over siblings, or any caveats. The description reads more like a label than a full tool explanation.
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?
The input schema already provides a complete description of the 'code' parameter, including a pattern and explanation. The description's mention of 'Lithuanian legal entity' essentially duplicates the schema. With 100% schema coverage, 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 the resource (participants/shareholders/members) and scope (Lithuanian legal entity), and the tool name includes 'get' to indicate retrieval. It differentiates from sibling tools like get_beneficial_owners by specifying shareholders and members, though it is phrased as a noun phrase rather than an explicit action statement.
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?
No guidance is provided on when to use this tool versus alternatives like get_beneficial_owners or lookup_company. The description does not mention any context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Real property registered to a Lithuanian legal entity, with the rights recorded on each object. Legal entities only.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses that the tool reads registered property data and includes rights, but does not mention any read-only guarantee, pagination, or potential error conditions. This is adequate but not rich.
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 the main purpose, and contains no filler. Every word adds value, including the 'Legal entities only' clarification.
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 single-parameter get tool with no output schema, the description covers what the tool returns, the scope (registered property, rights), and the entity-type restriction. It could mention whether results are paginated or list details, but this is not essential for basic 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?
The single parameter 'code' is fully documented in the schema with a pattern and description, giving high schema coverage. The tool description adds no extra parameter meaning, but baseline 3 is appropriate since the schema already carries the semantic load.
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 returns real property registered to a Lithuanian legal entity, including the rights recorded per object. This uses a specific resource (real property of legal entities) and distinguishes itself from sibling tools like get_court_cases or get_participants, which cover different domains.
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 restricts usage to legal entities, signaling when not to use it (individuals). It does not name alternative tools for other property types or scenarios, but the context is clear enough that an agent can infer this is the go-to tool for real estate holdings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Property seizure acts registered against a Lithuanian legal entity, with the institution that imposed them, the parties and the seized assets. An entity with no acts is a clean record, not a missing answer.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). | |
| interpret | No | Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that an entity with no acts returns a 'clean record' rather than a missing answer, which is a key behavioral nuance for result interpretation. It also outlines the response content, but does not mention error behavior, auth requirements, or rate limits. Overall, it provides meaningful context beyond the schema.
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, both essential and front-loaded. The first sentence presents the core functionality and output, while the second clarifies a potential misinterpretation of empty results. No unnecessary words or repetition of schema details.
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 lack of an output schema, the description provides useful details about the return data (institution, parties, seized assets) and clarifies the clean record behavior. It is not exhaustive (e.g., no date ranges or pagination), but it is sufficiently complete for a focused data retrieval tool alongside clear sibling 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?
The schema already provides 100% coverage for both parameters, including a regex pattern and description for 'code' and a detailed explanation for 'interpret'. The description adds no additional parameter-level semantics, so a baseline score of 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 specifies the tool's function: retrieving property seizure acts for a Lithuanian legal entity, including the imposing institution, parties, and seized assets. This distinguishes it from sibling tools like get_court_cases or get_beneficial_owners by focusing on seizure-specific 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 does not provide explicit guidance on when to use this tool vs. alternatives. It only mentions the clean record interpretation, which addresses data semantics rather than tool selection. No exclusions or alternative tool references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Core registry profile of a Lithuanian legal entity: name, legal form, status, registered address, registration dates, capital, activities and current management. Current data with officially attested provenance.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Lithuanian legal-entity code (juridinio asmens kodas). | |
| interpret | No | Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the data is 'current' and has 'officially attested provenance', which is useful context, but it does not disclose other behavioral traits like possible errors, response format, or rate limits. A mid-range score is appropriate.
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, directly stating the tool's purpose and content. It is well-structured and front-loaded with the key information, with no wasted words.
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 tool with simple parameters and no output schema, the description adequately lists the data fields returned and notes data currency. It is complete enough for an agent to understand the basic scope, though error handling and return structure are not elaborated.
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?
The schema has 100% description coverage for both parameters, so the description adds no additional parameter meaning. The schema already explains the code pattern and the interpret boolean with its fee implication. Baseline score of 3 is justified.
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 provides a 'core registry profile' of a Lithuanian legal entity, enumerating the specific data fields (name, legal form, status, etc.). This is specific and distinguishes it from sibling tools that focus on narrower aspects like ownership or court cases.
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 this is the general-purpose company information tool, but it does not explicitly state when to use it versus the specialized siblings. It gives context ('core registry profile') but omits any exclusion criteria or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
create_kyc_package1 field changedInput schema / properties / idempotencyKeyAdded value: +{
+ "description": "Reuse for retries of the same create request.",
+ "maxLength": 128,
+ "minLength": 1,
+ "type": "string"
+}create_kyc_packageget_kyc_packageget_beneficial_owners1 field changedInput schema / properties / interpretAdded value: +{
+ "description": "Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call.",
+ "type": "boolean"
+}get_due_diligence_report1 field changedInput schema / properties / interpretAdded value: +{
+ "description": "Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call.",
+ "type": "boolean"
+}get_seizures1 field changedInput schema / properties / interpretAdded value: +{
+ "description": "Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call.",
+ "type": "boolean"
+}lookup_company1 field changedInput schema / properties / interpretAdded value: +{
+ "description": "Set true to add the standardized legal interpretation of the answer: what the data means under Lithuanian law, with statute citations. Adds the interpretation fee to the call.",
+ "type": "boolean"
+}get_beneficial_ownersget_court_casesget_due_diligence_reportget_participantsget_real_estateget_seizureslookup_companyCzech & EU due diligence in one call — facts, insolvency, sanctions, VAT, risk score, UBO chain.
Czech KYC due-diligence — paid tier extension (nominee, phoenix, risk timeline, watchlist).
Due diligence & KYC: PEP, national and international sanctions (OFAC, UN, EU, UK, FBI, INTERPOL, FIN
KYB due diligence for agents: sanctions screening, EU VAT/VIES, LEI, IBAN in one verdict.
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