FabTally Valid

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

With no annotations, the description fully discloses the paid nature ($0.002, x402/USDC), the external API source (NHTSA vPIC), and the behavioral difference when x_payment is omitted (returns 402 challenge). This goes well beyond basic tool semantics.

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 focused sentences, front-loaded with the payment warning, then the core function, then the payment behavior. Every sentence adds necessary information with no 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?

Despite no output schema, the description enumerates the decode fields (make, model, year, body class, engine, plant country). The payment flow and VIN limitations are fully specified, making the tool's behavior predictable.

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 already describes both parameters, but the description adds value by explaining how x_payment is forwarded as the X-PAYMENT header and that omitting it yields the price challenge. This clarifies the 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 clearly states 'Decode a Vehicle Identification Number' and specifies the expected outputs (17-char format, check-digit validation, full decode via NHTSA vPIC). This differentiates it from sibling validation tools like validate_email or validate_vat.

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 context on when to use the tool (VIN decoding) and an explicit exclusion ('VIN-only (never plate→owner)'). It also explains the payment workflow. However, it does not explicitly name alternative sibling tools for comparison.

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 fully discloses critical behaviors: the paid x402 challenge flow, the need to pass x_payment to settle, and the absence of per-day API limits. It also states that the tool confirms existence and returns normalized data, leaving no major behavioral surprises.

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 compact and front-loaded with the critical 'PAID' flag and core purpose. Each sentence earns its place, covering payment, input modes, outputs, and the challenge workflow in a dense but readable format.

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 there is no output schema, the description compensates by listing the return values (normalized names, ISO codes, hierarchy, population, coordinates) and explaining the payment prerequisite and challenge behavior. It also mentions no rate limits, providing a complete operational picture.

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 covers all 5 parameters with descriptions, giving a baseline of 3. The description adds semantic value by explaining the OR relationship between 'query' and the structured fields, and clarifies that x_payment is forwarded as the X-PAYMENT header to settle the call. This goes beyond the basic parameter descriptions.

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 'Resolve' with a clear resource ('a place against a bundled open dataset') and enumerates the exact outputs (ISO codes, hierarchy, population, coordinates). It also distinguishes itself from sibling validation tools (VIN, email, IBAN, VAT) by its focus on geographic lookup rather than validation.

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 input modes ('Give {query:...} OR {country, state, city}') and explains the payment workflow, making it obvious when and how to use the tool. It does not explicitly name alternatives or exclusion criteria, but the sibling tool names make it clear this is the only geographic lookup tool.

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 disclosing behavioral traits, and it excels: it states the paid cost ($0.002), the x402 protocol, statelessness, non-PII (address never stored), and no SMTP probing. It also outlines exactly what checks are performed, leaving no ambiguity about side effects or safety. This is exemplary transparency for a tool with zero annotation support.

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, dense paragraph with no filler. The paid nature and purpose are front-loaded, followed by the specific validation features and key behavioral disclaimers. Every sentence contributes unique information, making it appropriately concise and well-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?

For a paid API with an x402 payment flow, the description thoroughly explains invocation, expected behaviors, and data handling. It does not describe the exact return value structure, but the listed validation categories imply the result shape. The absence of error-case details is a minor gap, but overall the description is complete enough for an agent to use the tool 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?

The schema already provides 100% coverage with basic descriptions for both parameters, so the baseline is 3. The tool description adds meaningful context beyond the schema by explaining the x402 challenge-response flow and how the email parameter is used across multiple validation checks. This enhances usability without being redundant, earning a 4.

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 validates an email address with specific checks: syntax, MX-record, disposable domain, and role flag. The verb 'validate' plus the resource 'email' unambiguously distinguishes it from sibling validate_iban and validate_vat tools. The enumerated checks go beyond a generic validation tool, making the purpose specific and actionable.

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 provides clear context including the payment mechanism (omit x_payment for a challenge, include to settle), which is essential for correct invocation. It does not explicitly name alternatives, but the email-specific purpose and the sibling tool names (validate_iban, validate_vat) make it obvious when to use this tool. No exclusions or alternative conditions are stated, but the usage context is effectively communicated.

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 and does well: it discloses the paid nature ('PAID $0.001 (x402, USDC on Base)'), the offline execution ('Pure-offline'), and the challenge/response behavior when payment is missing. It also previews the returned fields, providing useful behavioral 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 compact and information-dense. It front-loads the payment requirement, then gives a clear list of outputs, and ends with the no-payment behavior. Every sentence serves a purpose, and the title reinforces the key validation and extraction points.

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 validation tool with no output schema, the description adequately explains the return data (length, checksum, country, grouping, bank identifier) and the payment flow. It lacks explicit error-handling/edge-case details, but the core use case is fully covered given the tool's modest complexity.

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% (both 'iban' and 'x_payment' have detailed descriptions), so the baseline is 3. The description adds minimal extra semantics beyond the schema: it mentions '{iban}' and 'x402 challenge' but does not materially enhance parameter 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 the verb ('Validate an IBAN') and specifies the resource and expected outputs: ISO 13616 length, mod-97 checksum validation, country, human-formatted grouping, and bank identifier extraction. This distinguishes it from sibling tools like validate_email or validate_vat because it is IBAN-specific and mentions concrete derived data (e.g., Bankleitzahl, UK sort code).

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 it: whenever an IBAN needs validation/parsing. It does not explicitly list alternatives or exclusions, but sibling tools are for different entities (VIN, email, VAT, geo), so the use case is clear. The payment caveat ('Without payment returns the x402 challenge') is a practical guideline for invoking correctly.

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 to rely on, the description carries the full burden. It discloses the paid nature ($0.003, x402 USDC), the live lookup against VIES, the caching behavior (~1h), and the return content (company name/address when available). This goes beyond a simple 'validates' statement, though it doesn't detail error scenarios or exact response format.

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 with the most critical information (paid, flagship). Each sentence adds value: payment mechanic, validation steps, live lookup, caching, and challenge behavior. No fluff.

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 3-parameter tool with no output schema or annotations, the description explains the core behavior: what is validated, what is returned, payment challenge handling, and caching. It lacks an explicit description of the response structure on failure, but overall covers the essential contextual information for a paid VAT validation API.

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, including x_payment's purpose and country_code synonyms. The tool description adds no new parameter semantics beyond what the schema already provides, so 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 tool's purpose: 'Validate an EU/EEA VAT number' with specific actions (format + checksum pre-check and live VIES lookup). It distinguishes itself from sibling tools by focusing on VAT validation and mentions the specific VIES service, making it 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 clearly conveys when to use this tool (for VAT validation) and the condition for payment (without x_payment you get a challenge, with it you get real results). It does not explicitly compare with alternative tools, but the domain is so specific that exclusions are unnecessary, giving clear context.

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