Qiniso

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

Annotations already indicate readOnlyHint=true, so the tool is read-only. The description adds behavioral context by specifying locale-sensitive formatting (symbol position, separators) via an example, which is beyond the annotations. However, it does not address edge cases like negative amounts or rounding.

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 extremely concise: two sentences and an example. It is front-loaded with an imperative 'USE THIS', and 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?

Although no output schema is provided, the description includes an example return value ('£1,234.50') and explains the purpose. For a formatting tool, this is reasonably complete, though it could mention handling of invalid inputs.

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 clear descriptions for each parameter. The description adds a concrete example showing how parameters combine, but this does not significantly extend the schema's detail. 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 explicitly states 'USE THIS to format a money amount' and provides a concrete example, clearly identifying the tool's verb (format) and resource (money amount). It distinguishes itself from sibling validation tools by its unique function.

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 showing it in a price, invoice or email', which provides clear context. However, it does not explicitly state when not to use it or mention any alternative tools, though no such alternative exists among siblings.

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, which matches the description. Adds behavioral details beyond annotations: supports subdivisions, defaults to England, and covers many countries. 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 wasted words. Purpose is front-loaded. Information about country and subdivision support is efficiently included.

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 no output schema exists, the description covers the tool's core function and parameter semantics. Could mention return type explicitly, but overall complete for its 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?

Schema coverage is 100% so baseline 3. Description adds value by explaining date format, default country, and subdivision examples (SCT, WLS, US state), which adds meaning beyond schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: checking if a date is a public/bank holiday for business-day deadline calculations. It specifies the scope (supports ~200 countries, default GB) and distinguishes 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?

Explicitly advises when to use with 'USE THIS to...' and provides concrete contexts (deadlines, SLAs). Does not explicitly name alternatives but implies them through 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?

Annotations already indicate readOnlyHint=true. The description adds that the tool supports ~200 countries, uses ISO codes, and subdivision narrows to a region. This provides 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?

The description is a single sentence that gets to the point immediately with 'USE THIS'. It includes essential details without extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main functionality (when to use, date, country, subdivision). It doesn't specify the return format (e.g., what the output contains), but given no output schema, a minimal expectation is met 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?

Schema coverage is 100% and describes each parameter. The description adds value by explaining the purpose (e.g., 'after' is for date filtering) and providing concrete examples for country and subdivision codes.

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 finds the next public/bank holiday on or after a date, with a concrete use case (next working day). It distinguishes itself from the sibling is_holiday by focusing on 'next' rather than checking a specific date.

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 finding the next holiday, provides country code examples, and mentions subdivision narrowing. It does not explicitly contrast with siblings but the context is sufficient for appropriate 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?

Annotations already indicate readOnlyHint=true. Description adds that it returns a confidence flag and extracts specific fields, providing 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?

Three sentences with front-loaded purpose. No fluff, every sentence contributes meaning.

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 a single parameter, no output schema, and low complexity, the description is complete—covers input format, output fields, and return of confidence flag.

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 provides 100% coverage for the single 'input' parameter. Description adds that the input should be a UK or US free-text address and specifies the output structure, adding value beyond the schema 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?

Clearly states it extracts structured fields (country, postcode, city, state) from a free-text UK or US address. Distinguishes itself from sibling validation tools by being a parsing operation.

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 lists when to use: onboarding, KYC/fraud checks, storing an address, and advises against splitting the string manually. No alternatives among siblings since they are all validation tools.

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 annotations already indicate readOnlyHint=true, so the description doesn't need to reiterate. It adds value by mentioning locale-dependent behavior and the 'valid:false' return for impossible dates, though it doesn't detail successful return structure.

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 unnecessary words. It front-loads the primary purpose and includes critical usage notes efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the two parameters and full schema coverage, the description adequately covers the tool's behavior. It mentions return values for invalid dates but could be more explicit about successful return format. However, without an output schema, it provides reasonable context.

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. The description adds context about locale values ('en-GB' vs 'en-US') and their impact, and explains the purpose of the 'input' parameter for ambiguous dates, going 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 parses human-written dates into ISO 8601 format, specifically highlighting its use for ambiguous numeric dates. It distinguishes itself from sibling validation tools by focusing on date interpretation.

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' and provides context for when to use it, especially for ambiguous dates. It lacks explicit when-not-to-use or alternative tools, but the sibling tools are mostly validators, so the guidance 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 declare readOnlyHint=true, which aligns with description. Description adds critical behavioral context: date-sensitivity, handling of historical rates, US returns 0 for national VAT, and requirement to always pass invoice date for GB. 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?

Four sentences, no redundancy. Front-loaded with key directive. Every sentence adds value. Perfectly compact for the information conveyed.

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?

Tool is moderately complex (multi-country, date-sensitive). Description covers main use cases and constraints adequately. Lacks mention of error handling for invalid inputs but given simplicity of return value (rate or 0), it's sufficient.

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 all 3 parameters (100% coverage), so baseline is 3. Description adds value by explaining parameter interplay: country determines tax type, state needed for US, date critical for GB. Clarifies default for country is GB.

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 returns VAT for GB and sales tax for US based on date/state. Distinguishes from sibling tools (none tax-related) with specific verb+resource. No ambiguity.

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 tax calculation, warns against recalling from memory, specifies when to pass invoice date and state code. Clear when-not-to-use: US without state returns 0. No alternative tools to differentiate.

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 it validates structure only and does not perform lookup. No contradictions. The behavioral constraints are fully disclosed.

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 zero waste. Information is front-loaded with imperative instruction. Every phrase 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?

For a validation tool with one parameter and no output schema, the description fully covers what it does (format, checksum) and explicitly states what it does not do (lookup). It is complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with one parameter described. Description adds important detail 'spaces ignored' and mentions Verhoeff check digit and leading-digit rule, enriching the schema with algorithmic context.

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 format and checksum of an Indian Aadhaar number, and distinguishes from other validation tools by specifying it does not look up the number. It uses specific verb 'verify' and resource 'Aadhaar 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?

Description begins with 'USE THIS to...', providing clear context. It warns against assuming validity of 12 digits, but does not explicitly state when not to use or mention alternatives among sibling tools. However, given the sibling set is all validation tools, the usage 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 show readOnlyHint=true, and the description confirms no side effects (validates structure only). It adds specific behavioral details like handling the born-from-2000 rule in mod-97 checks, which goes beyond the annotation while being consistent.

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 sentences, front-loaded with the imperative 'USE THIS' and no unnecessary words. Every sentence provides distinct information: what to do, what it checks, and what it validates.

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, read-only, no output schema), the description is fully complete. It covers the purpose, checks performed, and limitation (structure only). 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 description for the single parameter. The tool description mentions punctuation is ignored, which adds some value. However, the baseline is 3 since schema already provides meaning, and the description does not significantly expand parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the tool validates a Belgian National Register Number, naming it in both languages (Rijksregisternummer / Numéro de Registre National) and mentions specific checks (11-digit form, mod-97 with born-from-2000 rule). This distinguishes it from sibling validators 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?

The description explicitly instructs to use this tool before relying on the number, providing clear context. It also states it validates structure only, which sets expectations. However, it does not explicitly exclude other scenarios or mention when not to use it, missing some depth.

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 states the tool 'validates structure only,' aligning with the readOnlyHint annotation. It clarifies there are no side effects, but it could further disclose the exact return format or error 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 concise with two sentences, front-loading the imperative usage instruction. Every sentence adds essential information 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?

The description explains the tool's input and validation logic but does not describe the expected output (e.g., boolean, status code) or potential errors. Given the lack of an output schema, this omission limits 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?

With 100% schema coverage, the schema already explains the 'egn' parameter. The description adds value by explaining the validation logic (10-digit form and check digit), helping the agent understand what the tool checks beyond the parameter 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 the tool's purpose: to verify the structure of a Bulgarian EGN, specifying it checks the 10-digit form and weighted mod-11 check digit. This distinguishes it 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?

The description explicitly says 'USE THIS to verify a Bulgarian EGN before relying on it,' providing clear context for when to use it. However, it does not mention when not to use it or suggest alternatives, which would be helpful given the many sibling validation tools.

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 (indicating non-destructive), the description explicitly states that the tool 'does NOT confirm the number is issued,' which is a critical behavioral trait. This prevents the agent from assuming the number is valid beyond structural correctness.

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 extremely concise, consisting of just three short sentences. The first sentence front-loads the purpose with 'USE THIS,' and every subsequent sentence adds necessary detail 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 that there is no output schema, the description could be more complete by hinting at the return format (e.g., boolean). However, the description adequately covers the tool's scope and limitations, and the sibling context implies a standard validation output. Minor lack of return value info prevents a 5.

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% (the single parameter 'bsn' is fully described with type, format, and whitespace handling). The description adds no additional parameter semantics beyond what the schema already provides, 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?

The description clearly states that the tool verifies a Dutch BSN by checking digit length and the '11-test' checksum. It specifies the exact resource (Dutch BSN) and distinguishes from sibling validation tools (e.g., validate_email, validate_iban) by targeting a specific identifier.

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 clear when-to-use guidance. It does not explicitly state when not to use or name alternatives, but given the 50+ sibling validation tools, 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?

Description details the validation algorithms (Base58Check, Bech32/Bech32m) and the consequence of bad checksum, which is beyond the readOnlyHint 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 well-structured sentences. Front-loaded with purpose and imperative usage, no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema, the description fully explains the operation, formats checked, and return information. No gaps: it covers what, why, and output hints.

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 a description, but the description adds context about accepted formats (legacy 1…/3… or bech32 bc1…) and the return value (type and network), adding value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool verifies a Bitcoin address, listing specific formats and return of type/network. Distinguishes from sibling validation 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?

Imperative 'USE THIS' indicates when to use, and provides a caution about assuming validity. However, no explicit comparison to alternative tools, though the specificity naturally guides 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?

Discloses all relevant behaviors: Luhn checksum verification, brand detection from BIN, length check. States limitations upfront. Annotations confirm readOnlyHint=true, and description adds 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 sentences that are extremely efficient. Front-loaded with 'USE THIS' imperative, immediately stating purpose. 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?

Given the tool's simplicity (1 parameter, no output schema needed) and the comprehensive annotations, the description fully covers what an agent needs to use it correctly. No additional context is required.

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 the single parameter with 100% coverage and description 'spaces and dashes are ignored'. Description adds semantic value by explaining what the validation involves (Luhn, brand, length), going beyond the schema's minimal 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?

Description clearly states 'check a payment card number's structure' and specifies the resource (payment card number). It distinguishes from sibling validation tools by focusing on payment cards and their specific attributes (brand, Luhn, length).

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 check a payment card number's structure before using it' and warns 'never assume a card number is valid or guess its brand'. Also clarifies what it does NOT check (real, active, funds), guiding when not to rely on 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?

The annotation readOnlyHint is consistent. The description adds that validation is structural only, which is key behavioral info. No contradictions. Could mention side effects but none expected for a read-only validator.

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, front-loaded with 'USE THIS', and each sentence adds value. No verbosity. Perfectly 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?

The description covers purpose, usage context, and limitations (structure only). Without an output schema, the return format is missing but likely a boolean, which is standard. Overall sufficient for a simple validator.

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 'ahv' has a schema description. The tool description adds context about the 13-digit form starting with 756 and the check digit, reinforcing the schema. No further parameter details 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 clearly states the tool validates a Swiss social-insurance number (AHV/AVS) and specifies it checks the 13-digit form starting with 756 and the EAN-13 check digit. It uniquely identifies the tool 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 advises using this tool before relying on an AHV number and clarifies it only validates structure. While it doesn't explicitly exclude other uses or mention alternatives, the context is clear given the sibling tools are different 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?

Annotations provide readOnlyHint=true. Beyond that, the description clearly states it validates structure only and does not confirm registration, adding crucial behavioral context about limitations.

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 two sentences and a short note. Every word adds value, and key information is front-loaded.

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 tool has a single parameter and no output schema. The description omits the return type (e.g., boolean or error), but the purpose and behavior are mostly clear given the sibling context.

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 adds the algorithm name and details about the check character, but these largely restate the schema's description, offering minimal additional 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 specifies the tool validates a Chinese Resident Identity Card number, mentions format and check character, and distinguishes from siblings by naming the specific ID type and its algorithm.

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' indicating when to use it, advises against guessing the check character, and contrasts with siblings implicitly. However, it does not explicitly state when not to use it or compare with other validation tools.

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 reveals the underlying validation logic (two mod-11 check digits), which is useful behavioral info beyond the readOnlyHint annotation. No contradictions detected.

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 unnecessary words. The first sentence immediately conveys the tool's purpose and usage directive, making it efficient for agents to parse.

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 a single parameter and no output schema, the description provides sufficient information about purpose and usage. It does not describe the return value, but that is acceptable given the tool's simplicity and the availability of output schema? (none) though some agents might benefit from knowing it returns a boolean or status.

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 'cnpj' parameter completely (14 digits, punctuation ignored). The description adds no additional semantic detail about the parameter. With 100% schema coverage, a 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's function: verify a Brazilian CNPJ by checking mod-11 check digits. It distinguishes from sibling validation tools by explicitly naming the 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 suggests when to use the tool ('instead of trusting 14 digits', 'Call this for onboarding Brazilian businesses'), providing a clear usage context. However, it does not explicitly state when not to use it or mention alternatives 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?

Annotations include readOnlyHint=true but no destructive hint. The description adds that it validates structure only (not registration), and mentions the check character algorithm. 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 two sentences, front-loaded with the main purpose, and every sentence 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?

The tool has no output schema, so the description could have explained the return value (e.g., boolean or validation result). It does not, leaving a gap. However, for a simple validation tool, the core purpose is adequately covered.

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 one parameter. The description adds meaning: '16-character', 'spaces ignored, case-insensitive', and the importance of not guessing the check letter, which goes beyond the schema 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 the tool verifies an Italian Codice Fiscale, specifies the checks (16-character format and mod-26 check character), and distinguishes it from other validation tools in the sibling list.

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' and warns against guessing the check letter. Also clarifies it does not confirm registration, setting expectations. Could be improved by mentioning when not to use it, but the sibling context makes the use case 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, which the description aligns with. The description adds behavioral details beyond annotations: it verifies two mod-11 check digits and rejects all-identical sentinels, disclosing the validation logic and edge cases.

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 (three sentences) with a strong imperative opening. Every sentence adds distinct value: directive, validation logic, and typical 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?

For a single-parameter validation tool with no output schema, the description fully covers purpose, validation algorithm, and common use case (KYC). It also addresses the specific sentinel rejection edge case, leaving no ambiguity about the tool's behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides basic description for the 'cpf' parameter (11 digits, ignored formatting). The description adds semantic value by explaining the validation algorithm (mod-11 checks, sentinel rejection), which is not in the schema and helps the agent understand what the tool does with the input.

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 specific verbs ('verify', 'checks') and clearly identifies the resource ('Brazilian CPF'). It explicitly mentions the two mod-11 check digits and rejection of all-identical sentinels, distinguishing it from many 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?

The description explicitly states 'USE THIS to verify a Brazilian CPF before relying on it' and provides context like 'KYC/onboarding of Brazilian individuals.' It implies when-not-to-use by stating 'never assume 11 digits are valid,' but does not explicitly differentiate from similar tools like validate_cnpj for companies.

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 the mod-10 check digit algorithm and return of expected digit on failure. Annotations indicate read-only, which is consistent. Adds behavioral info beyond annotations, though the return format on success is not specified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with no filler. Front-loaded with the command 'USE THIS' and immediately explains the validation logic.

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 provides sufficient context: what it checks and what it returns on failure. Could be more complete by describing success behavior, but overall adequate.

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 and example for the single parameter. The tool description adds context about CUSIP but does not significantly enhance 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?

Clearly states the tool validates a CUSIP (North American securities identifier) and describes the check digit verification. Distinct 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 a CUSIP' and implies when to use (when you have a 9-character string to validate). Does not explicitly contrast with sibling tools, but the context of CUSIP vs. other identifiers 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 declare readOnlyHint=true, and the description confirms 'Validates structure only.' It adds behavioral details about the mod-11 rule and the exception for pre-1954 numbers, which go beyond the 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?

The description is three sentences with no redundancy. It front-loads the imperative 'USE THIS' for quick scanning. Every sentence adds necessary information: action, rule, and caveat.

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 (one parameter, no output schema), the description covers the validation logic and structure. It does not explicitly state the return format, but for a validation tool, the behavior (checks validity) is clear. Slightly more detail on output would improve 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?

The single parameter 'rc' has a schema description (100% coverage). The tool description adds meaning by explaining the validation logic (mod-11 rule, pre-1954 handling), which is not present in the schema. This enriches the parameter's context.

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 Czech or Slovak rodné číslo (birth number). It specifies the validation rule for 10-digit forms and notes pre-1954 numbers. This precisely identifies the resource and action, distinguishing it from sibling national ID 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 begins with 'USE THIS to verify... before relying on it,' providing clear context for when to use. It implies the tool is for structural validation only, but does not explicitly exclude use cases or mention alternatives among the many sibling validation tools.

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 the description adds that the tool only validates structure and does not confirm registration. This sets correct expectations 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 sentences, imperative and front-loaded ('USE THIS'), with no extraneous information. Every sentence contributes 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?

Without an output schema, the description adequately explains what the tool does and its limitations. It provides enough context for an agent to understand the tool's scope.

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 describes the 'id' parameter with full coverage. The description adds that spaces and slashes are ignored, which is helpful beyond the schema definition.

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 German tax ID (Steuer-Identifikationsnummer), specifies the check digit algorithm (ISO 7064), and distinguishes it from registration confirmation. It differentiates well 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 explicitly advises using this tool before relying on a tax ID and warns against assuming 11 digits are valid. It also notes the tool only validates structure, not registration. While it lacks explicit 'when not to use' or alternatives, 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 already provide readOnlyHint=true. The description adds that the tool checks the control letter and returns a classification (DNI/NIE). It does not disclose error behavior or rate limits, but the read-only nature is clear. Annotations lower the burden, so score is adequate.

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 redundant words. Every part is informative and 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 validator with one parameter, no output schema, and readOnlyHint annotation, the description covers the tool's purpose, input expectations, and return type (DNI/NIE). 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 parameter description for 'id'. The description reinforces the control letter check but adds little new meaning 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 verb 'verify' for Spanish DNI/NIE, specifies 'checks the mod-23 control letter' and 'returns whether it is a DNI or NIE'. It distinguishes itself from sibling validators by targeting a specific Spanish document 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?

Explicitly says 'USE THIS to verify a Spanish DNI or NIE' and advises not to guess the control letter. Provides clear context for when to use, though it does not list explicit when-not-to or alternatives; however, the sibling tool names indicate this is specific to Spanish IDs.

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, which the description does not contradict. The description adds value by stating it returns the TLD and whether it is known, which is 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 sentences, no unnecessary words. Front-loaded with 'USE THIS' for immediate clarity. 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 tool with one parameter, no output schema, and simple annotations, the description is complete. It states the purpose, what it validates, what it returns, and when to use it.

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 meaning by explaining that the parameter is validated against IANA suffixes and catches made-up TLDs, providing context beyond the schema's basic 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 the tool's specific action: verifying domain name structure and checking TLD against IANA-delegated suffixes. It distinguishes itself from sibling validation tools by focusing on domain-specific validation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to use this tool for verifying domain legitimacy instead of assuming, and provides examples of what it catches (invalid labels, made-up TLDs). This gives clear when-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 adds behavioral context beyond the readOnlyHint annotation, detailing the two-stage mod-11 checksum validation and confirming it only checks structure. This provides useful information about what the tool does internally.

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 short sentences, immediately stating the tool's purpose and key details. No wasteful words; it is front-loaded with critical usage guidance.

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, the description adequately covers purpose, scope, and algorithm. However, it does not specify the output format (e.g., boolean or details), which could be helpful 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?

Schema coverage is 100%, and the description adds no additional meaning beyond what the schema already provides (e.g., 'The 11-digit Estonian isikukood (spaces ignored)'). Per rules, baseline is 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 it verifies an Estonian isikukood, specifies the 11-digit form and mod-11 check digit, and distinguishes it from sibling tools by naming the specific country and 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 explicitly says 'USE THIS to verify...before relying on it,' providing a clear usage context. It also notes it 'validates structure only,' implying when not to use it (e.g., for verifying identity). No explicit alternatives, but the scope is well-defined.

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 details RFC subset validation, TLD checking, 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?

Two sentences, front-loaded with 'USE THIS'. Every sentence provides essential information: usage context, what it validates, what it does not. 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?

For a simple read-only tool with one parameter and no output schema, the description is complete. It covers purpose, scope, limitations, and usage guidance. 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 covers 100% of parameters with basic description. Description adds context: it's the address to check syntax and TLD. Adds value by clarifying usage scenario.

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 (email address), and specific scope (syntax and TLD realness). Differentiates from siblings by specifying it validates email, not other formats.

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 it before saving or sending instead of trusting raw input. Also states what it does not check (deliverability). Could mention alternatives like validate_domain for domain-only checks, 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 indicate readOnlyHint=true, and description adds important behavioral context: validates format and checksum, returns checksummed form, and warns about permanent fund loss for incorrect addresses. 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, no fluff. First sentence gives imperative usage, second explains functionality, third warns of risk. Every sentence contributes meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool with read-only annotations, the description covers purpose, usage context, behavioral details, and risk. No gaps given complexity and 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 has 100% coverage with a single parameter described. Description adds value beyond schema by explaining why validation matters ('never trust...') and the consequence of errors, aiding understanding beyond the field 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 Ethereum address format and EIP-55 checksum, and returns the correctly-checksummed form. It uses a specific verb ('validate') and resource ('Ethereum address'), and is easily distinguished 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 when to use the tool: 'before sending funds or storing it'. It warns against trusting raw strings, providing clear context. No explicit when-not-to-use, but sibling tools cover different validation types, so exclusion is implicit.

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 discloses the specific validation performed (11-digit form, both mod-11 control digits) and the limitation (structure only, not registration). This adds significant behavioral context that the annotation alone does not 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?

The description is extremely concise: two sentences, front-loaded with 'USE THIS'. Every word adds value, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple validation tool with one parameter and no output schema, the description adequately covers purpose, validation scope, and limitations. The only minor gap is not describing the return format, but output schema is absent and the tool is self-explanatory.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage for the single parameter, with a clear description. The tool description adds no additional meaning beyond what the schema already provides. Per guidelines, 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 specifies the verb 'verify' and the resource 'Norwegian fødselsnummer (national identity number)'. It distinguishes this tool from over 50 sibling validation tools by explicitly naming the specific identifier and describing its function. The limitation 'does NOT confirm the number is registered' further clarifies 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 instruction 'USE THIS to verify... before relying on it' provides clear usage context. It explains what the tool checks and explicitly states what it does not do. While no alternative tools are named, the set of siblings implies this is the correct choice for Norwegian national ID validation.

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 details that it checks the 13-digit body with Corsica handling and the mod-97 key. It states 'Validates structure only,' but does not specify the return format, which would be helpful given no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, using two sentences that front-load the imperative 'USE THIS' and then deliver key details. No unnecessary words or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter validation tool, the description covers purpose, key behavioral details, and limitations. It lacks explicit mention of the return type, which is a minor gap given no output schema, but overall sufficient 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?

The input schema already describes the NIR format (13 digits + key, spaces ignored). The description adds semantic value by noting that Corsica codes (2A/2B) are handled and advising against guessing the key, enhancing parameter 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 verifies a French NIR, specifying the exact resource and actions. It distinguishes from sibling validation tools by focusing on the French social-security number and mentioning the specific format and key 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 explicitly advises using this tool when relying on a NIR ('do not guess the key'), providing clear when-to-use guidance. It also clarifies that it only validates structure, implying limitations, but lacks direct comparison to sibling tools.

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, and the description adds that it only validates structure, not registration, which is valuable context. 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 two short sentences, front-loaded with the imperative 'USE THIS', with no extraneous words. 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 the simple input (one string parameter) and no output schema, the description adequately explains what the tool does, what it checks, what it returns (issuing country), and its limitation (no registration confirmation). It is 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 covers 100% of the single parameter with a description, and the description adds that 'spaces and dashes are ignored,' 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 it verifies a GLN (Global Location Number) before relying on it, specifying it checks the check digit and returns the issuing country. It distinguishes from sibling validation tools by naming the specific identifier standard.

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 a GLN... before relying on it,' providing clear when-to-use guidance. However, it does not explicitly mention when not to use it or name alternatives, though the sibling list implies it's for GLN exclusively.

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, and the description adds behavioral details: it validates structure only, does not confirm real products, and returns barcode type and country. 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 usage intent, concise and without wasted words. Every sentence provides essential 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?

Despite no output schema, the description explains what is returned and the limitation of not checking real products. Parameter is thoroughly covered. The tool is well-documented for its complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage for the single parameter. The description adds value by explaining that spaces and hyphens are ignored, listing supported barcode types (EAN-8, UPC-A, etc.), and describing return values (barcode type, country).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool verifies product barcodes (GTIN/EAN/UPC) by validating the check digit, using a specific verb 'verify' and specifying the resource. It distinguishes itself among sibling validate_* tools by focusing on barcodes.

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 instead of guessing the check digit,' providing a clear when-to-use. It also notes the tool only validates structure, not product registration, but does not explicitly list when not to use or alternative tools.

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 indicating a safe read operation, the description adds that it 'validates structure only,' setting expectations that it does not check identity existence or assignment. It also explains the structural components being validated.

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. The imperative 'USE THIS' front-loads the purpose, and 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 the simple single-parameter schema and no output schema, the description fully covers the tool's behavior, limitations, and usage context. 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?

The schema already provides a description with an example, but the description adds meaning by explaining the structure format (DDMMYY + century sign, etc.), which enriches understanding beyond the schema's brief 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 a Finnish henkilötunnus (HETU), specifies the exact structure it checks (DDMMYY + century sign + individual number + mod-31 check character), and distinguishes itself from sibling validation tools by targeting a specific identifier 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 explicitly guides to use this tool to verify a HETU before relying on it and warns against guessing the check character. It provides clear context for when to use it, though it does not mention 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 indicate readOnlyHint=true, so no destructive behavior. Description adds that it validates structure only, providing transparency about scope. 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 redundant information. Every sentence adds value: first tells when to use, second explains what it checks. 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?

Tool is simple with one parameter and no output schema. Description covers purpose, validation method, and scope. Does not specify return format but is adequate for a validator 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 describes parameter as '11-digit Croatian OIB (spaces ignored)'. Description adds detail about validation algorithm (ISO 7064 MOD 11,10), exceeding schema coverage. With 100% schema coverage, baseline is 3, so extra context earns a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it validates Croatian OIB (personal identification number) by checking 11-digit form and ISO 7064 check digit. Distinguishes from sibling validation tools by specifying the exact standard and country.

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 'USE THIS to verify a Croatian OIB before relying on it', indicating when to use. Does not explicitly mention when not to use or alternative tools, but context of sibling tools implies uniqueness.

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. Description adds value by detailing the validation steps (country, length, checksum) and return fields, providing 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?

Two sentences, front-loaded with imperative 'USE THIS', no unnecessary words. Efficient and clear.

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 tool with one parameter and no output schema; description fully explains what the tool does, what it checks, and what it returns. Complete for the given complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% with one parameter. Description adds 'spaces are ignored,' which is additional useful information beyond the schema description. Provides meaningful extra context.

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 defines the tool's purpose: verifying IBANs. It specifies the checks performed (country, length, checksum) and what is returned, 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?

States when to use ('whenever a user supplies a bank account for a payment, payout or invoice') and provides an explicit directive ('USE THIS... instead of guessing'). Does not mention alternatives or when not to use, but context is clear given sibling tools.

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 behavioral details: checks Luhn check digit, recognizes IMEISV, returns TAC, and does not verify device authenticity. 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?

The description is two focused sentences, front-loaded with an imperative directive, and contains no redundant information. 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 tool's simplicity (single parameter, no output schema), the description covers the core purpose and limitations. However, it could briefly mention the likely return format (e.g., boolean or object with validity and TAC) to improve completeness slightly.

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 schema coverage is 100% and the parameter description already specifies format, the tool description adds value by explaining the validation logic applied to the input (Luhn, IMEISV, TAC extraction), enhancing the agent's understanding of how the parameter is processed.

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 phone/device IMEI, specifies the resource (IMEI), and distinguishes it from sibling validators by focusing on Luhn check digit and IMEISV recognition. It uses imperative language 'USE THIS' to direct the agent.

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 to use this for IMEI verification before relying on it, and clarifies what it does not check (real, active, blocklisted). This directly guides when to use and when not to use, despite not naming alternative tools.

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, and the description adds valuable behavioral details: strict RFC 791 compliance for IPv4 (rejecting leading zeros/out-of-range) and RFC 4291 for IPv6 (including compression and embedded IPv4), and that it returns the version. 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?

Two sentences, front-loaded with an imperative usage directive. Every sentence adds critical 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?

While the description covers validation logic and return of version, it does not specify the exact return format (e.g., boolean, object). With no output schema, this gap could affect an agent's interpretation of the tool's output.

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 single parameter described as 'The IPv4 or IPv6 address to validate.' The description enriches this by clarifying the strict validation checks and return value, adding context beyond the schema's basic 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 explicitly states the tool validates IP addresses, specifies IPv4/IPv6 with RFC details, and distinguishes from sibling validation tools by focusing on IP format. The verb 'validate' and resource 'IP' are 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?

The description begins with 'USE THIS to verify an IP address before relying on it', providing explicit guidance on when to use it. It does not mention alternatives or when not to use, but the sibling tools are all format-specific validators, making the 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?

The description discloses the validation behavior (checks prefix and check digit, returns expected check digit on failure), adding context beyond the readOnlyHint annotation. It does not mention return format or edge cases, but for a simple validation tool this is sufficient.

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, directly front-loaded with the imperative 'USE THIS', and every phrase adds value. No extraneous 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 tool's simplicity (single parameter, no output schema, read-only), the description covers key aspects: purpose, validation logic, and failure behavior. It could mention the return type, but this is not critical 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 input schema already describes the isbn parameter as 'The ISBN-13; hyphens and spaces are ignored.' with 100% coverage. The description adds no new semantic details beyond what the schema provides, meeting the baseline expectation.

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 ISBN-13 book identifier, specifying the exact checks (978/979 prefix and mod-10 check digit). It distinguishes from the sibling validate_isbn10 by explicitly mentioning ISBN-13, leaving no ambiguity about its resource.

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 to use this tool instead of trusting raw digits, providing a clear when-to-use directive. However, it does not mention when not to use it or directly name alternative validation tools for other formats, though the sibling list implicitly differentiates.

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; description adds behavioral detail: 'checks the mod-11 check digit (which may be 'X')'. 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, no waste, front-loaded with actionable instruction.

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 tool with one parameter, readOnly annotation, no output schema. Description provides sufficient context for correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage for the single parameter with description. Description adds 'hyphens/spaces ignored', which is useful but not essential 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 'verify an ISBN-10' and 'checks the mod-11 check digit', with explicit differentiation from validate_isbn for 13-digit ISBNs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use this tool (for ISBN-10) and when not to (for 13-digit ISBNs use validate_isbn).

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 no side effects. The description adds value by detailing the internal checks (format, Luhn digit) and return value (country code), providing 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 concise, with two sentences and an imperative opener 'USE THIS'. Every sentence adds value, and it is well-structured for quick comprehension.

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, what it checks, and what it returns. It is complete and leaves 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?

With 100% schema coverage, the description does not need to add much. It reiterates the parameter format and gives an example, which is helpful but does not provide new 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 clearly states the tool's purpose: 'verify an ISIN'. It specifies the resource (ISIN) and what it checks (format and Luhn check digit), distinguishing it from sibling validation tools that target 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?

It provides a clear use case: 'Call this when a user supplies a security/instrument identifier.' While it does not explicitly exclude alternatives, the tool's specificity to ISIN and the sibling context make the guidance 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; the description adds that the check digit may be 'X' and that the tool returns the expected digit on failure, 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 sentences, front-loaded with a clear imperative, and contains no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description explains the check digit behavior but omits what the tool returns upon successful validation. For a simple tool with no output schema, this is a notable 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 coverage for the single parameter is 100%, and the schema already describes '8 chars; hyphen ignored'. The description adds no additional parameter meaning, meeting the baseline but not exceeding it.

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 ISSN by checking its mod-11 check digit, distinguishing it 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 advises using the tool before relying on an ISSN, but does not specify when not to use it or provide alternatives among the many sibling validators, leaving usage guidance incomplete.

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 the tool checks the ISO 17442 / ISO 7064 MOD 97-10 check digits, which goes beyond the readOnlyHint annotation by specifying the validation algorithm. It does not describe the return format or behavior on invalid input, but the core behavioral detail is sufficient.

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 information. The imperative 'USE THIS to verify' effectively front-loads the purpose, and each sentence contributes valuable context about usage 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?

Given a single parameter, no output schema, and simple validation behavior, the description covers the tool's input, purpose, and algorithm adequately. It does not specify the return value (e.g., boolean or result object), but this is a minor omission for a straightforward validator.

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 documents the single parameter 'lei' with a description and example, achieving 100% coverage. The description adds no additional semantic information about the parameter beyond what the schema provides, meeting the baseline but not exceeding it.

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 Legal Entity Identifier (LEI) using specific standards (ISO 17442 / ISO 7064 MOD 97-10). The verb 'verify' and the specific resource 'LEI' are precise, and the tool is distinguished from sibling validators by its unique target.

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 an LEI and warns not to assume a 20-character code is valid. This provides clear context for when to invoke the tool and a key caveat, though it does not list alternative tools (which are self-evident from sibling names).

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, confirming no destructive behavior. Description adds that validation is structural only, clarifying it does not check against external databases. 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 with zero redundancy. All information is front-loaded and directly relevant to usage, behavior, and scope.

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 explains what is validated (format and check digit) and what is not (structure only). Lacks explicit return value description, but the purpose is clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema provides 100% coverage with a clear description for the single parameter (curp: 'The 18-character CURP (case-insensitive).'). The description's note about not guessing check digits is useful context but does not add new parameter meaning 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 Mexican CURP format and check digit, specifying the exact resource (Mexican CURP) and action (validate structure). It is distinct from sibling validation tools targeting 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?

Explicitly instructs when to use ('USE THIS to verify a Mexican CURP before relying on it') and warns against guessing check digits. Does not explicitly mention alternative tools, but given the specific identifier, no direct alternative exists.

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; description adds that it checks mod-11 check digit and emphasizes not to assume 9-digit validity, providing useful behavioral detail 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, front-loaded with 'USE THIS', no wasted words. Every sentence adds essential 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, the description covers purpose, usage, and algorithm. It does not specify return type, but given context of sibling tools, it is nearly 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% so baseline is 3; description adds value by explaining the validation algorithm (mod-11) which implies the parameter is a check-digit number, improving semantic understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool verifies a Portuguese NIF, uses specific verb 'verify', and explicitly distinguishes from sibling validate_dni.

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 gives explicit context ('before invoicing or onboarding'), warns against assuming validity, and directly points to alternative tool validate_dni.

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 details: the check digit algorithm (MOD 11-2, may be 'X') and accepted input formats (bare ID or URL). 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 short sentences, front-loaded with the key directive, and no redundant information. Every word contributes to understanding.

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 validation tool with no output schema, the description covers purpose, input format, and validation mechanism. It does not describe the return value format, but the core behavior is sufficiently explained.

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 meaning by explaining the check digit algorithm and that URL inputs are accepted, going beyond the schema's example.

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 researcher identifier, distinguishes it from blindly trusting 16 digits, and specifies the validation algorithm (ISO 7064 MOD 11-2). It differentiates from sibling validators by explicitly naming ORCID.

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 clear context for when to use. It does not mention when not to use or list alternatives, but the sibling tools are other validators, making the intent 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?

Discloses limitations (validates structure only, no registration check) and aligns with readOnlyHint annotation. No contradictions; provides 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?

Three front-loaded sentences with no wasted words. Imperative tone, key details in order: purpose, usage, 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?

Adequate for a simple validation tool with one parameter and no output schema. Covers what it does, format, and limitation. Could mention return type but not critical.

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 already clear. Description adds minor extra context about accepted digit forms and Luhn check, but does not significantly enhance understanding 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?

Clearly states the tool validates a Swedish personnummer before relying on it, specifies it checks Luhn digit, and distinguishes from sibling validation tools by naming the specific country identifier.

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 to use before relying on a number, and clarifies it does not confirm registration. However, it does not name alternative tools for registration checks or specify 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?

Describes the weighted mod-10 check digit beyond the readOnlyHint annotation. 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?

Two sentences, zero waste, front-loaded with imperative 'USE THIS'. Every word 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?

Complete for a single-parameter read-only tool with no output schema. Provides purpose, usage context, and behavioral detail.

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 parameter (100% coverage), but description adds behavioral context (check digit validation) and reinforces intended use, adding 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?

Description clearly states it validates a Polish PESEL, specifying the check digit mechanism and use case (KYC/onboarding). Distinguishes from sibling validate_* tools by naming the specific identifier.

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 for verification before relying on a PESEL, and for KYC/onboarding. Does not explicitly state when not to use or alternatives, but context is clear among 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?

Annotations already declare readOnlyHint=true, which matches the validation nature. The description adds behavioral details beyond annotations: it returns multiple formats (E.164, national, international) and line type, and explains the definition of 'valid'.

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 focused sentences with no extraneous text. The imperative 'USE THIS' at the start front-loads the purpose. Every sentence adds essential 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?

Despite no output schema, the description fully details return values (E.164, national/international, line type) and meaning of 'valid', making the tool's behavior fully understandable.

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 adds value by emphasizing the region parameter's impact and the necessity of using the correct country code, which goes beyond the schema's simple 'ISO country code' 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 states a specific verb ('check', 'normalise') and resource ('phone number'), and clearly distinguishes from sibling validation tools by specifying phone-specific outputs like E.164 and line 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?

Explicitly says when to use ('before saving, dialling, texting'), provides a crucial warning about passing the correct ISO country, and clarifies what 'valid' means (not live).

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, already indicating a safe read operation. The description enriches this by revealing the algorithm ('weighted mod-11 check digit') and scope ('Validates structure only'). This goes beyond what annotations provide, though it lacks details on the return format or error 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 extremely concise: two sentences, no wasted words. It front-loads the core purpose in an imperative tone and adds a technical detail in the second sentence. 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 single parameter and lack of output schema, the description adequately covers the tool's purpose and behavior. It could mention the return type (boolean or error) but the context of validation tools suggests a boolean. Overall, it is sufficient for an agent to select and use 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 already describes the single parameter 'cnp' as 'The 13-digit Romanian CNP (spaces ignored).' With 100% schema coverage, the description adds no further semantic information about the parameter, 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?

The description explicitly states the tool validates a Romanian CNP (Cod Numeric Personal), using the imperative 'USE THIS' and specifying it checks the weighted mod-11 check digit. It clearly distinguishes from the many sibling validation tools by targeting a specific national identifier.

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 it — never assume 13 digits are valid', implying it should be used when trust in a CNP is needed. It does not explicitly state when not to use or list alternatives, but the context of sibling tools makes the purpose 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 declare readOnlyHint=true, so the description adds value by detailing the checksum algorithm and explicitly stating the tool does not verify real bank accounts. This goes 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 sentences, front-loaded with purpose, no unnecessary words. 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 single-parameter input, readOnlyHint annotation, 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 coverage is 100% with a clear description of the 'routing' parameter. The tool description adds context about the 9-digit length and checksum validation, providing additional meaning 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 verifies a US bank routing/ABA transit number using a weighted mod-10 checksum. It distinguishes itself from sibling validation tools by specifying the exact resource and algorithm.

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 this before relying on a routing number for payment/direct deposit, and clarifies it does not check real bank existence. While it doesn't name alternatives, the sibling tools list provides clear 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?

Annotations indicate this is a read-only operation, and the description adds details on the specific checks (Luhn, DOB validity) and outputs (DOB, gender, citizenship). 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, front-loaded with the imperative usage instruction, followed by concise technical details. 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?

For a simple validation tool with one parameter and no output schema, the description fully covers the tool's behavior, inputs, and outputs. The sibling validator list provides sufficient context.

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 parameter description. The description adds minor extra context (stating '13-digit') but does not significantly enhance 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 explicitly states the tool verifies a South African ID number, checking Luhn check digit and date-of-birth validity, and returning encoded data. This clearly defines the specific resource and action, distinguishing it from sibling validators for other ID 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 tells the agent to use this before relying on a South African ID number. While it does not explicitly list when not to use it, the sibling tools context and tool name make it clear this is specific to SA IDs.

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, so the description does not need to state safety. The description adds context about the validation algorithm (no-vowels, check digit), but it does not specify the return value or error behavior, which is a gap given no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, front-loaded with a clear usage instruction. Every word adds value with no redundancy or 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 one-parameter read-only tool, the description covers purpose and usage. However, it lacks specification of the return format (e.g., boolean or error), which is needed since there is no output schema. This reduces completeness 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?

The parameter 'sedol' is fully described in the schema (100% coverage) with an example. The description adds context about SEDOL being an LSE identifier, but it does not add significant 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?

The description clearly states the tool verifies a SEDOL (LSE securities identifier) and specifies the validation criteria (no-vowels alphabet and weighted mod-10 check digit). It distinguishes the tool from siblings by naming the specific identifier type and the validation checks.

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 SEDOL before relying on it' is explicit about when to use the tool. However, it does not mention when not to use it or any alternatives among sibling validation tools, which are all different identifier 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 already declare readOnlyHint=true, indicating no side effects. The description adds behavioral context by confirming it 'validates structure only' and detailing what it returns (extension digit, prefix country), which 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 a single, well-structured paragraph that fronts the action directive 'USE THIS to verify'. Every sentence is informative and concise, with no superfluous text.

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?

Without an output schema, the description adequately explains the return values (extension digit, GS1 prefix country) and clarifies that only structural validation is performed. This provides sufficient context for an agent to understand the tool's capabilities.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter 'sscc' with a description covering format and whitespace handling (100% coverage). The description reinforces the 18-digit requirement and mentions the check digit, but adds no new semantic information beyond what the schema 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 clearly states the tool's purpose: verify an SSCC code. It explains what SSCC is, what it checks (check digit, extension digit, prefix country), and that it validates structure only. This distinguishes it from sibling validation tools which are for 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 ... before relying on it', providing clear context for when to use. However, it does not mention when not to use or explicitly compare to alternatives, though the sibling list makes the domain 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. The description adds the important behavioral detail that it checks algorithmic digits and the leading-digit rule, and explicitly states it does not confirm registration. 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: three sentences front-loading the imperative usage, followed by scope details and limitations. 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?

The description covers purpose, limitations, and parameter format well, but lacks mention of the return value or output format. Given no output schema, the agent would benefit from knowing the response structure.

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 the parameter format and that spaces are ignored. The tool description does not add further parameter semantics beyond what the schema already offers.

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 verb 'verify', the resource 'Turkish T.C. Kimlik No', and specifies it checks both algorithmic check digits and leading-digit rule. It also distinguishes that it only validates structure, not registration, making its purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs to use this tool before relying on a TCKN and warns not to assume 11 digits are valid. It does not explicitly mention alternatives, but sibling tools include many other validators, so the context is clear. Missing a 'when not to use' statement.

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 that it checks against the authoritative IANA list and returns valid:false for non-delegated TLDs, providing 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?

The description is extremely concise—two sentences—with no wasted words. It front-loads the purpose and usage instruction effectively.

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 tool is simple with one param and no output schema. The description explains the input, the authoritative source, and the false-case return. It does not fully specify the return format for the true case, but otherwise is complete enough for effective use.

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 already describes the tld parameter. The description adds minimal extra meaning (e.g., leading dot optional), so it does not significantly enhance clarity 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 TLD is real using the IANA list, distinguishing it from guessing. However, it does not explicitly differentiate from the sibling validate_domain, which checks full domains, leaving some ambiguity.

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 this tool before trusting a domain and gives examples of dubious TLDs, providing clear when-to-use context. It lacks explicit when-not-to-use guidance or alternatives like validate_domain.

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 goes beyond the readOnlyHint annotation by detailing the validation algorithm (WHATWG standard, IANA TLD check) and the exact return values (protocol, hostname, port, path, TLD known). 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?

The description is a single, well-structured sentence that conveys all necessary information without wordiness. It is front-loaded with the action and context.

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 tool is simple with one parameter, and the description covers input, behavior, and output completely. No output schema needed due to clear return description.

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 and a single parameter, the schema already explains the parameter well. The description adds context about usage but does not enhance the parameter semantics significantly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'validate', the resource 'URL', and specifies the validation methods: WHATWG URL parsing and TLD IANA suffix check. It also lists return fields, distinguishing it 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?

The description explicitly says 'USE THIS to verify a URL before fetching or storing it', providing clear context. It does not mention exclusions or alternatives explicitly, but the sibling list implies specialization.

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 behavioral context: checks canonical form and returns version, variant, nil UUID status. This is valuable 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-loaded with imperative 'USE THIS', includes an example. 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?

Complete for this simple tool: validates one string parameter, returns metadata. The description explains what it returns, compensating for lack of output schema. 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 the parameter description 'The UUID string to validate.' The tool description reiterates this but adds no new semantic detail. 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 validates UUIDs and extracts version/variant, with a concrete example distinguishing v4 from v7. This differentiates it from sibling validation tools like validate_email or validate_phone.

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' and gives an example scenario, but does not explicitly state when not to use it (e.g., for non-UUID strings). Given the sibling list, 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 already declare readOnlyHint=true. Description adds that it checks format+checksum only, not live registration, which is useful context 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 sentences, well structured and front-loaded with action. Every sentence adds value with no redundancy or 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 adequately explains tool behavior (format+checksum check) and important limitation (not live registered). Among many sibling validation tools, it stands out with clear EU/EFTA scope.

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 both parameters with descriptions (100% coverage). Description adds practical context: full number with country prefix (e.g., DE136695976) or digits plus country code, which helps correct invocation.

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 EU/EFTA VAT registration number format and checksum, with a specific use case (before invoicing or onboarding). It distinguishes from VIES lookup, clarifying it does not confirm live 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?

Explicitly says when to use ('before invoicing or onboarding') and when not to use (for live registration, use VIES lookup). Provides clear guidance on when this tool is appropriate versus 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 already indicate readOnlyHint=true. Description adds detail about specific checks (no I/O/Q, check digit in position 9) and return behavior (expected check digit on failure), enhancing 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?

Two concise sentences, front-loaded with action directive, followed by specifics. No redundant 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?

Covers input requirements, checks performed, and failure output. Could explicitly mention success return value, but adequate given 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 provides high coverage (100%) with description for 'vin' param. Description adds meaning by explaining validation logic (alphabet restrictions, check digit position), going beyond basic parameter 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 it validates a vehicle VIN by checking alphabet and check digit, distinguishing it from sibling validation tools like validate_email or validate_iban.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises use before acting on a VIN and not assuming a 17-character string is valid, providing clear context for when to use the tool.

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