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

No annotations provided, so description carries full burden. Reveals locale-aware formatting (symbol position, separators) but omits details like rounding behavior, precision handling, or error cases. Adequate but not fully transparent.

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 plus an example, efficient and front-loaded with 'USE THIS'. Every sentence adds value.

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

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

For a simple formatting tool with good schema coverage, it covers purpose, usage, and example. Lacks edge case handling description, but overall 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 coverage is 100% with clear parameter descriptions. Description adds value with an example demonstrating usage with currency and locale, though it doesn't significantly extend beyond schema info.

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

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

Description clearly states verb 'format' and resource 'money amount', with specific usage context (before showing in price, invoice, email) and a concrete example. Distinguishes from sibling tools which are mostly 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?

Explicit instructions 'USE THIS' and typical scenarios, but does not explicitly state when not to use or mention alternatives. However, no similar formatting siblings exist, so exclusions are unnecessary.

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

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

No annotations are provided, so the description must cover behavioral traits. It mentions country support and subdivision narrowing but does not disclose the return type (likely boolean), error handling for invalid dates or country codes, or any rate limits or side effects. The description is adequate but leaves some behavioral aspects implicit.

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: the first front-loads the purpose and usage context, the second adds practical details on parameters. Every sentence is necessary and concise, with 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 is simple (3 parameters, no output schema), the description covers the main purpose, parameter details, and usage context. It does not explicitly state the return value (e.g., boolean), but that is implied for a holiday check. It is largely complete for its complexity level.

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

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

Schema description coverage is 100%, so the schema already describes the parameters. The description adds value beyond the schema by providing examples of valid country codes (GB, US, ZA) and subdivision codes (SCT, WLS, NIR, US state), and noting the default for GB. This enhances understanding without being redundant.

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 deadlines, SLAs, or next working day. It specifies the resource (date) and the action (check holiday status), and distinguishes from siblings like 'next_holiday' by context. It also provides concrete use cases and examples of country codes.

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 check...' and gives clear contexts (business-day deadlines, delivery SLAs, next working day). It implies when to use it but does not explicitly state when not to use it or name alternatives like 'next_holiday'. The context is clear enough to guide selection.

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

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

With no annotations, the description carries the full burden. It discloses the supported countries and subdivision narrowing, but omits details on error handling (e.g., no holiday found), return format, or whether it accounts for weekends. The behavior is adequately described for common use 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 two sentences with no extraneous text. It opens with the primary purpose ('USE THIS to find...') and immediately provides an example, making it highly efficient and easy 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?

Given no annotations or output schema, the description covers the main purpose and parameters but lacks details on return value (e.g., date string vs. object) and edge cases (e.g., no holiday found). This leaves some ambiguity for the 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 largely echoes schema fields (e.g., default GB, YYYY-MM-DD format). It adds minor value with examples and context (e.g., 'e.g. GB, US, ZA, DE') but does not provide significant additional meaning beyond the input 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 action (find) and resource (next public/bank holiday), with specific examples like 'find the next working day'. It distinguishes itself from sibling tools like is_holiday by focusing on finding the next holiday 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 advises when to use this tool ('USE THIS to find the next public/bank holiday') and provides a practical example. While it does not explicitly state when not to use it or reference alternatives, the context is sufficient for an agent to infer appropriate 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?

With no annotations, the description should disclose behavior more fully. It mentions returning a confidence flag but omits output structure, error handling, or side effects. It is adequate but lacks detail.

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 (one sentence with bullet-like use cases) and prioritizes key information. It could be slightly more structured, but it is efficient and 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?

Given the lack of output schema, the description fails to specify the return format (e.g., JSON fields) beyond 'confidence flag.' This is a significant gap for a parsing tool, as agents need to know the output structure to use it 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 single parameter 'input' is described in the schema as 'free-text address,' and the description adds value by specifying the expected geographic scope (UK or US) and the extracted fields, which helps the agent format input appropriately.

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

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

The description clearly states the tool extracts structured fields (country, postcode, city, state) from free-text UK or US addresses. It is distinct from sibling validation tools, which check format rather than parse content.

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

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

The description provides specific use cases (onboarding, KYC, storing address) and recommends against manual string splitting. However, it does not explicitly list when not to use it (e.g., non-UK/US addresses) beyond the implied scope.

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 output format (ISO 8601) and failure indicator (valid:false); no annotations so description carries full burden, and it sufficiently covers key behaviors.

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 succinct sentences front-loaded with directive, no wasted words.

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

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

Fully covers the tool's purpose, parameters, and return behavior for a simple parse operation; 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?

With 100% schema coverage, baseline is 3; description adds context on why locale matters with concrete example, enhancing parameter meaning.

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

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

Clearly states verb 'interpret... into ISO 8601' with example of ambiguous dates, 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?

Explicitly advises use for ambiguous numeric dates and instructs passing locale; lacks explicit not-to-use scenarios but siblings are unrelated.

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

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

With no annotations provided, the description carries full burden. It discloses date-sensitivity, handling of historical/temporary changes, US returning 0 for national VAT, and dependence on state code. However, it does not specify the return format (e.g., decimal or percentage) or error behavior, leaving minor gaps.

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 every sentence adding value. It is front-loaded with the critical instruction to use this tool before tax calculations, followed by clear behavior and parameter guidance. No superfluous 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 no output schema, the description covers the tool's purpose, parameters, and usage well. It lacks explicit detail on return values or error handling, but for a tax rate tool the provided information is largely sufficient for correct invocation.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by reinforcing parameter usage: it emphasizes passing the invoice date for GB and clarifies that state is for US sales tax. This contextual guidance improves semantics beyond the schema alone.

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

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

The description clearly states the tool returns tax rates (VAT or sales tax) for GB or US, with date sensitivity and state-specific handling. It distinguishes itself from sibling tools (none are tax-related) and uses specific verbs and resources.

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

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

The description explicitly instructs to use this tool before calculating tax, warns against recalling rates from memory, and provides specific guidance for GB (always pass invoice date) and US (pass state code for sales tax). It clarifies when to use each parameter and implies no alternatives 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?

No annotations are provided, so the description carries the full burden. It clearly states the tool validates structure only (not a lookup), mentions the checks performed, and warns about assuming validity. This adds behavioral insight beyond the schema.

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

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

The description is three sentences, starts with an imperative action, and contains no redundant text. Every sentence adds critical information.

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

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

Given the simple validation tool with one parameter and no output schema, the description adequately covers purpose, validation method, and limitations. It could be more explicit about the return type, but the core completeness is strong.

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

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

The schema has 100% coverage on the single parameter 'aadhaar'. The description adds value by noting that spaces are ignored and emphasizing the 12-digit requirement, which is not explicit in 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 explicitly states the tool verifies format and checksum of an Indian Aadhaar number, naming specific checks (Verhoeff, leading-digit rule). It clearly distinguishes from sibling validation tools by specifying the unique resource and validation scope.

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

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

The description starts with 'USE THIS' and advises not to assume 12 digits are valid, providing clear guidance on when to use. It does not explicitly state when not to use or list alternatives, but the context of sibling tools (many other validators) implies 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?

With no annotations provided, the description takes full responsibility. It discloses that it checks the 11-digit form, performs mod-97 validation, handles the born-from-2000 rule, and validates only structure (not actual registration). This is transparent about its capabilities and 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 consists of two short sentences with no filler. The first sentence is an actionable command for when to use the tool, and the second explains the validation logic. Every word serves a purpose, making it highly efficient.

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

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

Given the tool's simplicity (single parameter, no output schema, no nested objects), the description is fully complete. It covers purpose, validation rules, limitations (structure only), and the special born-from-2000 rule. No additional context is needed for an agent to correctly use this tool.

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

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

Schema coverage is 100%, and the parameter description in the schema already provides basic meaning. The description adds value by clarifying that punctuation is ignored and by detailing the validation steps (11-digit, mod-97, born-from-2000), which goes beyond the schema's minimal 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 purpose: to verify a Belgian National Register Number. It specifies the verb ('verify'), the resource ('Belgian National Register Number'), and distinguishes it from sibling validation tools by naming the specific number type. The phrase 'USE THIS' reinforces its specific purpose.

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

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

The description explicitly says 'USE THIS to verify... before relying on it,' which tells when to use. It also clarifies that it 'Validates structure only,' implying it does not check existence, which is a usage guideline. However, it does not explicitly state when not to use it or provide alternatives, 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?

With no annotations, the description carries full burden. It clearly states it 'Validates structure only,' disclosing that it does not check actual issuance or validity beyond format. This is transparent for a validation tool.

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

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

Two sentences with no filler. Every word contributes meaning. Front-loaded with the key instruction 'USE THIS'.

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

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

For a simple 1-parameter tool with no output schema, the description adequately covers what the tool does and its limitations. No missing information for typical usage.

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

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

The schema already describes the parameter ('10-digit Bulgarian EGN (spaces ignored)'), and description coverage is 100%. The tool description adds the validation method (mod-11 check digit), which provides some added context 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's purpose: verify a Bulgarian EGN. It details what it checks (10-digit form, weighted mod-11 check digit) and clearly distinguishes from sibling validation tools by specifying the country and 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 starts with 'USE THIS to verify a Bulgarian EGN before relying on it,' providing clear when-to-use guidance. It does not explicitly mention when not to use or alternatives, but the sibling tools list implies it's for a specific format.

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 are absent, so the description carries full burden. It discloses it validates structure only, not issuance. It does not mention side effects, return format, or error behavior. For a validation tool, this is acceptable but not complete.

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 'USE THIS', and every sentence adds essential information. 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?

With no output schema, the description should hint at the return value (e.g., boolean). It does not. For a simple validation tool, this is a gap but not critical given the straightforward purpose.

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. The tool description reinforces the format but does not add semantic information beyond the schema (e.g., 'spaces/dots ignored' is already in the schema). Baseline 3 is appropriate.

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

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

The description clearly states the tool verifies a Dutch BSN by checking digit length and the elfproef, and explicitly distinguishes from issuance confirmation. This is specific verb+resource with differentiation from siblings.

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 opens with 'USE THIS to verify a Dutch BSN before relying on it', providing a clear when-to-use directive. It also states what it does NOT do (confirm issuance), which implies when not to use it. However, it does not name alternative tools explicitly.

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

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

With no annotations provided, the description carries full burden. It discloses the validation logic (checksum, SegWit) and explains the meaning of a bad checksum. It does not explicitly state that the tool is read-only or requires authentication, but the context of a validation function implies safety.

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: the first gives a clear imperative on usage, and the second provides necessary technical details. Every word serves a purpose, with no redundancy.

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

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

Given the single parameter and lack of output schema, the description adequately explains what the tool does and returns. It could be improved by describing the output format, but for a simple validation tool, the current description is sufficiently complete.

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

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

The schema covers 100% of parameters, providing a baseline of 3. The description adds significant value beyond the schema by explaining the validation checks performed and what information is returned (address type and network), helping the agent understand the tool's capabilities.

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 Bitcoin address, specifying the address formats it checks (Base58Check, Bech32/Bech32m) and the return information (type and network). It distinguishes itself from sibling validation tools by being specific to Bitcoin addresses.

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

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

The description explicitly tells the AI agent when to use this tool ('before sending funds or storing it') and warns not to assume validity. It does not mention when not to use it, but since there is no alternative Bitcoin address validator among siblings, 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?

With no annotations, the description discloses key behaviors: verifies Luhn, detects brand from BIN, checks length, and states what it does not check. Does not describe output format or error handling, but for a validation tool the behavior is well communicated.

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

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

Two sentences, front-loaded with usage instruction, no wasted words. Efficient and to the point.

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

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

Missing description of return value or output format (no output schema). For a validation tool, agents may need to know what the tool returns (e.g., boolean or result object). Otherwise, the description is specific and complete for its purpose.

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 'number' parameter description already covering spaces/dashes ignored. The description adds context on what validation is performed, but does not add new parameter-specific details beyond the schema.

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

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

The description clearly states the tool checks payment card number structure, verifies Luhn checksum, detects brand from BIN, and checks length. It distinguishes from other validation tools by specifying card-specific checks and what it does not do (real/active/funds).

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 checking card structure before use, and warns against assuming validity or guessing brand. It also clarifies what the tool does not check. No alternatives explicitly named, but sibling context makes this 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?

No annotations provided, but description discloses that the tool only performs structural validation (no real-world verification). Mentions checks on format and check digit, setting clear expectations.

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 filler, front-loaded with purpose. 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?

Tool is simple with one required parameter and no output schema. Description covers what the tool does, its limitations, and how the input is processed, making it complete for an agent to decide invocation.

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

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

Schema description coverage is 100% with parameter details. Description adds that the number starts with 756 and uses EAN-13 check digit, and notes dots are ignored, providing extra 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 the tool validates Swiss AHV/AVS numbers, specifying the format (13-digit starting 756) and EAN-13 check digit. Distinct from many sibling validate_* tools by targeting a specific country and number 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 Swiss social-insurance number... before relying on it', indicating when to use. Notes it only validates structure, implying it does not check existence. No explicit when-not-to-use, but context with siblings makes it 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?

With no annotations provided, the description must fully disclose behavior. It states the tool validates structure (18-character form) and the ISO 7064 MOD 11-2 check character, including that 'X' is allowed. It explicitly notes it does NOT confirm registration. This provides sufficient transparency for a validation tool, though it omits details like rate limiting or side effects (which are unlikely given read-only nature).

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

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

Three sentences with no fluff. The first sentence is an imperative usage instruction ('USE THIS to verify...'), immediately conveying purpose. The second explains the validation algorithm, and the third clarifies limitations. Every sentence adds value, and the structure is front-loaded with the most critical 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?

Given a single parameter, no output schema, and no annotations, the description is complete. It covers what the tool does (structure and check digit validation), what it doesn't do (registration check), and the specific format expected. An agent can confidently decide to use this tool without needing additional 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?

The input schema already describes the parameter well (100% coverage), but the description adds meaningful context beyond the schema: it explains the check character algorithm (ISO 7064 MOD 11-2) and warns against guessing it. This enriches the agent's understanding of what validation occurs, justifying a score above the baseline of 3.

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

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

The description clearly identifies the tool as validating a Chinese Resident Identity Card number (居民身份证). It specifies the action ('verify'), the resource ('Chinese Resident Identity Card number'), and distinguishes itself from sibling tools (e.g., validate_aadhaar for India) by naming the country-specific document. The description also states what it does not do (confirm registration), further clarifying scope.

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

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

The description begins with 'USE THIS to verify ... before relying on it', providing explicit context for when the tool should be invoked. It advises against guessing the check character, reinforcing proper use. However, it does not explicitly mention alternatives or conditions where this tool should not be used, though the sibling list implicitly offers other validation tools for different countries.

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

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

No annotations provided, so description must carry full burden. It discloses the algorithm (mod-11 check digits) and that it replaces blind trust in digits. However, it does not mention return format or side effects (e.g., read-only). Adequate but not comprehensive.

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

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

Two sentences, front-loaded with action and algorithm, followed by usage context. No wasted words; concise and efficient.

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

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

Given a simple single-parameter validation tool with no output schema or annotations, the description covers purpose, method, and context. It could specify the return type (boolean or validation result) but is otherwise 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% with clear description of the single parameter (cnpj as 14 digits, punctuation ignored). The tool description adds no extra 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 it verifies a Brazilian CNPJ using mod-11 check digits. It distinguishes from 'trusting 14 digits' but does not differentiate from sibling validate_cpf (also Brazilian). The verb 'verify' and resource 'CNPJ' are specific.

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

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

Explicitly says 'Call this for onboarding Brazilian businesses', providing a clear use case. While it doesn't specify when not to use, the sibling context of other validate_* tools implies alternatives for different identifiers.

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

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

No annotations present, but description discloses scope (structure validation only) and mentions case-insensitivity and space ignoring. Could be slightly more explicit about return type, but overall transparent.

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

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

Three concise sentences with no fluff, front-loaded imperative 'USE THIS', 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?

Given the simple nature of the tool and no output schema, the description sufficiently covers what the tool does and its limitations. No missing critical information.

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

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

Schema coverage is 100%, and description adds value by noting that spaces are ignored and input is case-insensitive, which is helpful for the agent when constructing 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 clearly states the tool verifies an Italian Codice Fiscale, checking format and check character, distinguishing it from other validation tools by specifying the exact purpose.

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

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

Provides explicit guidance: 'USE THIS to verify... before relying on it' and clarifies 'Validates structure only; does NOT confirm registration,' giving clear context for when to use and limitations.

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

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

No annotations provided, so description must disclose behavioral traits. It mentions checking mod-11 digits and rejecting sentinels, but fails to specify return type (boolean/error) or side effects. Important for an agent to know how to interpret the result.

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 wasted words, clearly structured.

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

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

Usage context is good, but lack of output schema and return type explanation leaves a gap. For a validation tool, the agent needs to know what the tool returns (e.g., boolean, error message) to act correctly.

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

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

Schema coverage is 100%. Description adds value beyond schema by clarifying the CPF is exactly 11 digits and that formatting like dots/dashes is ignored.

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 Brazilian CPF, specifies the check digit algorithm, and gives the context (KYC/onboarding). It distinguishes from sibling validation tools by naming the specific ID 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 tells when to use ('USE THIS to verify a Brazilian CPF before relying on it' and 'Call this for KYC/onboarding of Brazilian individuals'). Lacks explicit 'when not to use' but direction 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?

No annotations are provided, so the description carries full burden. It discloses that the tool checks the check digit and returns the expected digit on failure, but does not specify the return value for a valid CUSIP. This is a minor gap.

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 redundancy. The imperative 'USE THIS' front-loads the key action, making the purpose immediately 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?

For a simple validation tool with one parameter and no output schema, the description is adequate. It explains the verification logic and the outcome when the check digit fails. However, it lacks clarity on the success return value (e.g., true/false), which 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?

Schema coverage is 100% and the description adds context that the CUSIP is a North American securities identifier and includes an example. This adds marginal value beyond the schema's property description, sufficient for a baseline 3.

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

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

The description clearly states the tool's purpose: to verify a CUSIP by checking the mod-10 check digit. It specifies the resource (CUSIP) and the action (verify/check), distinguishing it from sibling validation tools.

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

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

The description instructs to use this tool when you have a 9-character string that might be a CUSIP and need verification. It implies a trust issue with naive 9-character acceptance. While it doesn't explicitly list alternatives, the context of sibling validation tools 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?

Describes what it checks (modern 10-digit mod-11, pre-1954 no check digit) and explicitly states 'validates structure only.' No annotations, so description carries burden; missing info on return format or error handling.

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

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

Two sentences, front-loaded with purpose, no redundant 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 single-parameter validation tool with no output schema, the description covers key behavioral aspects. Could mention return type but not necessary given tool 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 already explains parameter format (10-digit, slash/spaces ignored). Description adds value by explaining the validation algorithm and historical distinction, 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?

Clearly identifies the tool as validating Czech or Slovak rodné číslo (birth number). Specifies the algorithm (mod-11 for modern 10-digit) and distinguishes from many 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?

States to use it before relying on a rodné číslo, but does not explicitly mention when not to use it or suggest alternatives. Usage is implied but lacks exclusion criteria.

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 it validates structure only via ISO 7064 check digit, not registration. No annotations exist, but description provides key behavioral details. Could mention return format but not critical for a validation tool.

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

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

Three short 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?

For a simple validation tool with no output schema, description covers purpose, method, and limitation. Missing return value specification but common for such tools; overall complete enough.

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

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

Schema already describes the 'id' parameter as 11-digit German Steuer-IdNr with ignored spaces/slashes. Description adds context about check digit but not significant extra meaning; baseline 3 is appropriate given 100% schema coverage.

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

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

Description clearly states the tool verifies a German tax ID (Steuer-Identifikationsnummer / IdNr) and validates its structure using ISO 7064 check digit. It distinguishes from siblings by specifying the exact ID 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 to use before relying on the ID and warns that it does not confirm registration, setting clear boundaries on when to use and limitations.

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

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

No annotations provided, so description carries full burden. It states the tool checks a mod-23 control letter and returns document type, but does not describe error handling, return format, or whether the tool is read-only. Behavioral disclosure is adequate but incomplete.

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 command, no extraneous information. 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 tool is simple (1 param, no output schema), the description covers the core functionality. However, it lacks explicit detail about return values (e.g., whether it returns a boolean or a classification string), which would aid an agent in using the result.

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

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

Schema coverage is 100% with a clear parameter description. The tool description does not add additional meaning beyond the schema for the single 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?

Clearly states the tool validates Spanish DNI/NIE documents by checking the mod-23 control letter and classifying the type. The description explicitly distinguishes from sibling validation tools like validate_email or validate_phone by specifying the exact 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?

Provides explicit usage instruction: 'USE THIS to verify a Spanish DNI or NIE before relying on it' and warns against guessing the control letter. However, it does not mention when not to use alternatives or list conditions for using 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?

Discloses that it catches invalid labels and made-up TLDs, and returns TLD and known status. No annotations were provided, but description covers important behavioral aspects.

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

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

Three sentences with no wasted words. First sentence front-loads purpose and usage, second adds detail, third states return 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 complexity (single parameter, no output schema), the description is complete. It explains what it validates, what it catches, and what it returns. 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% for the single parameter, and the description adds meaning by explaining what the tool does with the domain (structure and TLD validation), beyond just the parameter name.

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

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

The description clearly states the verb 'verify' and resource 'domain name's structure and TLD', and distinguishes from sibling tools by specifying it checks TLD against IANA delegation.

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

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

Provides explicit instruction to use this instead of assuming legitimacy, with an example. Lacks explicit mention of when not to use or alternatives, 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?

No annotations are provided, so the description carries the full burden. It states that the tool 'validates structure only', which clarifies it does not check person existence or validity. However, it does not mention whether the operation is read-only or has side effects, though validation tools are typically safe.

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 with two sentences, no fluff, and front-loaded with the usage directive 'USE THIS'. 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?

Given the simplicity of the tool (one parameter, no output schema, no nested objects), the description is complete enough. It explains the validation scope (structure only) and the key algorithm detail. The lack of output schema is acceptable as the return value is implied (boolean).

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

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

The input schema covers the parameter with 100% coverage, describing that spaces are ignored. The description adds meaning by explaining the validation algorithm (two-stage mod-11 check digit), which goes beyond the schema's type and 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 validates an Estonian isikukood (personal identification code), specifying the type of code and the validation performed (11-digit form and mod-11 check digit). This distinguishes it from the many sibling validation tools for other country codes.

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

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

The description explicitly says 'USE THIS to verify an Estonian isikukood before relying on it.', which clearly indicates when to use. It does not mention alternatives or when not to use, but given the sibling list, each tool is for a specific code type, so it is implied.

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

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

With no annotations, the description transparently states it validates syntax and TLD but not deliverability. It does not mention side effects or network calls, but for a validation tool this 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?

The description is concise and front-loaded with the action prompt. No wasted 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?

The description covers purpose and limitations well, but lacks information about the output format (e.g., boolean, object). Given no output schema, this is a minor 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 is 100% with a basic description. The tool description adds value by explaining the validation scope (syntax and TLD), 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's purpose: to validate an email address's syntax and check that the domain TLD is real. It distinguishes itself from sibling validation tools by focusing on email-specific checks and specifying RFC standards.

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... before saving or sending — instead of trusting raw input.' Also clarifies what it does NOT do (deliverability), guiding the agent on 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?

Without annotations, the description fully discloses the tool's behavior: validates format and checksum, returns checksummed form. It also warns about irreversible loss if address is wrong. However, it does not mention error handling (e.g., returns false/throwing error on invalid input), but this is minor given the clarity.

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

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

Two sentences with no wasted words. The critical warning is front-loaded, and every sentence adds essential information about purpose, usage, and outcome.

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 no output schema, the description is fully complete. It covers validation logic, risk, and return value, enabling confident and correct tool invocation.

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

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

Schema coverage is 100% with one parameter described. The description adds significant value beyond the schema by explaining the validation process (EIP-55 checksum) and the output (correctly-checksummed form), which are not in the schema.

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

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

The description clearly identifies the tool as validating Ethereum addresses, specifies the verb 'verify', and explains what it does: validate format and EIP-55 checksum. It distinguishes from siblings like validate_btc_address by being specific to Ethereum.

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 an Ethereum address before sending funds or storing it', and warns against trusting raw strings. It provides clear context for when to use the tool and the consequence of misuse (lost funds).

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

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It clearly states what the tool checks (structure, control digits) and what it does NOT confirm (registration), leaving no ambiguity about its 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), front-loaded with a clear directive ('USE THIS'), and contains zero unnecessary 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?

The description is mostly complete: it explains what the tool validates, what it does not, and when to use it. However, with no output schema, it does not describe the return value (e.g., boolean), which is a minor gap for a validation tool.

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

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

Schema coverage is 100% and the schema already describes the parameter as an 11-digit number with spaces ignored. The tool description adds that it checks mod-11 control digits, but this is about behavior, not parameter semantics. Therefore, the description adds minimal value beyond the schema, meriting a baseline 3.

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

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

The description clearly states the tool verifies a Norwegian fødselsnummer, checks the 11-digit form and both mod-11 control digits, and explicitly distinguishes from other validation tools by specifying the country 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?

The description explicitly says 'USE THIS to verify ... before relying on it', providing clear context for when to use the tool. However, it does not mention alternatives or when not to use it, though the sibling tools are all for different identifiers, so the name already distinguishes.

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

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

With no annotations provided, the description carries full burden and discloses that the tool validates structure only (not real-world validity), handles Corsica numbers, and checks the key. It does not describe the return format, which is a minor gap.

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 an imperative directive ('USE THIS'), no redundant information, and 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?

For a simple validation tool with one parameter and no output schema, the description covers essential aspects: purpose, scope, and structural checks. It could mention the return type, but given low complexity, it remains complete enough.

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

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

Schema coverage is 100% with parameter description stating the format. The description adds meaning by explaining what parts of the NIR are validated and mentioning Corsica handling, which goes beyond the schema.

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

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

The description clearly states the tool validates French social-security numbers, specifies what it checks (13-digit body, mod-97 key, Corsica handling), and distinguishes it from sibling validation tools by targeting a specific national ID.

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

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

Explicitly says 'USE THIS to verify a French social-security number before relying on it', providing clear context for when to use. It does not explicitly state when not to use or compare to sibling tools, but the name and description imply it's for French NIR only.

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

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

With no annotations, the description carries the full burden. It discloses the algorithmic nature (check digit validation), describes the output (issuing country), and explicitly states what it does not do (confirm registration). This provides good insight into behavior, though it could mention if any external calls or auth are needed (likely none).

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 zero wasted words. It front-loads the usage instruction ('USE THIS to verify...'), then details what it does and its 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?

For a simple validation tool with one parameter and no output schema, the description covers everything needed: what it validates, how (check digit), what it returns (country), and limitations (structure only, not registration). No gaps.

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

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

The schema has 100% coverage with a decent description. The tool description adds valuable context: defines GLN as 'GS1 Global Location Number' and explains its purpose in supply chains and EDI. This extra context clarifies the parameter's 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 verb 'verify' and the resource 'GLN'. It specifies exact operations: checks 13-digit GS1 mod-10 check digit and returns issuing country. Distinguishes from siblings by specifying it validates GLN structure only, not registration status.

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 the tool 'before relying on a GLN', providing clear when-to-use guidance. It also states that it validates structure only, not registration, which implies limitations. However, it does not explicitly mention when not to use or compare to alternative tools, though sibling tools cover 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?

With no annotations provided, the description carries full burden. It discloses that validation is structural only, not a real-product check, and mentions the output includes barcode type and country. It does not directly state that the operation is read-only or side-effect-free, but that is implied. Good transparency overall.

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 three sentences each serving a purpose: imperative instruction, technical details, and a limitation. No unnecessary words, and front-loaded with the key directive.

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

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

Given the simplicity (one param, no output schema), the description is quite complete. It covers purpose, supported formats, validation logic, output elements, and a limitation. It could mention the exact return type, but the description is sufficient for an agent to invoke correctly.

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

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

The single parameter 'gtin' is fully described in the schema. The description adds value by noting that spaces and hyphens are ignored, which is not in the schema. This enhances usability.

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 'product barcode — GTIN/EAN/UPC', and lists the specific formats handled (EAN-8, UPC-A, EAN-13, GTIN-14). It distinguishes itself from sibling validation tools by focusing on barcodes, not 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 product barcode... instead of guessing the check digit', providing a clear when-to-use. It also warns that it validates structure only, not real product registration. However, it does not explicitly compare to or exclude sibling tools like validate_isbn, though the name and context are 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?

With no annotations, the description fully informs the agent: it only validates structure (format and check digit) and does not verify real-world existence. The breakdown of components (DDMMYY, century sign, etc.) clarifies what is checked. This is sufficient for a validator tool.

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

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

The description is two sentences, immediately front-loading the imperative 'USE THIS' followed by the purpose. The second sentence provides necessary technical detail. No wasted 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?

For a simple one-parameter validator with no output schema, the description is complete: it explains the input, the validation logic, and the limitation ('structure only'). No missing information 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?

The schema describes the 'hetu' parameter with an example. The description adds structural details (DDMMYY + century sign + individual number + mod-31) which help the agent understand valid input beyond syntax. Schema coverage is 100%, so this 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?

The description clearly states the tool's purpose: 'verify a Finnish henkilötunnus (HETU / personal identity code)'. It specifies the exact components validated (DDMMYY + century sign + individual number + mod-31 check character) and contrasts with guessing. This is a specific verb-resource pair that distinguishes 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 instructs to use this tool 'before relying on it' and warns against guessing the check character. While it doesn't list when not to use, the context of sibling validators implies it's for Finnish HETU only. The guidance is clear and actionable.

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

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

No annotations are provided, so the description fully carries the burden. It discloses that the tool performs structural validation (format and check digit) and does not perform lookup or live checks. This is transparent for a simple validation tool.

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

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

The description is two sentences with no wasted words. It front-loads the purpose and provides essential details 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?

For a simple validation tool with one parameter and no output schema or annotations, the description adequately covers what the tool does. It could be improved by specifying the return type (e.g., boolean), but the current description is sufficiently complete.

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

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

Schema description coverage is 100%, and the parameter description in the schema already states '11-digit Croatian OIB (spaces ignored).' The tool description does not add additional meaning beyond what the schema provides, so a baseline score of 3 is appropriate.

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

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

The description clearly states the tool verifies a Croatian OIB, specifies what it checks (11-digit form and ISO 7064 MOD 11,10 check digit), and notes it validates structure only. This distinguishes it from sibling validation tools for other IDs.

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 tool before relying on a Croatian OIB, providing clear context. However, it does not mention when not to use it or suggest alternatives, though the sibling tools cover different ID types, making the usage 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?

Describes validation logic (country, length, checksum) and return values. No annotations to contradict; description adds value beyond no annotations.

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

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

Two sentences, no fluff. First sentence gives imperative use, second lists checks and outputs. Very 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?

For a single-parameter validation tool with no output schema, the description fully covers what it does, how it validates, and what it returns. 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 already fully describes the parameter (100% coverage). Description does not add new parameter-level detail beyond schema, so baseline 3.

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

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

Clearly states it validates IBAN, specifies checks (country, length, checksum) and outputs (country, check digits, BBAN). Distinguishes from 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?

Explicitly says 'USE THIS to verify an IBAN' and 'Call this whenever a user supplies a bank account'. Provides clear context, though missing explicit exclusions for 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?

With no annotations provided, the description carries full burden. It discloses key behaviors: Luhn check digit validation, IMEISV recognition, TAC extraction, and the explicit limitation that it does not verify device existence or blocklist status. This gives the agent a clear behavioral model.

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 the first sentence acting as an imperative front-load. Every word adds value: usage instruction, core function, and clear limitations. 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?

For a single-parameter validation tool with no output schema, the description is fully complete. It explains input format, validation algorithm, output (TAC), and limitations. The agent has all necessary context to use the tool correctly.

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

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

Although schema coverage is 100% (only one parameter), the description adds crucial semantics beyond the schema: it specifies the expected length (15 or 16 digits) and clarifies that spaces/dashes are ignored. This helps the agent format input correctly.

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, check, returns') and clearly identifies the resource (IMEI). It distinguishes from sibling tools by explicitly stating what it does NOT do (check device real/active/blocklisted), setting it apart from other validation tools.

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

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

The description begins with a strong usage directive ('USE THIS to verify...') and clarifies the tool's scope by listing exclusions (does not check device status). While it doesn't name specific alternative tools, the context of sibling validation tools makes the niche 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?

No annotations are provided, so the description fully carries the burden. It details strict checking behavior, RFC compliance, leading zero rejection, IPv6 compression support, and that it returns the version. This is comprehensive.

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

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

The description is two sentences long, front-loaded with 'USE THIS,' and contains no extraneous information. Every word 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?

Given the tool has a single required parameter and no output schema, the description explains the input, behavior, and return value (version) completely. 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% (only one parameter 'ip' with description). The description does not add new semantics beyond what the schema provides, meeting the baseline for high coverage.

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

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

The description clearly states the tool validates IP addresses, specifies it checks both IPv4 and IPv6 with strict rules (RFC references, rejection of invalid formats), and returns the version. This distinguishes it from sibling validation tools.

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

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

The description explicitly advises to use this tool before relying on an IP address, implying a verification use case. It does not list alternatives, but the context of sibling tools (all other validation types) makes the usage 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 explains the verification actions (checking prefix and check digit) and what happens on failure (returns expected check digit). However, it does not specify the return value on success or error handling. Given no annotations, the description adds moderate behavioral context but misses some details.

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

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

The description is two concise sentences, front-loaded with the primary action, and contains no redundant words. Every sentence serves a purpose.

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

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

The description covers the tool's core behavior, failure output, and compares to 'trusting digits.' For a simple validation tool with one parameter and no output schema, it is nearly complete. Minor gap: does not state success return type, but this is inferable.

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 parameter description that allows hyphens/spaces. The tool description reinforces that and adds context about validation logic, but does not significantly augment parameter meaning beyond the schema. Baseline of 3 is appropriate.

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

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

The description clearly states that the tool verifies an ISBN-13 identifier, distinguishing it from the sibling tool 'validate_isbn10' by specifying ISBN-13. It mentions specific checks (prefix and check digit), making the purpose explicit and unique.

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 indicates when to use the tool ('USE THIS to verify...') and implies it should be used instead of trusting raw digit strings. While it does not explicitly mention the sibling 'validate_isbn10' for ISBN-10, the context from sibling tools provides clear differentiation. The guidance is adequate but lacks explicit exclusions.

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

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

Describes the validation mechanism (mod-11 check digit, includes 'X') but doesn't explicitly state it's read-only or non-destructive; however, the context implies a simple check.

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, no wasted words.

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

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

For a simple validation tool with one parameter, the description fully covers purpose and behavior; 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 covers 100% of parameters, and description adds context about check digit logic beyond schema.

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

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

The description clearly states the tool verifies ISBN-10 using mod-11 check digit and distinguishes from sibling 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 tells when to use (ISBN-10) and when not (13-digit, use validate_isbn), with clear alternative.

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

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

With no annotations, the description discloses that it checks format, Luhn digit, and returns country code. This provides useful behavioral traits beyond the input schema, though it could mention whether it makes external calls or if it's purely local.

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 fluff. Every sentence adds value: motivation, action, and trigger condition.

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 simple validation tool with one parameter and no output schema, the description covers all necessary aspects: purpose, input constraints, checks performed, and output. 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% (single parameter with description and example). The description adds no extra meaning for the parameter itself; it only elaborates on output behavior. Baseline 3 is appropriate as schema already carries the burden.

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 ISIN identifiers, checking format and Luhn check digit, and returning country code. The verb 'verify' and resource 'ISIN' are specific, and the tool is distinct from siblings by name and description.

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 call when a user supplies a security/instrument identifier and warns against assuming validity. While it doesn't name alternatives, the context suggests using this for ISIN specifically; missing explicit when-not-to-use but overall 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?

No annotations are provided, but the description fully discloses behavior: checks mod-11 check digit, mentions possible 'X' digit, and states return value on failure. 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 imperative, no wasted 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?

For a simple validation tool with one parameter and no output schema, the description fully explains purpose, algorithm, and return behavior. 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 'issn' parameter. The tool description adds the context of '8 chars; hyphen ignored' which matches the schema, but does not add significant new meaning beyond what 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?

Description clearly states the tool verifies an ISSN, explains the mod-11 check digit validation, and what it returns on failure. Distinguishes from sibling validation tools by naming the specific identifier type 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?

The phrase 'before relying on it' implies when to use, but there is no explicit guidance on when not to use or alternatives among the many sibling validation tools. The context is implied by the tool name.

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

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

With no annotations, the description carries full burden. It discloses the check digit validation method but does not specify the output format (e.g., boolean) or any side effects. Additional details would improve transparency.

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

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

The description is two sentences long, front-loaded with an imperative, and contains no superfluous words. Every sentence serves a purpose.

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

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

Given the simple input and no output schema, the description covers the tool's purpose and method. However, it lacks explicit mention of the return value (e.g., boolean), which would make it fully 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% with a parameter description, but the tool description adds value by explaining the purpose of the check (verifying LEI validity using ISO standards) and cautioning against assuming validity, which goes beyond the schema.

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

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

The description clearly states it verifies an LEI by checking ISO check digits, using specific verbs like 'verify' and 'checks'. It distinguishes from sibling validation tools by focusing on LEI.

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 instructs to use this tool before relying on an LEI, providing clear context. However, it does not mention when not to use it or alternatives 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?

No annotations are provided, so the description carries full burden. It discloses that it 'validates structure only', meaning it does not check against a government database, which is critical behavioral information.

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, no 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?

For a simple validation tool with one parameter and no output schema, the description is complete. It explains what is validated (format and check digit) and the limitation (structure only).

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 description 'The 18-character CURP (case-insensitive)'. The description adds that it checks the check digit and structure, but this is behavioral, not parameter-specific. Baseline of 3 is appropriate.

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

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

The description clearly states it validates a Mexican CURP, checks the 18-character format and base-37 check digit. It distinguishes itself from sibling validators by name and specific details.

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 tells when to use ('verify a Mexican CURP before relying on it') and what not to do ('do not guess the check digit'). It does not mention alternatives, but the context of sibling validators makes usage 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 mod-11 check digit validation. No annotations present, so description carries burden. Could mention it is read-only/idempotent, but sufficient for a simple validation tool.

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

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

Two sentences with no fluff: first sentence gives action and context, second adds algorithm and sibling reference. Information is front-loaded and efficient.

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

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

Covers purpose, usage context, algorithm, and sibling differentiation. Lacks explicit return value description, but reasonable given typical validation tool behavior and no output schema.

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

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

Schema already describes parameter well (100% coverage). Description adds purpose and algorithm context beyond schema, aiding interpretation.

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?

Uses 'verify' verb with specific resource 'Portuguese NIF', explicitly distinguishes from sibling 'validate_dni' for Spanish tax ID. Clear and unambiguous.

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

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

States exactly when to use ('before invoicing or onboarding'), warns not to assume 9 digits valid, and provides explicit alternative for Spanish tax ID.

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 algorithm (ISO 7064 MOD 11-2), mentions acceptance of bare ID or URL, and notes the check digit may be 'X'. With no annotations, it provides good behavioral context beyond the schema, though return value 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, front-loaded with 'USE THIS', no unnecessary words. Every sentence provides 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 (one parameter, no output schema), the description covers the essential aspects: what it does, input format, and validation logic. It could mention the return type, but overall it is sufficiently complete.

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

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

Schema already has a good description for 'orcid' (100% coverage), but the description adds value by specifying acceptance of both bare ID and URL and detailing the check digit logic.

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

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

Clearly states it verifies an ORCID researcher identifier and checks the ISO 7064 MOD 11-2 check digit. It is specific and distinct from sibling validation tools, which cover 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 says 'USE THIS to verify an ORCID researcher identifier instead of trusting 16 digits', providing clear context for use. It does not list exclusions or alternatives, but the purpose 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?

With no annotations, the description fully handles behavioral disclosure: it confirms the input format, the Luhn check, and the limitation of not verifying registration. 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 clear imperative tone; critical information (use case, format, check type, limitation) is front-loaded and concise with no filler.

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

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

For a single-parameter tool with no output schema, the description covers purpose, usage, behavioral details, and limitations comprehensively. 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 already describes the parameter well (100% coverage), but the description adds the Luhn check detail and reinforces accepted formats, providing additional semantic value.

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

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

The description clearly states it validates a Swedish personnummer, checks structure and Luhn digit, and does not confirm registration. This differentiates it from sibling validation tools for other countries and 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?

Explicitly advises using this tool before relying on a personnummer, and clarifies it only validates structure, not registration. However, it does not mention alternatives among siblings, though context implies it is the only Swedish-specific 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?

Discloses that it checks the weighted mod-10 check digit, which is the core behavior. No annotations provided, so the description carries the burden. It does not mention error handling or return format, but for a simple validation tool, this 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?

Three sentences with no wasted words. The first sentence is an imperative instruction, front-loading the 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?

Given the simple input (one required string) and no output schema, the description is complete. It covers what the tool does, when to use it, and a key input constraint (ignored spaces/dashes).

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 description for 'pesel.' The description adds context: 'never assume 11 digits are valid' and notes that spaces/dashes are ignored, which goes beyond the schema.

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

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

Description explicitly states it validates a Polish PESEL (national identification number) and checks the weighted mod-10 check digit. It clearly distinguishes from sibling tools by specificity to Poland and PESEL.

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?

Advises use 'before relying on it' and specifically for 'KYC/onboarding of Polish individuals.' While it doesn't list when not to use or name alternatives, the context is clear given the tool name and sibling list.

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

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

No annotations provided, so description carries full burden. It clarifies what 'valid' means (conforms to numbering plan, not live line) and mentions output formats. However, it does not explicitly state read-only or side-effect status, though implied by validation purpose.

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

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

Three sentences with no waste. The first sentence front-loads the core instruction and purpose. 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?

For a 2-parameter tool with no output schema and no annotations, the description provides purpose, usage guidelines, meaning of validity, and output return types. It is sufficient for an agent to use the tool correctly without additional 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 important context beyond schema: it emphasizes the region parameter's critical role in correctness and explains that 'number' is the phone number. This adds value over the schema alone.

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

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

The description clearly states the tool validates and normalizes phone numbers to E.164 format, using specific verbs 'check' and 'normalise'. It distinguishes from sibling validation tools by being phone-specific, and the 'USE THIS' imperative clarifies its domain.

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 check...' and gives a mandatory guideline: 'You MUST pass the ISO country the number ACTUALLY belongs to.' It also clarifies the prerequisite for region and warns against reusing unrelated country fields.

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

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

With no annotations provided, the description fully discloses the tool's behavior: it checks a weighted mod-11 check digit and validates structure only. It does not hide any limitations. There is no contradiction with annotations as none exist.

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, immediately stating the purpose and the key algorithm. It is front-loaded with an imperative tone ('USE THIS'), and every word serves a purpose. No unnecessary information.

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

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

For a simple validation tool with one parameter and no output schema, the description covers the core functionality and its limitation. It is mostly complete, though it omits what the tool returns (e.g., boolean or validation result). Given the simplicity, the gap is minor.

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 only parameter 'cnp' is fully described in the schema (13-digit Romanian CNP, spaces ignored). The description adds no additional semantic meaning beyond what the schema provides. According to the rules, since schema coverage is 100%, the baseline score 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 specifies the tool's purpose: to verify a Romanian CNP by checking its weighted mod-11 check digit. It distinguishes from sibling validation tools by explicitly naming the algorithm and stating 'validates structure only.' The directive 'USE THIS ... before relying on it' reinforces its specific role.

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

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

The description explicitly states when to use ('before relying on a CNP') and implies limitations ('validates structure only'), guiding the agent away from using it for identity verification. However, it does not mention alternatives or explicitly say when not to use it, though the sibling tool names provide 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?

Discloses both what the tool does (9-digit weighted mod-10 checksum) and its limitation (does not check if bank or account is real), which is critical for proper use.

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 usage 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?

For a simple validation tool with one parameter and no output schema, the description covers purpose, what it checks, what it doesn't, and usage 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 already documents the routing parameter as 'The 9-digit ABA routing number.' The description adds no extra semantic meaning beyond reaffirming the 9-digit format and referencing the checksum, which is behavioral 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 states the tool verifies a US bank routing/ABA transit number using a checksum, distinguishing it from sibling validation tools targeting other entities (e.g., email, card, 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?

Begins with 'USE THIS to verify...' explicitly stating when to use it, but does not mention alternatives or when not to use 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?

With no annotations, the description fully carries the burden. It details input checks (Luhn, DOB) and output (DOB, gender, citizenship). Does not mention error handling or possible side effects, but for a read-only 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?

Two well-structured sentences. The first imperative sentence immediately states the tool's purpose, and the second explains functionality. 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 a simple single-parameter tool without output schema or annotations, the description provides all necessary information: what it does, what checks it performs, and what it returns. 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% for the single parameter 'id', and the description reinforces its purpose and format. Adds context about what the tool does with the parameter, but not additional semantic detail beyond the schema.

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

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

The description clearly states the tool validates a South African ID number, with specific checks (Luhn, DOB) and returns encoded data. It distinguishes itself from many sibling validation tools targeting 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 'USE THIS to verify a South African ID number before relying on it', providing clear context for use. Could be improved by explicitly stating not to use for other countries, but the sibling context implies this.

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

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

No annotations provided, so description carries full burden. It discloses the validation algorithm ('no-vowels alphabet and weighted mod-10 check digit'), which is sufficient for a read-only validation tool.

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

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

Two concise sentences: an imperative usage instruction followed by the validation details. No wasted words.

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

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

For a simple validation tool with one parameter and no output schema, the description adequately explains what it does and what it checks. It does not mention return format but that is typical for such tools.

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

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

Schema coverage is 100% and the parameter description in the schema is identical to the tool description ('The 7-character SEDOL, e.g. B0YBKJ7'). Description adds no new information 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?

Description clearly states the verb 'verify' and the specific resource 'SEDOL (LSE securities identifier)', 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?

Description explicitly says 'USE THIS to verify a SEDOL before relying on it', providing clear context. It does not explicitly mention alternatives but is implied by the specific resource name.

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

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

No annotations provided, so description must disclose behavior. It explains that it checks the check digit, returns extension digit and GS1 prefix country, and validates structure only. This is sufficient transparency for a validation tool.

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

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

Two sentences, front-loaded with 'USE THIS'. No unnecessary 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?

No output schema, but description states return values (extension digit, GS1 prefix country). Also clarifies scope ('validates structure only'). Complete for a simple validation tool.

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

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

Input schema has 100% description coverage for the single parameter. The description repeats the schema's description exactly (ignoring spaces/dashes). Thus, no additional meaning beyond schema, baseline 3.

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

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

Clearly states it verifies an SSCC from a shipping label and defines the acronym. Distinguishes from sibling validation tools by specifying the exact code type and its context.

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

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

Explicitly says 'USE THIS to verify... before relying on it.' Provides clear when-to-use guidance. Does not state when not to use, but specificity implies it is not for other codes.

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

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

No annotations provided; description fully discloses validation scope (structure only, not registration) and parameter handling (spaces ignored). No hidden behaviors.

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?

One sentence, front-loaded imperative ('USE THIS'), all words essential. No redundancy.

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

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

For a single-parameter validator with no output schema or annotations, description covers purpose, usage, behavior, and parameter. Nothing missing.

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

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

Single parameter 'tckn' with schema description 'The 11-digit TCKN (spaces ignored).' Description adds 'spaces ignored' beyond schema, clarifying input flexibility.

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 TCKN, specifies checks (algorithmic check digits, leading-digit rule), and explicitly states what it does NOT confirm (registration). Distinguishes from siblings as a structural validator.

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?

Advised to use before relying on TCKN, with warning not to assume validity. Lacks explicit when-not-to-use or alternatives, but context among sibling validators makes usage 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?

Without annotations, the description discloses that checks are against the IANA root-zone list, kept current, and returns valid:false for non-delegated TLDs. It does not discuss idempotency or side effects, but for a validation tool, these are sufficiently transparent.

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 'USE THIS', and contains no extraneous words. Every part serves a purpose: examples, authoritative source, and expected return 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 the tool has one parameter and no output schema, the description fully covers the input, process, and output. It explains what it validates, against which source, and what the result means, leaving no gaps.

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

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

The tool description adds examples of TLDs to check but the parameter schema already fully describes the 'tld' parameter (with/without leading dot). Schema coverage is 100%, so the description provides marginal extra 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?

The description clearly states the tool validates whether a top-level domain is real using the authoritative IANA root-zone list, providing specific examples like .zip and .corp. It distinguishes itself from siblings like validate_domain by focusing on TLDs alone.

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 'USE THIS to check whether a top-level domain is real before trusting a domain or link — do NOT guess' which provides strong when-to-use guidance. However, it does not mention alternatives or specific when-not-to-use scenarios, though siblings like validate_domain imply a different scope.

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

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

No annotations are provided, so the description carries full burden. It discloses the parsing standard (WHATWG), TLD check via IANA suffix list, and lists the return fields (protocol, hostname, port, path, TLD known). This provides sufficient behavioral insight.

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 key action ('USE THIS to verify...'), and concise. Every sentence adds value, no wasted words.

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

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

Given a single parameter and no output schema, the description is fairly complete: it explains what the tool does, how it validates, and what it returns. It lacks discussion of error handling or edge cases, but for a simple validation tool this is acceptable.

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

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

Schema coverage is 100%, with the schema already describing the 'url' parameter. The description adds no extra parameter-level meaning beyond the schema; it explains the validation logic but not parameter specifics. Baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose: to verify a URL before fetching or storing it, using the WHATWG URL standard and checking TLD against IANA suffixes. This is specific and distinct from sibling tools like validate_domain or validate_email.

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 URL before fetching or storing it', providing clear usage context. It does not explicitly exclude alternatives, but the sibling context implies each tool has its own validation 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?

No annotations are provided, so description is the sole source. It describes what the tool does (checks canonical form, returns version/variant/nil), but does not disclose error behavior, return format, or any side effects. Adequate but not comprehensive.

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 excess words. Every sentence adds value. Perfectly concise and structured.

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

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

For a simple validation tool with one parameter and no output schema, the description covers the key functional aspects: what input it expects, what it checks, and what it returns. Could be improved by noting error behavior, but sufficient for typical 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 provides a description for 'uuid' parameter. Description adds that it checks the 'canonical 8-4-4-4-12 form', which adds format detail beyond the schema. With 100% schema coverage, this extra info is valuable.

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, read) and resource (UUID). It explains the purpose of distinguishing UUID versions, which is specific to UUIDs. Sibling tools are other validators but the description's focus on UUID version/variant differentiates it well.

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 explicitly says 'USE THIS to verify a UUID' and gives an example use case. It does not mention alternatives or when not to use, but the tool name and context of many sibling validators imply it's for UUID only. Strong guidance overall.

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?

Without annotations, the description carries the full burden. It states that the tool performs format and checksum validation only, not a live VIES lookup. It also clarifies the scope (EU/EFTA + UK). No destructive behavior is mentioned, and the note about passing full number or separate country code explains parameter behavior. A slightly higher score could be justified, but there is no mention of output format or error handling.

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

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

The description is concise, using two sentences plus a note. It is well-structured, starting with an imperative 'USE THIS' to grab attention, followed by the action, scope, and limitations. Every sentence serves a purpose with no redundancy.

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

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

Given the tool's simplicity (no output schema, no nested objects, 2 parameters), the description is complete. It covers what the tool does, its scope, its limitations, and parameter usage. No additional information is needed for correct invocation.

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

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

The input schema has 100% description coverage, so the baseline is 3. The description adds value by explaining how to use the parameters: 'Pass the full number incl. country prefix... or the digits plus a country code.' This clarifies the relationship between the two parameters and provides concrete examples, enhancing usability.

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 an EU/EFTA VAT registration number's format and checksum. It specifies the action (verify), the resource (VAT number), and the context (before invoicing or onboarding). It also distinguishes itself from a VIES lookup by noting what it does not do, ensuring no confusion with sibling validation tools.

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

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

The description explicitly says 'USE THIS to verify... before invoicing or onboarding a business' and tells when not to use it (i.e., not for live registration checks). It provides clear guidance on the intended use case and constraints, setting expectations for the agent.

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

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

With no annotations, the description fully bears the burden of transparency. It discloses that it checks the allowed alphabet (no I/O/Q) and the ISO 3779 check digit in position 9, and returns the expected check digit when validation fails. It does not state whether the operation is read-only or if there are side effects, but the disclosed internal logic is sufficient for understanding tool 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 fluff. The first sentence is front-loaded with an imperative action, and every clause provides valuable information. It perfectly balances brevity and informativeness.

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

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

For a simple one-parameter validation tool with no output schema, the description provides enough context: it explains what the tool does, what checks it performs, and what it returns on failure. It does not specify the return value on success, but that is typically implied (true or valid). Given the sibling context of many validation tools, the description sufficiently equips an agent to use it correctly.

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

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

Schema coverage is 100% (single parameter with description 'The 17-character VIN to validate'). The description adds context beyond the schema by clarifying that the VIN is for a vehicle and that the tool performs specific checks. This added meaning justifies a score above the baseline of 3.

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

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

The description clearly states the verb 'verify' and resource 'vehicle VIN', and distinguishes it from other validation tools by specifying that it checks the allowed alphabet (no I/O/Q) and the ISO 3779 check digit. It explicitly instructs to 'USE THIS to verify a vehicle VIN before acting on it', leaving 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?

The description provides explicit when-to-use guidance ('before acting on it') and warns against assuming a 17-character string is valid. It does not explicitly name alternatives, but the sibling list of many validate_* tools implies that other identifiers should use the respective tool. A clear 'when not to use' or explicit alternative naming would improve it.

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