AgentKYB

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

With no annotations, the description carries the full behavioral burden. It conveys a read-only lookup via 'Check' and 'public', but does not disclose potential side effects, rate limits, authentication needs, or error behavior. This is adequate for a simple read tool but leaves 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 a single, front-loaded sentence with no redundancy. It leads with the core action and resource, then lists the relevant fields, making efficient use of every word.

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 tool with no output schema, the description adequately covers the tool's purpose and the types of data returned. It doesn't clarify error handling or output formatting, but these are minor for a lookup tool and are partly implied by the listed fields.

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 fully describes the sole parameter ('Domain name, e.g. example.com') with 100% coverage, so the baseline is 3. The description doesn't add parameter-level meaning beyond what the schema already provides; it only lists output fields, not 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 specifies the verb 'Check', the resource 'public RDAP registration evidence for a domain', and enumerates the data fields (status, registrar, dates, registry information). This clearly distinguishes it from the sibling tools, which focus on companies, sanctions, and vendor preflight.

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 usage for domain registration checks but provides no explicit when-to-use guidance or when-not-to-use alternatives. It doesn't mention sibling tools or exclusions, leaving the agent to infer appropriate invocation.

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

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It explicitly lists the returned fields (legal name, registration number, jurisdiction, status, LEI, confidence, source corroboration), which clarifies the read-only, look-up nature. It does not explicitly state that no data is modified, but 'resolve' strongly implies a non-destructive operation, and the output detail offers reasonable transparency.

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, well-structured sentence that front-loads the purpose and then lists the key returns. Every clause adds value: the action, the input type, the source, and the output fields. There is no redundant wording or unnecessary elaboration.

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 2-parameter lookup tool with no output schema and no annotations, the description is largely complete. It tells the agent what the tool does, what to input, and what it will output. It does not mention edge cases (e.g., not found), rate limits, or authentication, but these are not critical for making the call. Given the tool's simplicity, it covers the essential context adequately.

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 both parameters ('name' and 'country') documented with descriptions. The tool description does not add further semantic detail about parameter formats or constraints beyond what the schema provides. The baseline of 3 applies because the schema already does the heavy lifting, and the description merely refers to 'business or vendor name' and optional country.

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 action ('Resolve'), the resource ('a business or vendor name'), and the outcome ('to an official legal entity'). It also specifies the data source ('AgentKYB's global and national business-registry sources') and enumerates the returned fields, making it readily distinguishable from siblings like check_domain or screen_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 purpose implies use for legal entity lookups, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. It lacks guidance on when not to use it (e.g., if only a domain is known, use check_domain) or any prerequisites. The context is present in the purpose but not framed as usage guidance.

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

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 does add useful context by naming the indexed sources and stating that potential matches require human/compliance review. However, it does not disclose the output format, match certainty, or whether results include non-matches, which matters because there is no output 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?

Two concise sentences with no filler. The core operation and entity scope are front-loaded, and the compliance-review caveat is placed right after, giving the reader the operational and risk-relevant context efficiently.

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 tool, the description covers purpose, applicable names, data sources, and a meaningful follow-up requirement (human/compliance review). It could be improved by stating what the tool returns or by mentioning sibling-tool trade-offs, but nothing essential for invoking it correctly is missing.

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 fully documents the only parameter ('Name to screen'), so the baseline is 3. The description adds meaningful semantic detail by specifying that the name should be a company, vendor, or counterparty and by listing which sanctions lists will be searched, going slightly beyond 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?

Clearly identifies the action (screen), the target entity types (company, vendor, counterparty name), and the specific sanctions sources (OFAC SDN, non-SDN, UK, UN). This makes it readily distinguishable from sibling tools like check_domain, resolve_company, and vendor_preflight.

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 the tool: whenever a business name must be checked against official sanctions lists. However, it does not explicitly state when not to use it or point to an alternative such as vendor_preflight, which may be the broader compliance-oriented option.

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

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

With no annotations, the description carries the full burden. It communicates that the tool aggregates evidence and returns decision support, but it does not disclose whether external calls are made, whether any state changes occur, what the compact evidence result contains, or how results should be interpreted.

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?

Two sentences with no filler. The core purpose is front-loaded, and the second sentence adds a meaningful caveat. Every phrase contributes to understanding what the tool does.

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 description is adequate for a high-level composite tool but leaves gaps: there is no output schema, no explicit return-value description, and no guidance on how this relates to the sibling tools. An agent could call it correctly, but it would not know what evidence fields to expect or when a single-purpose sibling is more appropriate.

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 adds mild value by linking 'domain/company-name consistency' to the name and domain parameters and implying country is relevant to sanctions screening, but it does not explicitly explain each parameter's role beyond 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 identifies a specific resource and action: a pre-transaction business counterparty check for AI agents. It enumerates the exact evidence components combined (legal-entity resolution, sanctions screening, RDAP domain evidence, domain/company-name consistency), so the tool's scope is unambiguous even without referencing sibling names.

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 phrase 'Pre-transaction' and the exclusion 'not legal or transaction approval' give useful context, but the description does not explicitly say when to use this composite tool versus the sibling tools check_domain, resolve_company, and screen_sanctions. Usage is implied rather than stated: use this when a combined evidence result is needed.

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