Verify Israeli companies using structured public-registry evidence for suppliers and due diligence.
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Average 3.7/5 across 3 of 3 tools scored.
Each tool serves a clearly distinct role: describe_service explains the service, get_schema provides input/output schemas, and verify_company performs the actual verification. There is no overlap or ambiguity between them.
All tool names follow a consistent snake_case verb_noun pattern: describe_service, get_schema, verify_company. The naming scheme is predictable and uniform.
Three tools is exactly right for a narrowly scoped, single-purpose API service: one discovery/metadata tool, one schema tool, and one core execution tool. No redundant or missing tools.
The tool set covers the full user workflow: understanding the service capabilities, obtaining the required schema, and executing the verification. For the stated domain of Israeli company verification, there are no obvious gaps.
describe_serviceDescribe Israel Business IntelligenceAFree service capabilities, pricing, evidence scope, and limitations.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the scope of returned information but does not describe any further behavioral traits such as output format or response structure. There is no contradiction with the 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 very short and front-loads the key dimensions: capabilities, pricing, evidence scope, and limitations. It is economical and understandable, though it is a noun phrase rather than a complete sentence, which slightly reduces structural completeness.
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 no-parameter, read-only informational tool, the description covers the main things an agent needs to know before calling it. The lack of an output schema is acceptable because the description sufficiently scopes what the tool addresses.
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 tool has zero parameters, so there is nothing for the description to explain. The empty input schema is unambiguous, and the description correctly focuses on the tool's informational content rather than parameters.
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 title 'Describe Israel Business Intelligence' supplies the verb and resource, and the description lists the specific content areas: capabilities, pricing, evidence scope, and limitations. It is clear enough for an agent to understand the tool's role, though it does not explicitly contrast itself with get_schema or verify_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 implies this tool is used when an agent needs an overview of the service, including its capabilities and limitations. However, it gives no explicit guidance about when to prefer describe_service over get_schema or verify_company, leaving usage to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_schemaGet verify_company schemaAFree machine-readable input and output schemas for verify_company.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that the tool provides machine-readable input and output schemas, but offers no additional behavioral context beyond that.
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, direct sentence that states exactly what the tool returns. No redundant elaboration. The only slight weakness is 'Free,' which is not actionable, but it does not meaningfully hurt clarity.
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 no-parameter metadata retrieval tool, the description is largely sufficient: it names the target resource and the kind of schemas returned. It does not explicitly explain how this relates to describe_service, but the core call behavior is clear.
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 tool has zero parameters, so the description carries no parameter documentation burden. The schema is fully self-explanatory with 100% coverage and no required fields.
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 'get' and the resource: input and output schemas for verify_company. However, it does not distinguish itself from the sibling describe_service, so an agent might not know whether get_schema or describe_service is the better metadata endpoint without further investigation.
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 tool should be used to retrieve schemas for calling verify_company, but it does not explicitly state when to choose it over describe_service or mention any exclusions. Usage context is inferable but not spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_companyVerify Israeli companyAVerifies Israeli companies and resolves Israeli company numbers, returning structured public-registry evidence for supplier verification, due diligence, and business intelligence. Costs $0.05 USDC per successful call on Base Mainnet.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | ||
| depth | No | standard | |
| website | No | ||
| language | No | en | |
| company_name | No | ||
| company_number | No | ||
| expected_entity_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds meaningful context beyond that: it discloses a per-call cost of $0.05 USDC and clarifies that successful calls return public-registry evidence, adding operational and financial 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 only two sentences, front-loads the primary action and use cases, and then adds the cost detail. Every sentence carries useful information with no filler.
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?
With no output schema, the description should explain the return structure but only says 'structured public-registry evidence.' It also fails to clarify how to choose among the 7 optional parameters or what qualifies as a successful call, leaving critical invocation details 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?
Schema description coverage is 0% and there are 7 parameters, but the description only hints at 'company numbers' without explaining the roles of city, depth, website, language, company_name, or expected_entity_type. It does not compensate for the missing schema descriptions, so parameter meaning is largely unclear.
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 uses a specific verb and resource: it 'verifies Israeli companies' and 'resolves Israeli company numbers,' which precisely describes the tool's purpose. It also states the output is structured public-registry evidence, distinguishing it from the generic sibling tools describe_service and get_schema.
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 gives clear intended contexts: supplier verification, due diligence, and business intelligence. It does not explicitly mention alternatives or exclusions, but the use cases are concrete enough to guide an agent on when to invoke this tool.
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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