Qiniso

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

Discloses that it formats (read-only operation) with example output. Annotations already indicate readOnlyHint=true, but description adds concrete behavior.

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, no unnecessary words. Straight to the point with example.

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 formatting tool with 3 parameters and no output schema, description covers purpose, usage, and example 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 already covers all parameters with descriptions. Description adds example but no new semantic detail beyond 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?

Description clearly states 'format a money amount' with locale and currency, and provides an example. Distinguishes from sibling validation 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 says when to use (before showing in price/invoice/email) and gives an example. No exclusion needed due to sibling context.

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?

The description adds behavioral context beyond the readOnlyHint annotation, such as supporting ~200 countries, defaulting to GB, and allowing subdivision narrowing. It does not contradict 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 two sentences, front-loaded with purpose, and every word adds value. It is 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?

The description effectively covers input details and use cases, but lacks explicit mention of the return value (e.g., boolean) or error handling. However, it is sufficient for a simple lookup 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?

While input schemas have 100% coverage, the description adds meaning by providing examples (e.g., ISO codes like GB, US) and explaining default values for country and subdivision, which goes 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 the tool checks if a date is a public/bank holiday, specifically for computing business-day deadlines. It includes supported country codes and default behavior, distinguishing it from siblings like 'next_holiday'.

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 states when to use the tool (e.g., for business-day deadlines, delivery SLAs, next working day) but does not mention when not to use it or contrast with alternatives like 'next_holiday'.

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?

Description adds value beyond annotations: default today behavior, country/subdivision support scope. Annotations already declare readOnlyHint=true, so no contradiction. Disclosure is adequate for a read-only 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?

Two concise sentences with no redundant words. Purpose and key details are front-loaded. Every sentence earns its place.

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?

Lacks description of return format or output structure. Since there is no output schema, the agent is left to infer what 'next holiday' means (date? name?). Adequate for simple tool but incomplete for full certainty.

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%, but description enriches parameter meanings with examples (GB, US) and explains subdivision (narrows to region, e.g., UK nations or US states). This adds practical value beyond schema definitions.

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?

Description clearly states 'find the next public/bank holiday' with specific verb and resource. Provides examples of country codes and distinguishes purpose from 'is_holiday' by focusing on 'next' and default today.

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?

Explicit 'USE THIS' directive and example usage (find next working day) guide the agent. Does not explicitly exclude alternatives like 'is_holiday', but the context of 'next' vs checking a specific date is implied.

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?

Annotations declare readOnlyHint=true, confirming safe read operation. Description adds that it returns a confidence flag and targets UK/US addresses, providing useful behavioral context beyond 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?

Single sentence with em-dash separation, front-loaded with 'USE THIS', no wasted words. Highly efficient.

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 low complexity (one parameter, no output schema), the description covers purpose, input, output, and confidence flag fully. No gaps.

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 covers 100% of parameters, but the description adds meaning: it specifies the address must be free-text and UK/US, and lists the extracted fields, enhancing understanding 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 the tool extracts structured address components (country, postcode, city, state) from free-text UK/US addresses. It is distinct from sibling validation 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 recommends use for onboarding, KYC/fraud checks, and address storage, and suggests it over manual string splitting. No explicit when-not to use, but context is clear.

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?

The description adds behavioral context beyond the 'readOnlyHint' annotation by stating it returns 'valid:false' for impossible dates and emphasizes locale handling. This informs the agent of edge cases without contradicting the safe read nature.

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 with no wasted words. It front-loads the action ('USE THIS') and efficiently communicates key information.

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 complexity of date parsing and the presence of sibling validators, the description covers the essential functional behavior and return value (valid:false). The lack of an output schema is partly compensated by describing a key output field.

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 baseline is 3. The description adds value by explaining the ambiguity problem and locale significance, but does not provide additional syntactic details 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 the tool interprets human-written dates into ISO 8601, with specific examples of ambiguous numeric dates. It distinguishes itself from sibling tools, which are mostly validators and formatters, by being the dedicated date parser.

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 advises using this tool for date interpretation, especially for ambiguous dates. While it does not provide when-not-to-use or alternatives, the sibling list (all validation/formatting) makes the context clear, and the 'USE THIS' directive strongly guides 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?

The description adds significant behavioral context beyond the readOnlyHint annotation: it explains that for GB it handles historical/temporary changes, for US it returns 0 without a state code or the state base rate, and that the result is date-sensitive. This helps an agent understand the tool's output without calling it.

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, consisting of three sentences that are front-loaded with the imperative usage instruction, followed by clear explanations for GB and US, and a final reminder. Every sentence adds value, and there is no unnecessary information.

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 adequately explains return values for both countries and the importance of the date. It could be more precise about the output format (e.g., decimal vs percentage), but overall it provides enough context for proper usage. The sibling tools do not overlap, so no missing guidance.

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 has 100% coverage with descriptions for each parameter, but the tool description enhances semantic understanding by linking the 'date' parameter to the invoice date for GB and clarifying the 'state' parameter's role in US sales tax. This provides context that is not in the schema alone.

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: provide VAT or sales tax rates for invoice/quote calculations. It specifies that it returns UK standard VAT rate for GB and US state sales tax rates, and emphasizes date-sensitivity, distinguishing it from guessing rates. The purpose is unambiguous and well-defined.

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 instructs to use this tool before calculating taxes and to never rely on memory due to date-sensitivity. It also says to always pass the invoice date for GB. While it does not list alternatives, there are no sibling tools with similar functionality, so the guidance is clear and adequate.

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?

Annotations already declare readOnlyHint=true, so no contradiction. The description adds specific behavioral details (Verhoeff check digit, leading-digit rule) and clarifies it only validates structure, not existence. This enriches the annotation's safety profile.

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 purpose. Every sentence adds value: first states action, second adds algorithm details and limitations. 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 simple format validation tool with one parameter and no output schema, the description covers all necessary aspects: what it does, on what input, how (algorithm), and what it doesn't do. No missing information.

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 has 100% coverage for the single parameter, describing it as a 12-digit number with spaces ignored. The description adds meaning about the internal validation rules (Verhoeff, leading-digit), which informs the agent about what constitutes a valid input 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 it verifies the format and checksum of an Indian Aadhaar number, using specific algorithms (Verhoeff, leading-digit rule). It distinguishes from siblings by emphasizing it does not look up the number, making it unambiguous among many validation 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?

The description starts with 'USE THIS', giving clear directive. It explains what it validates and explicitly states what it does NOT do (lookup), providing implicit guidance against misuse. However, it does not mention when to use alternative tools, but the sibling context is clear.

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?

Annotations already declare readOnlyHint=true. Description adds that it validates structure only and mentions specific checks (mod-97, born-from-2000 rule), which is consistent but not beyond what annotations imply.

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 two sentences, front-loaded with 'USE THIS', and covers key points without fluff. Could be slightly more concise by merging the first two sentences.

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 read-only validation tool with one parameter and no output schema, the description fully covers what the tool does, its limitations, and specific checks.

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 the single parameter (nrn) with high coverage. Description does not add new meaning beyond the schema's description.

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?

Description clearly states the tool validates a Belgian National Register Number, specifying the checks performed (11-digit form, mod-97 check, born-from-2000 rule) and that it validates structure only. Distinct from sibling validators.

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 use this tool before relying on a Belgian NRN. While it does not explicitly state when not to use, the context of sibling tools (many country-specific validators) implies it is only for Belgian NRNs.

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?

Annotations already declare readOnlyHint=true, and the description adds that it 'validates structure only,' clarifying it does not perform external database checks. This adds behavioral context beyond annotations and does not contradict them.

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 concise sentences, front-loaded with a clear instruction. Every sentence adds value: target audience, validation actions, and scope. 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?

The description covers purpose and behavior but does not specify output format (e.g., boolean, object). With no output schema, agents may need to infer the return value. Adequate but not fully complete for a validation 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 schema covers the single parameter with a description ('10-digit EGN, spaces ignored'), and the description reinforces the 10-digit and check digit aspects. With 100% schema coverage, the description adds no new parameter semantics beyond reinforcement.

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 verifies a Bulgarian EGN, specifies the checks (10-digit form, weighted mod-11 check digit), and distinguishes it from many sibling validators by naming the exact identifier type. The verb 'verify' and resource 'Bulgarian EGN' are 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 instruction 'USE THIS to verify a Bulgarian EGN before relying on it' gives context but does not explicitly state when not to use it or mention alternatives. Sibling tools imply this is only for Bulgarian EGN, but no direct guidance is provided.

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?

The description fully discloses behavior: it checks format and checksum only, does not confirm issuance. This complements the readOnlyHint annotation well, and there is no contradiction. The agent knows exactly what the tool does and does not do.

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 with no wasted words. It is front-loaded with the imperative 'USE THIS', making the purpose immediately clear. Every sentence provides necessary information.

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 low complexity (single parameter, validation task), the description is complete. It covers what the tool checks, what it does not, and provides usage guidance. No output schema is needed for this tool type, and the description explains the return implicitly (boolean result).

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 description does not need to add much. It mentions 'spaces/dots ignored' and '8- or 9-digit', but these are already in the schema's description. No additional semantic value is added 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 the tool validates a Dutch BSN by checking digit length (8–9 digits) and the '11-test' checksum. It specifies the exact resource and purpose, distinguishing it from sibling tools that validate other identifiers.

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 begins with 'USE THIS to verify a Dutch BSN before relying on it', providing an explicit usage context. It also clarifies the tool only validates structure, not issuance, which sets expectations. However, it does not explicitly mention when not to use it or alternatives, though the sibling list makes context clear.

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?

Annotations provide readOnlyHint=true. The description adds that it checks specific address formats and returns the address type and network, and explains what a bad checksum indicates. It provides useful behavioral context beyond the annotation.

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 front-load the usage instruction and provide necessary detail. Every sentence is informative with 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?

Given no output schema, the description mentions return values (address type and network) and explains the implication of a bad checksum. For a simple validation tool with one parameter, the context is sufficiently complete.

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% for the single parameter. The description reiterates the address formats but does not add new semantic detail beyond the schema's description. Baseline 3 is appropriate as the schema already documents the parameter well.

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 a Bitcoin address before sending funds, specifying the formats checked (Base58Check, Bech32/Bech32m) and return values. It distinguishes from sibling validate tools by being Bitcoin-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 explicitly says 'USE THIS to verify a Bitcoin address before sending funds or storing it — do not assume it is valid.' It provides clear context but does not mention when not to use it or alternatives, though the name and sibling list make the domain clear.

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?

Annotations indicate readOnlyHint=true, and the description adds value by detailing that the tool does not verify real cards, active status, or funds. No contradiction with 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 concise (two sentences) with no fluff. The first sentence provides an imperative usage guideline, and the second lists capabilities and limitations. Front-loaded and efficient.

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 input schema and lack of output schema, the description is complete. It covers what the tool does, what it checks, and its limitations. No additional context is needed.

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% for the single parameter, and the description adds meaning beyond the schema by explaining that spaces and dashes are ignored and how the card number is processed (Luhn, brand, length). This exceeds the baseline 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 clearly states that the tool checks the structure of a payment card number, including Luhn checksum, brand detection from BIN, and length. It uses specific verbs and distinguishes it from other validators by focusing on payment cards.

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 instructs when to use the tool ('USE THIS to check a payment card number's structure before using it') and clarifies what it does not check (real, active, funds). This provides clear guidance for the agent.

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?

Disclosure that it 'validates structure only' sets appropriate expectations beyond the readOnlyHint annotation, clarifying no database or identity verification occurs.

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 fluff, front-loaded with imperative 'USE THIS', quickly conveying purpose and limitations.

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 with no output schema needed, the description fully covers what it does, its scope, and constraints.

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 already fully covers the parameter (100% coverage), and the tool description only echoes the format details without adding new 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?

Description clearly states the tool validates Swiss AHV numbers, specifies the format (13-digit starting 756) and check digit validation, and distinguishes from sibling validation tools for other identifiers.

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 says 'USE THIS to verify... before relying on it', providing clear usage context. Implicitly excludes other identifier types via sibling tools, but no explicit when-not-to-use.

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?

Annotations indicate readOnlyHint=true, consistent with a validation tool. The description transparently states it validates structure only, not registration, and specifies the check character may be 'X'. No contradictions.

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 concise sentences, front-loaded with the most important instruction ('USE THIS'), no unnecessary words. Every sentence serves a purpose.

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 validation tool with no output schema, the description adequately covers behavior (structure-only validation), input format, and check character. No gaps.

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 a good parameter description. The description adds value by explaining the check character and format, beyond what the schema provides. Slightly higher than baseline 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 clearly states the tool verifies Chinese Resident Identity Card numbers, specifies the 18-character format with ISO 7064 MOD 11-2 check digit, and distinguishes from other validation tools. It provides a specific verb ('verify') and resource ('China RIC number').

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 instructs 'USE THIS' and warns against guessing the check character, providing clear usage context. However, it does not mention when not to use it or suggest alternative tools among the many sibling validators.

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?

Beyond the readOnlyHint annotation, the description adds that the tool checks mod-11 check digits, which informs the agent of the validation logic. No contradictions with 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?

Two sentences with no fluff, front-loaded with the core purpose and usage guidance. Every sentence is useful.

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 read-only validation tool with no output schema, the description provides complete context: what it does, when to use it, and what it checks. No gaps.

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 schema already describes the parameter. The description doesn't add additional semantic detail beyond the validation logic, which is about behavior rather than the parameter itself.

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 verifies a Brazilian CNPJ and checks the two mod-11 check digits, distinguishing it from sibling validation tools by specifying the exact identifier type and purpose.

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 says 'USE THIS...instead of trusting 14 digits' and 'Call this for onboarding Brazilian businesses', providing clear context. Lacks explicit when-not-to-use, but sibling tools are all different validations, making the usage context unambiguous.

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?

Annotations already set readOnlyHint=true. The description adds valuable behavioral context: it only validates structure (format and check character), and does not confirm registration. This goes beyond the annotation and provides full 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 two sentences with no wasted words. It opens with an imperative 'USE THIS', front-loading the action. Every sentence adds unique value.

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 simplicity (one parameter, no output schema), the description is mostly complete. However, it does not describe the return value (e.g., boolean or validation details), which an agent might need to interpret results.

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 100% and already describes the code parameter well (16-character, spaces ignored, case-insensitive). The description reinforces but adds no new semantic detail 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 explicitly states the tool verifies an Italian Codice Fiscale, covering format and check character, and distinguishes from registration lookup. The verb 'verify' and resource 'Codice Fiscale' are specific, and the exclusion of registration confirmation clarifies its scope.

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 advises when to use ('before relying on it') and what not to do ('do not guess the final check letter'). It also explicitly states what the tool does not do ('does NOT confirm registration'), providing clear usage boundaries.

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?

Annotations only provide readOnlyHint. Description adds that it checks mod-11 check digits and rejects all-identical sentinels, which is behavioral information beyond annotations. No contradictions.

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, no superfluous words. Front-loaded with 'USE THIS'. Efficient and to the point.

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 tool (one parameter, no output schema), the description covers purpose, usage, and behavioral details. No missing information 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 coverage is 100% with a clear description of the 'cpf' parameter. The description does not add significant additional meaning beyond the schema, 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?

Clearly states the tool validates a Brazilian CPF (individual taxpayer ID), specifies it checks mod-11 check digits and rejects all-identical sentinels, and mentions use case (KYC/onboarding). Distinguishes from sibling validators by targeting Brazilian CPF.

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 says 'USE THIS to verify a Brazilian CPF' and 'Call this for KYC/onboarding of Brazilian individuals'. Provides context for when to use, though does not explicitly mention when not to use or list alternatives.

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?

Annotations declare readOnlyHint=true, and the description adds behavioral context beyond that: it checks the mod-10 check digit and returns the expected digit when it fails. This is consistent and informative.

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 with no waste. It is front-loaded with the imperative 'USE THIS' and clearly communicates the core function and behavior.

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 explains the check digit verification and what happens on failure, but does not specify the return format when validation succeeds (e.g., boolean true). For a tool with no output schema, this detail would enhance completeness.

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 100% (providing example and type). The tool description does not add extra meaning to the parameter beyond the schema, 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: to verify a CUSIP by checking its check digit. It specifies the resource (CUSIP) and action (verify), and distinguishes it from sibling tools by its specific focus on North American securities identifiers.

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 (when you need to verify a CUSIP) but does not explicitly state when not to use or mention alternatives. The sibling tools are all different validators, so the context is clear, but explicit guidance is missing.

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?

Annotations indicate readOnlyHint=true; description adds that it validates structure only and explains the mod-11 rule and pre-1954 numbers, providing context beyond 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?

Two concise sentences, front-loaded with 'USE THIS'. No superfluous information.

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, no-output-schema tool, the description is fully adequate, covering purpose, algorithm, and limitations.

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 already covers the parameter (10-digit, slash ignored). Description adds meaning by specifying CZ/SK and the validation rule (mod-11), enhancing the schema info.

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 verb (validate), resource (CZ/SK rodné číslo), and specific checks (mod-11, structure). Distinguishes itself from sibling validation 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 advises using before relying on the number. Provides context on what it checks and limitations (structure only), but does not mention when not to use or alternatives.

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?

The description fully discloses behavioral traits: checks only structure/check digit, ignores spaces/slashes, does not confirm registration. Annotations confirm readOnlyHint=true, and there is no contradiction.

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, front-loaded with imperative 'USE THIS', no unnecessary words. Every sentence adds value: purpose, scope, limitation.

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 validation tool with one parameter and no output schema, the description covers all essential aspects: what it validates, how it validates, and its limitation (no registration check). No gaps.

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 'id' has a clear schema description. The tool description adds behavioral context (structure-only validation) but does not enhance parameter semantics beyond what the schema already provides.

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 validates a German tax ID (Steuer-Identifikationsnummer) using ISO 7064 check digit. It clearly distinguishes from sibling validators by specifying the exact ID type and scope (structure only, not registration).

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 advises using the tool before relying on a tax ID and clarifies it does not confirm registration. However, it does not explicitly name alternative tools for registration verification or provide when-not-to-use scenarios.

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?

Annotations already provide readOnlyHint=true, so the description adds value by explaining the algorithm (mod-23 check) and the output (DNI or NIE type). It discloses the behavioral trait of performing validation without side effects.

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, directly stating purpose and behavior. No wasted words, front-loaded with the imperative. Highly efficient.

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 validation tool with one parameter and readOnly annotations, the description covers purpose, algorithm, and output type. It could specify the return format more explicitly, but is sufficient for an AI agent.

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 100%, with a clear description of the 'id' parameter. The description adds minor context about the control letter but does not significantly enhance the schema's existing documentation.

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 verifies Spanish DNI or NIE, checks the mod-23 control letter, and returns whether it is DNI or NIE. It uses an imperative 'USE THIS' and distinguishes from sibling validators for other identifiers.

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 says when to use: 'before relying on it' and advises against guessing the control letter. However, it does not explicitly contrast with sibling tools or state when not to use it.

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?

Annotations already declare readOnlyHint=true. The description adds that it returns the TLD and its known status, and catches invalid labels and made-up TLDs, which provides useful behavioral context beyond the annotation.

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 convey the purpose, usage, and return value without any fluff. Every word earns its place.

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 single-parameter input, the presence of annotations, and no output schema, the description is sufficient. It covers validation behavior and return content, though it could hint at error handling for invalid domains.

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% and the parameter 'domain' is described as 'The domain name, e.g. 'example.com'.' The description adds no extra meaning beyond this example, so it meets baseline but does not excel.

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 domain structure and checks TLD against IANA, distinguishing it from other validation tools for emails, IBANs, etc. It uses a specific verb 'verify' and resource 'domain name'.

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 says 'USE THIS' for domain verification instead of assuming legitimacy, giving clear context. It does not explicitly list when not to use, but the sibling tools are distinct enough.

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?

Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds that it 'validates structure only', clarifying it does not verify actual assignment to a person. This is useful but does not go beyond what annotations already signal; thus a moderate 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 long, front-loaded with 'USE THIS', and every sentence adds value. No wasted words; it is concise and easy to read.

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 parameter, no output schema, read-only annotation), the description is sufficient. It explains what the tool does and its scope. A small gap: it does not describe the return format, but for a typical validation tool, a boolean or result object is implied.

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 schema already describes the parameter. The description adds minor context ('11-digit', 'spaces ignored', 'two-stage mod-11 check digit'), but these are either redundant with the schema or behavioral details rather than parameter semantics. Baseline 3 is correct.

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 'verify' and the specific resource 'Estonian isikukood (personal identification code)'. It explicitly distinguishes this validation tool from the many sibling validation tools for other countries, effectively avoiding ambiguity as the tool name alone could be misread.

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 says 'USE THIS to verify an Estonian isikukood... before relying on it', which provides clear context for when to use it. It does not explicitly state when not to use it or mention alternatives, but the sibling tools are all for different identifiers, so the purpose is well-scoped.

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?

Annotations already declare readOnlyHint=true, and description adds meaningful behavioral context: validates syntax and TLD, flags made-up TLDs, and explicitly states deliverability is not checked. No contradictions.

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 sentences: first gives use-case, second describes what it does, third clarifies limitation. Front-loaded, no redundant information, every sentence earns its place.

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 one parameter, no output schema, and readOnly annotation, the description adequately covers validation scope. However, it does not hint at the output format (e.g., boolean or error), which could be inferred but is not explicit.

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 a clear description for the email parameter. The tool description reinforces the validation purpose but does not add new semantic detail beyond what the schema provides. 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?

Description clearly specifies the verb 'check' and resource 'email address's syntax AND domain TLD', distinguishes from trusting raw input, and defines scope with RFC reference. Sibling tools like validate_domain exist but email validation inherently covers domain/TLD, and description's use-case guidance ('before saving or sending') differentiates it.

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 ('before saving or sending') and when not to rely on it ('Does NOT check deliverability'). However, it does not suggest alternative tools for deliverability checking or clarify relationship to sibling validate_domain/validate_tld.

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?

Annotations provide readOnlyHint=true, so the tool is safe. The description adds that it validates format and checksum, returns the correctly-checksummed form, and warns that errors lead to lost funds. No contradictions.

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 concise—three sentences with no fluff. It front-loads the urgency and purpose, then provides key details and consequences. Every sentence earns its place.

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 input (one string) and no output schema, the description is fully complete. It covers purpose, usage, what it validates, and the consequence of incorrect addresses. The agent has all needed information.

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% (only one param, well-described). The description adds value by explaining the EIP-55 checksum validation and the return of the correctly-checksummed form, which goes beyond the schema's simple type description.

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 Ethereum address format and EIP-55 checksum, with a specific verb ('verify'/'validate') and resource. It distinguishes itself from the many other validation tools by explicitly focusing on ETH addresses.

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 strong guidance: 'USE THIS to verify an Ethereum address before sending funds or storing it' and warns about trusting raw strings. It does not explicitly mention when not to use it, but the context makes it clear this is for ETH addresses only.

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?

Adds value beyond readOnlyHint by stating it validates structure only and ignores spaces. No contradictions.

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, front-loaded with 'USE THIS', every sentence provides critical information.

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?

Fully describes the tool's functionality, limitations, and parameter behavior for a simple validation tool with no output schema.

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 has full coverage, but description adds that spaces are ignored, which is extra useful detail.

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 tool validates Norwegian fødselsnummer, checks 11-digit form and mod-11 control digits, and distinguishes from sibling validation tools by specifying what it does and does not do.

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 says to use before relying on the number, and notes it does not confirm registration. Provides clear context but does not explicitly mention when to use alternatives.

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?

Discloses structural validation only, Corsica support, and mod-97 key check. Annotations already declare readOnlyHint=true, and the description adds specific behavioral context without contradiction.

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, front-loaded with 'USE THIS', 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 simple validation tool with one parameter and no output schema, the description fully covers purpose, usage, what is validated, and limitations.

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 has 100% coverage with parameter description. The tool description adds extra meaning by explaining NIR format and caution about not guessing the key, beyond schema details.

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 tool verifies a French social-security number (NIR) with specific details (13-digit body, Corsica handling, mod-97 key) and distinguishes it from sibling validation tools by being FR-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?

Directly says 'USE THIS to verify ... before relying on it — do not guess the key', providing clear when-to-use guidance. Does not explicitly mention alternatives, but the context is sufficient.

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?

Annotations include readOnlyHint=true, and the description adds that it validates structure only (not registration), which is valuable behavioral context beyond what annotations provide.

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 short sentences with no wasted words. The imperative 'USE THIS' is front-loaded for quick agent scanning.

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 validation tool with one parameter and no output schema, the description covers what it does, what it returns, and its limitations. No further details needed.

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 100%, and the description adds meaning by explaining the GS1 mod-10 check digit and country return, which is not in 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 it verifies a GLN (Global Location Number) and specifies what it checks (check digit) and returns (country). It distinguishes itself from sibling validation tools by focusing on a specific identifier type.

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 begins with 'USE THIS to verify a GLN before relying on it,' providing explicit guidance on when to use. It also mentions what it does not do ('does not confirm the location is registered'), but does not name specific alternatives.

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?

Beyond the readOnlyHint annotation, description details what the tool checks (GS1 mod-10 check digit, returns barcode type and issuing country), and explicitly states it does not verify product registration. This fully informs an agent of behavior and limits.

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 sentences with no wasted words. First sentence is an imperative that quickly conveys the tool's purpose. Information is front-loaded and structured logically.

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?

No output schema exists, but the description compensates by explaining what the tool returns (barcode type and issuing country with examples). Input and limitations are well covered. Complete for a simple validation 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 coverage is 100% and the schema description already explains the input parameter. The tool description does not add additional semantics beyond the schema, so 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?

Description clearly states verb 'verify' and resource 'product barcode', specifies supported formats (EAN-8, UPC-A, etc.), and distinguishes from 'guessing check digit'. This sets it apart from sibling validation tools that target other identifiers.

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 says 'USE THIS to verify a product barcode... before trusting it', which tells when to use. Also provides a key limitation: 'Validates structure only — it does NOT confirm the barcode maps to a real, registered product.' Not explicitly contrasted with sibling tools, but context is clear.

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?

Annotations provide readOnlyHint=true, and description adds that the tool validates structure only, not actual person existence. This is useful context beyond annotations, though no mention of edge cases or error handling.

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, no redundant information. Directly to the point with clear instructions.

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 validation tool with one parameter and no output schema, the description fully covers what the tool does and its limitations. No gaps.

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 has 100% coverage for the single parameter 'hetu' with a description. The tool description adds an example format and case-insensitivity note, but these are already implied by the schema description ('case-insensitive' is explicit). 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 verifies a Finnish HETU (personal identity code) and validates its structure. It uses specific verb+resource ('verify a Finnish henkilötunnus') and distinguishes from sibling validation tools by being country/format-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?

Explicitly instructs to use this tool before relying on a HETU and warns not to guess the check character. This provides clear when-to-use guidance and an alternative (not guessing).

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?

The description adds value beyond the readOnlyHint annotation by detailing what is checked (format and check digit) and explicitly stating limitations ('Validates structure only'), making the tool's behavior clear.

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, efficient and front-loaded with the imperative use instruction. Every sentence contributes value, though the structure could be slightly more formal.

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 and the schema's coverage, the description is mostly complete. However, it does not mention the return type or error behavior, which would be helpful for a validation tool without an output schema.

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 100%, so baseline is 3. The description reinforces the parameter's purpose by mentioning the check digit algorithm, but does not add substantial new meaning beyond what the schema already provides.

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 it verifies a Croatian OIB, specifies '11-digit form' and 'ISO 7064 MOD 11,10 check digit', and explicitly says 'Validates structure only' which distinguishes it from other validation tools that may verify existence or other properties.

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?

Commands 'USE THIS to verify a Croatian OIB before relying on it', providing clear context for when to use. Does not explicitly state when not to use or mention alternatives, but the sibling tool list makes it obvious this is for Croatian OIB specifically.

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?

Annotations already indicate readOnlyHint=true. The description adds behavioral details: it checks country-specific length and checksum, ignores spaces, and returns specific fields. No contradiction, but it could mention error handling or invalid input behavior.

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 short (60 words), front-loaded with the imperative action, and every sentence adds value. 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?

No output schema, but the description explains what the tool returns. Covers validation criteria, input format (spaces ignored), and usage context. Complete for a simple validation 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?

Input schema covers the parameter thoroughly (100% coverage). The description adds the useful detail that spaces are ignored, slightly extending schema 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 clearly states the tool validates IBANs, specifies the checks performed (country, length, checksum), and lists return values (country, check digits, BBAN). It distinguishes from guessing and is specific among sibling validation 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 says to use whenever a user supplies a bank account for payment, payout, or invoice. Provides clear context but does not explicitly state when not to use, though the specificity of the tool makes alternatives obvious.

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?

Annotations already mark readOnlyHint=true. The description adds beyond that by clarifying the tool only validates the number format and does not check device existence, providing essential scope limits.

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 focused sentences: a usage guideline and a behavioral summary. No redundant words, all information earns its place.

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 validation tool with one parameter, the description adequately covers purpose, usage, and output. Missing output format details, but the mention of returning TAC is sufficient for an agent.

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?

Input schema covers the IMEI parameter description. The description adds value by explaining that it handles spaces/dashes and distinguishes IMEI from IMEISV, plus mentions the validation logic (Luhn) and output (TAC).

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 IMEI by checking the Luhn check digit and returning the TAC. It distinguishes from verifying device status, making its purpose specific and 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?

Describes when to use (before relying on an IMEI) and explicitly lists what it does NOT do (check real device, active, blocklisted). While no alternative sibling is named, the context is clear enough.

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?

Annotations indicate readOnlyHint=true, consistent with validation. The description adds strict checking details (rejects leading zeros, out-of-range octets, supports IPv6 compression). No contradiction.

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, front-loaded with actionable instruction ('USE THIS'), 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?

Describes validation details but lacks explicit return format (e.g., object with version and validity) and error handling. Without output schema, this is a gap for complete understanding.

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 covers 100% of parameters with a description for 'ip'. The tool description adds context about validation strictness but does not add new semantic meaning beyond the schema's basic type.

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 verifies IP addresses, specifies IPv4 and IPv6 formats, and mentions RFC compliance. It distinguishes itself from sibling tools that validate other entities like email, phone, 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?

It explicitly says 'USE THIS to verify an IP address before relying on it' and warns against assuming validity. However, it does not mention when not to use it or provide alternatives, though siblings are for unrelated 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?

Annotations declare readOnlyHint=true, consistent with verification. The description goes beyond annotations by detailing the validation process (prefix and check digit checks) and the behavior on failure (returns expected check digit). No contradictions.

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, front-loaded with imperative instruction, each sentence adds value. 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 simple validation tool with good annotations and schema coverage, the description is complete. It explains what it does, what it checks, and what it returns on failure. No output schema needed.

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 100% and includes the note about ignoring hyphens/spaces. The description adds context about the validation logic but does not significantly enhance parameter semantics beyond the schema. 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 verifies ISBN-13 book identifiers, specifying the checks performed (978/979 prefix, mod-10 check digit) and the return value. This distinguishes it from siblings like validate_isbn10 and other validation 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?

The description explicitly says 'USE THIS to verify an ISBN-13...', providing clear guidance on when to use it. It implicitly excludes ISBN-10 by naming validate_isbn10 as a sibling, but does not explicitly state alternatives or when not to use it.

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?

Annotations provide readOnlyHint=true (consistent). Description adds details about mod-11 check digit and 'X' possibility, giving deeper behavioral insight. Could mention return type but still strong.

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, front-loaded with 'USE THIS'. Every word adds value. 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 simple read-only validation tool with one parameter, description covers purpose, algorithm, and guidance. No gaps given schema and annotations.

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 parameter (100% coverage) and notes hyphens/spaces ignored. Description adds algorithm detail but no new syntax beyond schema. 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?

Description explicitly states it verifies ISBN-10, differentiates from 13-digit ISBNs via validate_isbn sibling. Verb 'verify' + resource 'ISBN-10' 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?

Provides explicit instruction: 'USE THIS...instead of trusting 10 characters' and direct alternative for 13-digit ISBNs ('use validate_isbn'). Clear when to use and when not.

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?

Description adds beyond annotations: it details the validation steps (format and check digit) and output (country code). Annotations only have readOnlyHint, so description fully covers behavioral traits.

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 impactful sentences, front-loaded with imperative, no unnecessary words. Excellent conciseness.

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 validation tool with no output schema, the description adequately covers purpose and behavior. Could mention output type explicitly but not a major gap.

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 has 100% coverage with description and example for the single parameter. Description reiterates the 12-character nature, adding marginal value.

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 verifies an ISIN by checking format and Luhn digit, and returns country code. It distinguishes from the many sibling validation tools by focusing on ISIN specifically.

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 explicit instruction 'USE THIS to verify an ISIN before relying on it' and 'Call this when a user supplies a security/instrument identifier' provides clear usage guidance. No when-not-to, but context is sufficient.

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?

Annotations already indicate readOnlyHint=true. The description adds useful behavioral detail: it checks the mod-11 check digit (which may be 'X') and returns the expected digit on failure. This adds value beyond 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?

Two sentences, front-loaded with 'USE THIS', and no wasted words. Every sentence is essential and concise.

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 simplicity of the tool (single parameter, no output schema, read-only), the description is adequate. It explains the core validation logic and what happens on failure. It lacks explicit mention of return value on success, but that is implied.

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 100% for the single parameter. The description does not add additional parameter information beyond what the schema already provides. Baseline 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 verb 'verify' and the resource 'ISSN (serial/journal identifier)'. It is distinct from sibling tools which validate different identifiers.

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 says 'USE THIS to verify an ISSN before relying on it', providing clear context. However, it does not explicitly state when not to use or mention alternatives, though the sibling list makes alternatives obvious.

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?

Adds specific behavioral detail (checks check digits per ISO standards) beyond the readOnlyHint annotation. No contradictions.

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, imperative tone front-loaded with 'USE THIS', no extraneous 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?

Adequately describes the tool's action and input for a simple validation tool; missing explicit output format but not critical given lack of output schema.

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 covers 100% of parameters; description adds a concrete example and reiterates the 20-character format but does not significantly extend semantic meaning.

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 it validates a Legal Entity Identifier (LEI) by checking ISO 17442 / ISO 7064 MOD 97-10 check digits. Distinct from sibling validation tools targeting other identifiers.

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?

Provides explicit instruction to use before relying on an LEI, with a warning not to assume validity. Contextually clear among siblings, though no direct alternatives are named.

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?

Annotations declare readOnlyHint=true, indicating safe read operation. The description adds that validation is structural only and does not check against a live database, providing useful behavioral context beyond 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 two concise sentences, front-loaded with the imperative 'USE THIS'. Every word contributes meaning 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 one parameter, readOnly annotation, and no output schema, the description adequately covers purpose and constraints. It could mention output type (e.g., boolean) for completeness, but is sufficient for this simple 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 has 100% coverage with description for the parameter 'curp'. The tool description adds context about what is validated (format and check digit), which goes beyond the schema's parameter description.

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 tool validates a Mexican CURP, checking the 18-character format and base-37 check digit. It clearly identifies the resource (CURP) and action (verify), distinguishing it from sibling validation 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?

The description instructs to use this tool for verification before relying on a CURP and explicitly warns against guessing the check digit. While it doesn't compare with siblings, the context of many validation tools makes the purpose clear.

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?

Describes the mod-11 check digit algorithm and warns not to assume 9 digits are valid, adding behavioral context beyond the readOnlyHint annotation. No contradictions.

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 efficient sentences with front-loaded usage directive, 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?

Fully covers purpose, usage context, algorithm, and sibling reference for a simple validation tool with one parameter and no output schema.

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 fully documents the single parameter (nif) with description including spaces ignored. The description does not add new parameter-specific meaning beyond what the schema 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?

Clearly states the tool verifies a Portuguese NIF (tax number) using mod-11 check digit, distinguishing it from sibling validate_dni for Spanish tax ID.

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 use before invoicing/onboarding and points to validate_dni for Spanish tax ID, providing clear when-to-use and when-not-to-use 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?

The description aligns with the readOnlyHint annotation and adds specific behavioral details: the check digit algorithm, acceptance of 'X' as check digit, and acceptance of both bare ID and URL. No contradictions; the description enhances transparency beyond 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 two sentences long, front-loaded with a clear use directive, and every word adds value. No unnecessary information, making it highly 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?

While the description explains the validation logic, it does not mention the return value or output format. Given no output schema, an agent might benefit from knowing the response shape (e.g., boolean or validated ID). The low complexity of a simple validation tool keeps the score at a 3.

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 comprehensive description of the 'orcid' parameter with examples. The description adds algorithmic context but does not significantly enhance parameter understanding beyond what the schema offers. With 100% schema coverage, a baseline 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 verifies an ORCID identifier using a specific algorithm (ISO 7064 MOD 11-2), distinguishing it from merely trusting the digit count. It specifies the input formats (bare ID or URL), making the purpose unambiguous among many sibling validation 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?

The description explicitly says 'USE THIS to verify an ORCID researcher identifier instead of trusting 16 digits', providing a clear when-to-use scenario. It does not explicitly exclude other use cases or mention alternatives, but the sibling context implies other tools for different identifiers, earning a 4.

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?

The description adds key behavioral context beyond the readOnlyHint annotation: it checks Luhn digit, validates structure only, and does not confirm registration. This disclosure is valuable for understanding the tool's limitations and safety profile.

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 concise sentences with no wasted words. The first sentence is front-loaded with an imperative usage recommendation, making it easy for an agent to quickly grasp the tool's purpose.

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 validation tool with one parameter, full schema coverage, and no output schema, the description provides all necessary context: what it does, what it does not do, and when to use it. No additional information is needed.

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 fully describes the single parameter with 100% coverage. The description reinforces the accepted digit count but adds no new semantic detail about the parameter beyond what the schema provides. 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 purpose: validate a Swedish personnummer. It explicitly states the accepted formats (10- or 12-digit), the Luhn check digit algorithm, and the scope (structure only, not registration). This clearly distinguishes it from the many sibling validate_* 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?

The description advises use 'before relying on it' and explicitly states what it does not do (confirm registration). This provides clear usage guidance. However, it does not directly reference sibling tools or explicitly state when to use an alternative, though the sibling list makes differentiation possible.

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?

Annotations indicate readOnlyHint=true, and the description adds that it checks the mod-10 check digit, giving behavioral insight beyond the annotation. No contradiction.

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 efficient sentences: first states purpose and warning, second details check digit and use case. 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?

No output schema provided; description mentions checking the check digit but doesn't explain the return value (likely boolean). For a validation tool, this is adequate but could be more complete by specifying output format.

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% for the single parameter, with description noting spaces/dashes ignored. The tool description adds context about Polish national ID, but doesn't add new parameter semantics 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 explicitly states the tool verifies a Polish PESEL number, checks the weighted mod-10 check digit, and distinguishes from many sibling validation tools by specifying the exact use case for KYC/onboarding.

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 instructs to use this tool to verify a PESEL before relying on it, and warns against assuming 11 digits are valid. It also provides context for when to use (KYC/onboarding of Polish individuals). Could be improved by mentioning when not to use, but the specificity is strong.

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?

Annotations declare readOnlyHint=true, and the description adds important behavioral context: normalizes to E.164, returns multiple formats and line type, and clarifies that 'valid' means well-formed not live. No contradictions.

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, front-loaded with 'USE THIS', and every sentence provides essential information without redundancy. Highly efficient.

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?

No output schema, but the description enumerates returned values (E.164, national/international formats, line type). It covers validation behavior well, though error handling is not mentioned. Adequate for the tool's simplicity.

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?

Input schema already describes both parameters with 100% coverage. The description adds critical nuance: region must be the actual ISO country, result depends on it, and default is GB. This adds value beyond 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 checks phone number formatting and normalizes to E.164, with specific verbs 'check' and 'normalise'. It distinguishes from sibling validation tools by explicit reference to phone numbers and E.164 format.

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 explicit when-to-use context ('before saving, dialling or texting') and crucial instruction about passing the correct ISO country code and not reusing unrelated fields. It lacks explicit negative use cases or alternatives but is highly specific.

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?

Discloses that only structural validation (mod-11 check digit) is performed, not database existence checks. This adds context beyond the readOnlyHint annotation. Could further clarify return behavior (e.g., boolean vs. error).

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, front-loaded sentences that immediately convey purpose and key behavior. No redundant or irrelevant information.

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?

Adequate for a simple validation tool, but lacks specification of return format (e.g., boolean or error). Without an output schema, this leaves the agent unclear on how to interpret results.

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 describes the 'cnp' parameter with detail (13-digit, spaces ignored). The description adds no new semantic meaning beyond the schema. Baseline of 3 is appropriate given 100% schema 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 it verifies a Romanian CNP using a specific algorithm (mod-11 check digit). The tool is uniquely identified among siblings by its country-specific name and validation purpose.

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 advises when to use ('verify a Romanian CNP before relying on it') and warns against assuming validity. However, it lacks explicit 'when-not' or alternative tools for deeper verification beyond structure.

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?

Annotations already declare readOnlyHint=true. The description adds behavioral details: it performs a weighted (3,7,1) mod-10 checksum on the 9-digit number, and explicitly states it does not verify real bank existence. This goes beyond the annotation.

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. The first sentence front-loads the use case with a clear directive ('USE THIS'). Every word is informative with 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 simple single-parameter tool with no output schema, the description covers the verification algorithm, its purpose, and its limitations. It is sufficiently complete for an agent to decide when to invoke and what to expect.

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?

With 100% schema description coverage, the parameter 'routing' is already well-described as a 9-digit ABA number. The description adds value by explaining the checksum algorithm applied, which enriches understanding without redundancy.

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 verifies a US bank routing/ABA transit number, distinguishing it from sibling validations for other identifiers. It specifies the action (verify) and resource (routing number), and explicitly mentions what it does not check.

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 tells when to use: 'before relying on it for a payment or direct deposit.' It also provides an exclusion: 'Does NOT check whether the bank or account is real,' which helps the agent understand limitations. However, it does not explicitly mention alternative tools for real bank checking.

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?

Annotations provide readOnlyHint. Description adds checks (Luhn, date-of-birth) and returns (DOB, gender, citizenship), beyond 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?

Two sentences, no wasted words, front-loaded with purpose ('USE THIS').

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?

Single required parameter with clear description, no output schema needed as returns are implied. Complete for a validation 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 coverage 100% so baseline 3. Description mentions '13-digit' but schema already does; no additional semantic value.

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?

Explicit verb 'verify' with specific resource 'South African ID number'. Distinct from siblings as it is country-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?

States 'USE THIS to verify... before relying on it', implying context and urgency. Could explicitly mention not for other ID types, but sibling list provides differentiation.

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?

Adds specific behavioral details beyond 'readOnlyHint' annotation: checks no-vowels alphabet and weighted mod-10 check digit. No contradictions.

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, front-loaded with action instruction, 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?

Simple validation tool with one parameter and no output schema. Description fully covers what the tool does and why.

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% and parameter description is clear. The tool description does not add meaning beyond the schema for the parameter itself, but it explains the validation logic.

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?

Clear verb 'verify' and resource 'SEDOL (LSE securities identifier)'. Distinguishes from sibling validation tools targeting other identifiers.

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?

Explicit instruction 'USE THIS to verify a SEDOL... before relying on it' provides solid usage context. Lacks explicit when-not-to-use, but sibling names make alternatives obvious.

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?

Annotations already indicate readOnlyHint=true, so no need to restate. The description adds that it checks the mod-10 check digit and returns extension digit and GS1 prefix country, and explicitly states 'Validates structure only'. This provides behavioral context beyond 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 brief—two sentences—and front-loaded with the action directive 'USE THIS'. 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 no output schema, the description adequately explains what the tool returns (extension digit, GS1 prefix country) and its scope (structure validation only). It covers the necessary details for a simple validation 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 coverage is 100% with a clear description for the sscc parameter. The description adds meaning about the tool's action on the parameter (check digit validation) and what is returned, enriching the schema's minimal info.

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: to verify an SSCC (GS1 Serial Shipping Container Code). It uses specific verbs ('verify', 'checks') and identifies the resource (SSCC). It distinguishes from sibling validation tools by naming the specific code type.

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 begins with 'USE THIS to verify... before relying on it', clearly indicating the context of use. It does not explicitly state when not to use it or list alternatives, but the context of sibling tools implies it's for SSCC only. Slightly lacking in explicit exclusions.

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?

Beyond readOnlyHint annotation, description adds that it checks algorithmic check digits and leading-digit rule, and that it does not check registration. Provides valuable behavioral context.

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 sentences, no fluff. Front-loaded with 'USE THIS'. Every sentence adds value.

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 single parameter, no output schema, and straightforward operation, the description fully covers purpose, usage, and limitations. No missing information.

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 parameter description already explaining 'spaces ignored'. Description adds no new semantic info for the parameter.

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 verb 'verify' and resource 'Turkish T.C. Kimlik No' with specific scope (structure only). Distinguishes from sibling validation tools for other countries.

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 tells when to use ('before relying on it') and warns against assumptions. Also clarifies limitation ('does NOT confirm registration'). Does not mention alternatives, but siblings are different countries so no confusion.

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?

Annotations already declare readOnlyHint=true, but the description adds behavioral context: it checks against the authoritative IANA root-zone list, is kept current, and returns valid:false for non-delegated TLDs. No contradictions.

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 with clear, front-loaded instructions. Every sentence adds value and there is no redundant information.

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 tool (one parameter, no output schema), the description fully covers its purpose, behavior, and return value. It is complete and actionable.

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 100%, so the baseline is 3. The description does not add extra meaning beyond what the schema provides for the 'tld' parameter, but no additional details are needed.

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 'check' and resource 'top-level domain', clearly stating the tool's function. It distinguishes itself from sibling tools by focusing on TLD validation against IANA list, not domain syntax or other validation types.

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 states when to use the tool ('before trusting a domain or link') and provides a clear negative example ('do NOT guess whether a TLD exists'). This offers strong guidance on usage.

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?

Annotations already declare readOnlyHint=true. The description adds behavioral details: WHATWG parsing, TLD suffix check, and returned fields (protocol, hostname, port, path, TLD known). No contradictions.

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, front-loaded with 'USE THIS', no waste. Every part earns its place.

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 purpose, usage, behavior, and return values. No gaps remain.

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 a clear description of the 'url' parameter. The description does not add new semantic meaning to the parameter itself; it provides tool context instead. Baseline 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 verb 'verify' and the resource 'URL', specifying that it parses with the WHATWG standard and checks TLD. It distinguishes itself from siblings like validate_domain and validate_email by targeting full URLs.

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 says 'USE THIS to verify a URL before fetching or storing it', providing clear context. It does not explicitly mention alternatives, but the sibling list implies specialized tools for other types, so guidance is strong.

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?

Annotations declare readOnlyHint=true, indicating no destructive actions. The description adds behavioral context by detailing the return values (version, variant, nil check), going beyond what annotations provide. No contradictions are present.

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 consists of two succinct sentences, with the first sentence front-loading the usage instruction. No extraneous information is included, every sentence earns its place.

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 validation tool with one parameter, no output schema, and read-only annotations, the description covers all necessary aspects: purpose, usage guidance, return fields, and format constraints. It is fully complete for an agent to select and 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?

The input schema provides a description for the single 'uuid' parameter ('The UUID string to validate.'), achieving 100% coverage. The tool description does not add further parameter-level detail beyond this, so 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 verifies a UUID and reads its version/variant, distinguishing it from guessing. It specifies the canonical form check and return values (version, variant, nil UUID). This completely clarifies the tool's unique function among sibling validators.

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 says 'USE THIS to verify a UUID and read its version/variant instead of guessing,' providing a clear when-to-use directive. While it does not explicitly mention when not to use or alternatives, the sibling tools are other validators for different formats, making the context sufficiently clear.

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?

Annotations indicate readOnlyHint=true, and description adds that tool only checks format+checksum, not live status. No contradictions; description provides behavioral context beyond 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?

Two sentences with front-loaded 'USE THIS' imperative. Each sentence serves a purpose: tells what it does and what it doesn't. No waste.

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?

No output schema, but description clearly states the tool's scope and limitations. For a validation tool that returns a boolean result, the description is complete enough for correct 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?

Schema coverage is 100% with descriptions for both parameters. Description adds practical guidance: vat should include prefix, country is for prefix-less numbers. This adds meaning beyond schema definitions.

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?

Description explicitly states it verifies VAT number format and checksum, specific to EU/EFTA region. Clearly distinguishes from siblings by specifying the scope and use case.

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 says 'USE THIS' for invoicing/onboarding, and clarifies it does NOT confirm live registration, directing to VIES lookup as alternative. Provides clear when-to-use and when-not-to-use 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?

Beyond the readOnlyHint annotation (true), the description discloses that it checks the allowed alphabet, ISO 3779 check digit in position 9, and returns expected check digit on failure, providing useful behavioral context.

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, front-loaded with usage instruction, no wasted words. Efficiently conveys key information.

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 validation tool with one parameter and no output schema, the description is complete: states purpose, validation logic, and failure behavior. No additional details are necessary.

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 covers 100% of parameters (one required string 'vin'). The description adds value by specifying it expects a 17-character VIN and detailing the validation checks, going beyond the schema's basic type constraint.

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 a VIN by checking alphabet and check digit, distinguishing it from sibling validation tools (e.g., validate_card, validate_email) which validate other types of identifiers.

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 use this tool to verify a VIN before acting on it and warns against assuming a 17-character string is valid. No explicit alternative mentioned, but sibling tools cover other identifiers.

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