dropcoin-validation

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

No annotations are provided, so the description carries the full burden—and it succeeds. It discloses fuzzy matching, auditable reasons per hit, the need for manual review, the non-legal nature of results, the absence of PEP data, the 15-credit cost, and the API key requirement. This is excellent disclosure for an agent.

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 dense sentences, front-loaded with the core purpose, and every clause adds meaningful information. There is no repetition or 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?

There is no output schema, but the description conveys the essential behavior, key inputs, caveats, and cost. It mentions 'auditable reason per hit' which hints at the return shape, though it does not fully specify the response format. A little more detail about what a clean vs. hit result looks like would round it out, but it is sufficiently complete for an agent to invoke correctly.

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%, so the description must compensate. It does partially: 'person or company' maps to the 'type' parameter, and 'fuzzy name matching' hints at the purpose of 'minScore'. However, it does not explain the minScore range or how the auditable reason relates to the output, leaving the agent to rely on schema constraints.

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 opens with a specific verb ('Screen') and a concrete resource ('person or company against official EU, US (OFAC SDN) and UK (OFSI) sanctions lists'). It clearly differentiates from sibling validation tools by naming the exact domain and data sources.

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 clearly implies when to use this tool (sanctions screening) and explicitly states exclusions: 'a clean result is not legal clearance and covers no PEP data.' It does not name alternative sibling tools, but the siblings are all validation tools, so the context is sufficient to distinguish.

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?

No annotations are provided, so the description carries full behavioral disclosure. It transparently lists the operations performed (syntax, disposable-domain, MX via DNS-over-HTTPS), the return type (verdict), cost (2 credits), and authentication requirement (API key). It does not explicitly state it is non-mutating, but 'validate' and 'returns a verdict' imply a read-only operation.

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 concise sentences, front-loaded with the core action and resource, then adding specific checks and cost/auth requirements. Every sentence adds value; there is no padding 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?

For a simple one-parameter tool with no output schema and no annotations, the description covers the core operation, specific checks, return value, cost, and authentication. It does not describe the verdict format or edge cases, but these are not critical for a basic validation tool and the description is sufficiently complete to guide correct usage.

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 has one parameter 'email' with no description (0% coverage). The description provides the semantic meaning by stating 'Validate an email address' and explaining what checks are performed on it. This compensates for the lack of schema-level parameter documentation, though it does not go into additional detail about formatting.

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 the specific verb 'Validate' with the resource 'email address' and clearly enumerates the validation types: syntax, disposable-domain check, and MX record via DNS-over-HTTPS. It also states the return value (deliverability verdict). This clearly distinguishes it from sibling tools like validate_iban or validate_vatid.

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 clear context for when to use the tool: validating an email address with specific checks. It does not explicitly mention alternatives or when not to use it, but the sibling tools handle other identifiers (IBAN, VAT ID), so the intent is unambiguous. It also notes that it costs 2 credits and requires an API key, which is usage-relevant.

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 discloses the credit cost and API key requirement, but does not describe the return format, potential side effects, or whether the tool is read-only, which are relevant for a validation 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 a single concise sentence that front-loads the primary action ('Validate an IBAN') and includes useful extra context (credits, API key) without unnecessary 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?

The description covers purpose, cost, and auth, which is a good start, but lacks a description of the return value since there is no output schema, and does not explicitly guide the agent on when to choose this over sibling validation tools.

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 provides no description for the 'iban' parameter, and the description only notes that it validates an IBAN and mentions ISO 13616. It offers minimal added meaning beyond the parameter name and length constraints, providing no format examples or additional guidance.

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 validates an IBAN, specifies the ISO 13616 check digit standard, and mentions SEPA membership, which distinguishes it from sibling validation tools like validate_email and validate_vatid.

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?

It clearly indicates this is for IBAN validation and notes that it costs 2 credits and requires an API key, providing usage prerequisites. However, it does not explicitly mention when not to use it or name alternative tools for other entity types.

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 full behavioral disclosure. It reveals important traits: 5 credits, API key requirement, and that invalid formats still incur cost without reaching VIES. This goes beyond minimal expectations, though it does not detail the return format or possible errors.

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 and front-loaded, opening with the core purpose and then adding caveats and requirements. Every sentence provides value, with no redundant or filler content.

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 validation tool, the description covers purpose, cost, prerequisites, and invalid-format behavior. It lacks an explicit mention of the return value structure, but the 'got an answer' phrase hints at it, and the lack of output schema makes this acceptable.

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 description identifies 'vatId' as an EU VAT ID, providing some meaning beyond the raw schema. However, it does not specify the expected format (e.g., country code + digits) or provide examples, leaving a gap since schema description coverage is 0%.

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 validates EU VAT IDs against the live VIES registry, using a specific verb and resource. It distinguishes itself from the sibling tool 'validate_vatid_format' by emphasizing the live registry check, making the purpose unambiguous.

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 clear context on when to use the tool: for live VIES validation. It also implies that format-only checks may not need this tool, but it does not explicitly name alternatives or exclusions. The mention of cost and API key adds practical 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. It discloses that it is free, syntax-only (no registry lookup), rate-limited per IP, and requires no API key. While it does not describe the response format or exact rate limits, the disclosed traits are significantly helpful for an AI agent.

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-loading the core purpose and adding key context. Every phrase earns its place, with no redundant wording.

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 with no output schema, the description covers the essential context: purpose, limitations, rate limit, auth-free access, and an alternative. It omits what the return value looks like, but for a validation tool this is often implied. Overall, the description is sufficient for safe selection and 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 schema has one parameter (vatId) with min/max lengths but no description. The tool description does not explicitly explain the parameter, though 'EU VAT-ID' in the description clarifies the expected domain. The description adds some context but does not fully compensate for the 0% schema description coverage.

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 a specific verb ('check') and resource ('EU VAT-ID format'), with scope: syntax only, no registry lookup. It distinguishes this tool from the paid validate_vatid tool, which performs live VIES checks, ensuring no confusion with sibling tools.

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 when to use this tool (for format checks) and when to use the alternative (paid validate_vatid for live VIES registry checks). Also notes rate limiting and lack of API key requirement, providing clear context for selection.

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 the full burden of behavioral disclosure. It importantly discloses cost (150 credits), the API key requirement, the composite verdict/check-log return, and the exclusion of commercial-register checks. This is strong for a non-annotated tool, though it does not elaborate on error handling or what makes a result 'inconclusive'.

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 dense sentences that front-load the core purpose and efficiently pack in the checks, output format, input requirements, exclusions, and cost/auth prerequisites. Every phrase earns its place with no redundancy or 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?

For a multi-source verification tool with no output schema, the description covers the return contract (verdict + check log), input preconditions, exclusions, and pricing/auth. It could go further in documenting parameter semantics and explicit alternatives, but overall it provides sufficient context for an agent to decide on and invoke 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 description coverage is 0%, so the description must compensate. It clarifies that name, vatId, and lei are the identifier alternatives, and it hints at iban's role via 'IBAN checksum and country consistency'. However, it leaves the 'country' parameter and its relationship to IBAN ambiguous, and does not state whether iban/country are optional or required in certain combinations.

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 ('Verify a business partner'), enumerates the underlying checks (EU VAT via VIES, LEI via GLEIF, IBAN checksum/country consistency), and specifies the output format ('one verdict (pass|fail|inconclusive) with an auditable check log'). This specific verb+resource+scope combination distinguishes it from sibling single-purpose validators like validate_vatid and validate_iban.

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 an explicit input precondition ('Provide at least one of name, vatId, lei') and a clear exclusion ('Does not include commercial-register existence checks'). While it does not explicitly name alternative tools, the 'one call' phrasing and combination of checks clearly imply when it should be used instead of individual validators.

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