mcp-server

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

The description claims to 'generate a similarity key,' implying a non-destructive read operation. However, the annotations set destructiveHint to true, creating a contradiction. The description does not clarify any destructive behavior, nor does it explain side effects, authorization needs, or error conditions. The cost information is useful but insufficient.

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: purpose, outcome, and cost. No redundant wording. The key action and use case are front-loaded, making it easy for an AI agent to quickly grasp the tool's function.

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 2 simple parameters and no output schema, the description adequately explains the output (a similarity key) and the use case. It omits details like return format or error handling, but given the tool's simplicity, the description is largely 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 input schema covers 100% of the 2 parameters with descriptions. The description adds minimal extra meaning: 'US or international' for address and 'Full individual name' for fullname. This provides slight context beyond the schema, meeting the baseline expected 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 it generates a combined similarity key from full name and address for high-precision household/contact-level deduplication. This is a specific verb-resource pair that distinguishes it from sibling tools like interzoid_fullname_match or interzoid_address_match_advanced.

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 mentions the use case: 'high-precision household/contact-level deduplication.' It does not mention when not to use or alternative tools, but the context is clear and appropriate for the intended purpose.

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

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

Annotations include destructiveHint=true and readOnlyHint=false. The description adds cost transparency ($0.01 USDC) and confirms the tool generates a key without modifying input, which supplements the destructive annotation without contradiction.

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

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

The description is two concise sentences, front-loading the primary purpose and adding cost info in the second. Every word serves a purpose with no waste.

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

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

With no output schema, the description does not specify the return format or practical use of the similarity key. It adequately covers parameter behavior but misses output details, leaving the agent partially uninformed.

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

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

Schema coverage is 100%. The description adds context beyond schema by explaining the tool handles unit numbers, directionals, and abbreviations, and that it produces an AI-powered similarity key, enhancing understanding of how parameters contribute to the output.

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

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

The description clearly states the tool's function: generating an advanced AI-powered similarity key for US street address matching. It specifies handling of unit numbers, directionals, and abbreviations, and distinguishes it from siblings like interzoid_address_parse and interzoid_global_address_match by focusing on US addresses and advanced matching.

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

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

The description implies usage for US address matching requiring fuzzy logic, but lacks explicit guidance on when to use this tool versus siblings or when not to use it. No alternatives or exclusions are mentioned.

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

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

The description states 'Parse' which implies a read-only operation, but annotations set destructiveHint=true, indicating a potential side effect or mutation. This contradiction undermines transparency. The description adds cost info but fails to clarify the nature of the operation.

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

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

Two concise sentences: one for purpose, one for cost. No extraneous information, efficiently front-loaded.

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

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

The description lists output components, partially compensating for missing output schema. However, it lacks details on output format, error handling, or when to use the tool. Given low complexity, it is fairly 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%, so the parameter 'address' is already described. The component list in the description is output-oriented and does not add meaning to the input parameter beyond what the schema provides.

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

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

The description specifies 'Parse a full address string into component parts' with a clear verb and resource, listing the parts (street number, street name, unit, city, state, zip code). It is distinct from sibling tools like 'interzoid_address_and_fullname_match'.

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?

No guidance is provided on when to use this tool versus other address-related siblings. The description only mentions cost, not context for selection.

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

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

Annotations set readOnlyHint=false and destructiveHint=true, but description describes a read operation ('Retrieve'). This is a direct contradiction. Description does not disclose other behavioral traits besides cost.

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 listing fields and cost; front-loaded with purpose. Efficient but no structural formatting (e.g., bullets) that could improve readability.

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

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

No output schema provided, despite returning many fields. Contradiction with annotations and lack of usage guidance make the description incomplete for an AI agent to fully understand behavior.

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

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

Schema describes the single parameter 'address' as 'US property street address'. Description adds 'any US property address' but no significant extra meaning. Baseline 3 due to 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 verb 'Retrieve' and the resource 'commercial building profile' for a US property address, listing many specific fields. However, it does not explicitly differentiate from sibling tools like interzoid_property_history.

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?

No guidance on when to use this tool versus alternatives. Only mentions 'Premium API' and cost, lacking any context for 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?

The description claims it is a retrieval operation ('Retrieve'), which implies read-only and non-destructive behavior, but the annotations set destructiveHint=true, indicating the opposite. This is a direct contradiction. No other behavioral traits (e.g., rate limits, response format) are disclosed beyond the annotations.

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

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

The description is extremely concise with two sentences: one for purpose and one for cost. It is front-loaded, with no unnecessary words or repetition, effectively communicating the tool's value proposition.

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

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

The description covers the main return fields (industry, revenue, employee counts, executive info) but lacks details on output format, any limitations (e.g., geographic scope, data freshness), and prerequisites. For a paid tool with a single parameter, the basics are present but depth is 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?

Schema coverage is 100% with the single parameter 'lookup' already documented as 'Company name, website, or email'. The description does not add any additional semantic detail about the parameter, so it meets the baseline without improvement.

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 'Retrieve' and the resource 'comprehensive AI-powered business intelligence for a company', listing specific data types like industry, revenue, employee counts, and executive info. This distinguishes it from the many sibling tools that focus on more narrow domains such as address matching or company verification.

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 no guidance on when to use this tool versus the many siblings, such as interzoid_company_verification or interzoid_executive_profile. The only usage clue is the cost mention, which may discourage casual use, but it fails to explicitly state when to choose this over alternatives.

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

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

Description states 'identify' implying read-only behavior, but annotations set destructiveHint=true, indicating possible side effects. This contradiction misleads the agent about the tool's side effects. Additionally, no mention of credit consumption beyond cost.

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: first explains functionality with examples, second notes cost. No filler, front-loaded, 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?

The description covers the tool's purpose and cost, but lacks details about return format or pagination. For a simple one-parameter tool with no output schema, this is fairly 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?

With 100% schema coverage, the description adds no meaning beyond the schema's 'Target company name'. Baseline of 3 is appropriate as the schema already documents the parameter fully.

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 identifies recent buying signals for a target company, listing specific examples like funding events and hiring trends. This distinguishes it from sibling tools that focus on matching, parsing, or profile lookups.

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 mentions it's a premium API with cost, but does not explicitly guide when to use this tool versus alternatives like interzoid_business_info or interzoid_competitor_analysis. Usage is implied but lacks exclusions or comparisons.

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

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

Annotations indicate destructiveHint=true, but the description portrays the tool as a harmless standardization process without mentioning side effects. The cost info adds transparency, but the contradiction between description and annotations reduces 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?

The description is very concise: two sentences front-loading purpose and key features. Every word adds value, 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 simplicity of the tool and the presence of annotations, the description covers basic functionality and cost but omits return format and potential side effects hinted by annotations.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the schema provides, merely restating the purpose.

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 with a specific verb 'standardize' and resource 'city name data'. It details handling of abbreviations, alternate spellings, and local variations, making the functionality distinct from siblings like interzoid_state_abbreviation or interzoid_country_standard.

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

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

The description implies use for city name standardization but does not explicitly guide when to use this tool over siblings. No exclusions or alternatives are mentioned, relying on the tool name for context.

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

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

The description contradicts the annotations: it describes a key-generation operation, which is non-destructive, but annotations set destructiveHint to true. No disclosure of the discrepancy is provided, and the tool's openWorldHint is not explained. This is a clear annotation contradiction.

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

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

The description is three sentences long, front-loaded with the primary action, and includes a cost note. Every sentence adds value without redundancy.

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

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

The description covers the purpose and use case but omits details about the return format (e.g., string key) and behavioral aspects like idempotency or determinism. Given the low complexity (2 params, no output schema), it is adequate but not fully comprehensive.

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 both parameters well (coverage 100%). The description adds no new information about parameter formats, constraints, or examples beyond what the schema provides. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool generates a combined similarity key from company name and street address, using a specific verb and resource. It explicitly targets business-location deduplication, distinguishing it from siblings like interzoid_company_match_advanced or interzoid_address_match_advanced by focusing on the combined entity.

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 a clear context ('ideal for business-location deduplication across vendor, supplier, and account datasets') but does not explicitly state when not to use the tool or name alternatives. This is sufficient but not exhaustive.

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?

Annotation destructiveHint=true conflicts with description of generating a key (non-destructive). No explanation of 'destructive' behavior, permissions, or other traits. Contradiction noted.

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: purpose, use case, cost. No fluff, front-loaded with action.

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 and use case; lacks output format details (no output schema). For a simple key generator, adequate but not exhaustive.

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

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

Schema coverage is 100%, so baseline 3. Description adds minimal meaning beyond schema (e.g., 'full individual name' vs 'Full individual 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 tool generates a key from company and fullname for deduplication. It distinguishes from siblings by combining both inputs, but does not explicitly name alternatives.

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 mentions ideal use case (contact-level deduplication in CRM/marketing/sales) but lacks when-not-to-use or explicit alternatives.

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

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

Annotations show destructiveHint: true and readOnlyHint: false, while the description describes generating a key (seemingly read-only). The cost disclosure adds transparency, but the mismatch with destructiveness is not fully resolved. No mention of failure modes or rate limits.

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

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

Three sentences, each providing essential information: what the tool does, example names, and cost. No filler or redundancy.

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

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

No output schema, so the description lacks return format details. The tool is simple, but with destructiveHint true, more context about side effects would be beneficial. Adequate for a straightforward matching function.

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 both parameters are described in the schema. The description adds a small example ('ai-deep') but does not significantly enhance understanding beyond the schema.

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

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

The description states the specific action: 'Generate an advanced AI-powered similarity key for company/organization name matching.' It gives concrete examples (IBM, International Business Machines, IBM Corp) and distinguishes it from sibling tools that handle other matching or data lookups.

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

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

The description implies usage for deduplication and record linkage, which is clear context. It also mentions the cost, but does not explicitly state when not to use or point to alternatives. However, the sibling list is large, so the tool's purpose is reasonably distinct.

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 indicates a non-destructive lookup (verify existence), but annotations set destructiveHint=true, which contradicts. No other behavioral traits (rate limits, idempotency) are disclosed.

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

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

The description is concise (two sentences), front-loaded with the core action, and includes essential cost information. No unnecessary words.

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

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

The description explains the output (score 0-99 with AI reasoning) and cost, which is sufficient for a simple tool. However, the contradiction with destructiveHint undermines completeness, and idempotency is not addressed.

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

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

Schema coverage is 100% with the parameter 'lookup' described as 'Company or organization name to verify'. The description adds context about the verification score but does not provide additional semantics beyond the schema.

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

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

The description clearly states the tool verifies company existence and provides a verification score with AI reasoning. It distinguishes from siblings by focusing on existence verification rather than other business info or matching.

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 mentions it is a Premium API with a cost ($0.25 USDC), implying usage when payment is acceptable. However, no explicit guidance on when not to use or alternatives among sibling tools is provided.

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

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

The description adds cost information ($0.25 USDC via x402) and notes it's a premium API, which is beyond the annotations. However, it does not clarify the 'destructiveHint: true' annotation or elaborate on side effects, rate limits, or authentication requirements.

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: first explains purpose, second adds cost. No redundant words, front-loaded with the core action.

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

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

Given one parameter and no output schema, the description adequately explains the input and what the output includes (market positioning, products, competitive advantages) and adds cost context. Could mention authentication implicitly, but it's sufficient.

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

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

Schema coverage is 100% for the single parameter 'lookup', and its description in the schema ('Company name to analyze competitors for') already conveys the meaning. The tool description adds no further parameter details, so baseline 3 is appropriate.

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

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

The description clearly states the verb ('Identify and analyze') and the resource ('a company's primary competitors'), and distinguishes this tool from its many siblings by focusing on competitor analysis rather than address matching, company info, etc.

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

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

The description implies usage for analyzing competitors but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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 provides no indication of side effects, while annotations set destructiveHint=true, creating confusion. The cost note is helpful, but behavioral traits beyond annotations are missing.

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 cover the essential purpose and cost with no redundancy, making it highly concise.

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

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

The description lists return fields (ISO codes, currency, etc.) but lacks details on output format, error handling, or rate limits, leaving some gaps despite the tool's simplicity.

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

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

Schema coverage is 100% and the description adds that country names can be in any language and algorithm defaults to 'ai-medium', but these match the schema descriptions; no additional meaning is provided.

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 standardizes a country name and returns comprehensive info (ISO codes, currency, internet code, calling code), distinguishing it from similar tools like interzoid_country_standard and interzoid_currency_rate.

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

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

The description implies usage for retrieving country details but does not explicitly state when to use or avoid this tool versus alternatives, leaving guidance to the 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?

The description adds behavioral context via cost disclosure ($0.01 USDC via x402) but does not address the destructiveHint annotation (true) or explain side effects. The openWorldHint and idempotentHint are not discussed. Some useful behavior is added, but gaps remain.

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 exceptionally concise with only two sentences, no redundant information, and places the core purpose first. 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 tool has no output schema, but the description implies the output is a standardized country name. It covers cost and purpose well. However, it lacks explanation of error handling or algorithm variant effects, and the behavioral transparency gap reduces completeness slightly.

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

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

The input schema has 100% coverage, with clear descriptions for both 'country' and 'algorithm' parameters. The description does not add significant meaning beyond the schema, such as format or constraints, 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's function: 'Standardize a country name to a consistent canonical form.' It provides specific examples like 'Great Britain', 'UK', 'United Kingdom', which differentiates it clearly from siblings such as 'interzoid_country_info' that deal with information rather than standardization.

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

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

The description gives clear context on when to use the tool (standardizing country names with variations) and mentions the cost. However, it does not explicitly state when not to use it or mention alternative tools, though the sibling list helps differentiate.

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

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

Annotations indicate destructiveHint: true and readOnlyHint: false, which strongly suggest the tool modifies state. However, the description describes a read-only retrieval ('Get live currency exchange rates', 'Returns current mid-market rates'), creating a clear contradiction. The description fails to explain the potential destructive side effects or why these annotations 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 (15 words) with zero redundancy. It efficiently conveys the core function, return value, and cost. Every word earns its place.

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

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

The tool is simple with two string parameters and full schema coverage. The description mentions the return type ('current mid-market rates') but does not detail the output structure (e.g., JSON fields). Given no output schema, this is a minor gap. Annotations add contradictory context, reducing 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% with adequate descriptions for both parameters (e.g., 'Source currency code (e.g. USD, EUR, GBP)'). The description does not add extra meaning beyond the schema, meeting the baseline for full 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 gets live currency exchange rates between two currencies and returns mid-market rates. The verb 'Get' and specific resource 'live currency exchange rates' are explicit. This tool is distinct from all sibling tools, which cover other data domains.

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

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

The description implies when to use (when needing live exchange rates) but does not explicitly state when not to use or mention alternatives. Given the list of siblings, there is no other currency rate tool, so confusion is unlikely, but the description could be more precise.

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

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

Annotations include destructiveHint=true and openWorldHint=true. The description adds context about cost implications ('Premium API, cost varies by model') and the custom nature of data, providing transparency beyond annotations. It does not contradict annotations.

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

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

The description is concise: two sentences plus an example. It is front-loaded with the most important information and wastes no words.

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

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

Given the tool's complexity (4 parameters, no output schema), the description covers the essential: purpose, parameters, example, and cost. It could include error handling or response format details, but it is adequate for understanding the tool's 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 description coverage is 100%, so the baseline is 3. The description adds an example and clarifies that 'output' is a JSON array, but this is minimally additive to the schema descriptions. The parameters are well-documented, but the description does not significantly enhance 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?

The description clearly states the tool's purpose: 'Define your own data API' with specific parameters (topic, lookup, output). It distinguishes itself from sibling data enrichment tools by emphasizing custom, self-defined fields and provides an illustrative example.

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 explains the tool's usage through an example and notes it's premium and cost varies. However, it lacks explicit guidance on when to use versus alternatives (e.g., when you need predefined data vs. custom fields) and does not mention 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?

The description adds cost and premium API info, but it states 'Retrieve', implying a read-only operation, while annotations set destructiveHint=true. This contradiction reduces transparency. No additional behavioral details (e.g., side effects, rate limits) are provided.

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 composed of two concise sentences. The first sentence lists all relevant data points in a clear structure, and the second adds cost information. There is no wasted 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?

The description lists the types of rates and restrictions returned, which is helpful given the lack of an output schema. However, it does not mention the format or potential errors, leaving minor gaps. Overall, it provides sufficient context for a premium API 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%; both parameters have descriptions in the input schema. The description does not add further semantics beyond what is already in the schema, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool retrieves import customs duty rates for any HS code and destination country, listing specific rate types (MFN, FTA, VAT/GST, etc.). It uses a specific verb 'Retrieve' and resource 'customs duty rates', effectively distinguishing it from sibling tools that handle addresses, companies, etc.

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

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

The description explicitly states when to use the tool: to retrieve customs duty rates for any HS code and country. It provides context but does not discuss when not to use or alternative tools. However, the specificity of the tool's function makes its 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?

Annotations include destructiveHint=true and readOnlyHint=false, yet the description uses 'Get' which implies a read-only, non-destructive operation. This contradicts the annotations, making it misleading. The description does not disclose the behavioral trait of being potentially destructive or non-idempotent.

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 covering purpose, capabilities, and cost. No fluff, front-loaded with the main action. 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 single-param tool with no output schema, the description gives a solid overview of functionality and cost. It lacks details on the output format, but the high schema coverage compensates. The contradiction with annotations is the main 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 clear parameter description. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states it gets an email trust score (0-99) and AI-generated risk analysis, with specific capabilities like validating deliverability and identifying disposable addresses. It distinguishes itself from siblings which cover different data lookups.

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 context about the tool being a premium API with a cost, implying it's for important or high-stakes email validation. It does not explicitly note when not to use it or suggest alternatives, but siblings are clearly different types of data.

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

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

The description adds cost information ($0.01 via x402), which is helpful. However, it does not address the annotation `destructiveHint: true`, which contradicts the non-destructive nature of classification. Annotations already provided, but the description misses clarifying this inconsistency.

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

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

The description is very concise, consisting of two sentences that immediately convey the tool's purpose and cost. Every sentence adds value without redundancy.

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

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

Given the simplicity of the tool (one parameter, no output schema), the description covers what it does and the cost. However, it falls short by not describing the output format or providing guidance on interpreting results, 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% with a basic parameter description. The tool description adds no further meaning beyond the schema, 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's function: determining the entity type of a data value (person, company/organization, location, or other). This specific verb+resource combination distinguishes it from sibling tools that perform different data enrichment tasks.

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 lacks guidance on when to use this tool versus alternatives. It does not mention prerequisites, limitations, or scenarios where it is appropriate. With many sibling tools, explicit usage context would be beneficial.

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 implies a read-only operation ('Retrieve'), but annotations set destructiveHint: true, creating a contradiction. This misleads the agent about potential side effects. Additionally, no other behavioral traits are disclosed.

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

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

Two concise sentences with no extraneous information. Every word adds value, clearly stating purpose, included data points, and cost.

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

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

Given one parameter and no output schema, the description provides basic context but lacks details on return format, error handling, or rate limits. Adequate but minimal for a premium API.

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

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

Schema coverage is 100% with adequate description for the single parameter 'lookup'. The description adds no additional meaning beyond the schema.

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

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

The description clearly states the tool retrieves an ESG profile including specific components. However, it does not differentiate from sibling tools like business_info or company_verification, which might also provide company data.

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?

No guidance on when to use this tool versus alternatives. The mention of 'Premium API' and cost is not usage context. Lacks explicit when/when-not or alternative tool references.

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 says 'retrieve' implying a read operation, but annotations set destructiveHint=true, a contradiction. It mentions cost but does not clarify the destructive nature.

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

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

The description is concise with three front-loaded sentences, each adding value: purpose, premium claim, and cost.

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

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

The description covers the main use case and output details adequately for a single-parameter tool without output schema, though response format is omitted.

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

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

The description adds meaning beyond the schema by specifying acceptable lookups (European countries) and output content (categories, thresholds), enriching the single parameter's context.

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

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

The description clearly states the tool retrieves current VAT rates for European countries, specifying the scope and output details. It distinguishes from sibling tools by focusing on VAT rates for Europe.

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

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

The description implies usage when European VAT rates are needed but does not explicitly compare to alternatives or state when not to use it.

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

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

The description states 'Retrieve', indicating a non-destructive read operation, but the annotations set 'destructiveHint: true', which contradicts the description. This is a significant inconsistency that confuses the agent about the tool's side effects. Additionally, the cost is noted but not reflected in annotations.

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

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

The description is concise at two sentences, front-loading the core purpose. The cost information is extra but relevant for an agent making decisions. Every sentence earns its place, though the description could be slightly more 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?

Given the tool has no output schema and limited annotations, the description provides some context on output content ('leadership details, roles, and professional background') but does not explain return format, error handling, or whether results are guaranteed. Adequate but not comprehensive.

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

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

With 100% schema description coverage, the input schema already fully documents the single parameter. The description adds no additional meaning beyond what is in the schema, so the baseline score of 3 is appropriate.

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

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

The description uses the verb 'Retrieve' and specifies the resource as 'executive profile information' including leadership details, roles, and background. It clearly distinguishes from sibling tools by focusing on executive profiles rather than general company info, though does not explicitly contrast with alternatives like 'interzoid_company_verification'.

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?

Mentions that it is a 'Premium API' with a specific cost ($0.25 USDC via x402), which signals that it should be used judiciously and when cost is acceptable. However, no explicit guidance is given on when to use this tool versus siblings, nor 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?

The description states 'Retrieve', implying a read operation, but annotations indicate destructiveHint=true and readOnlyHint=false, directly contradicting the description. No additional behavioral details are provided.

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

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

Two sentences, no waste. First sentence gives the core purpose, second adds cost context. Could be more structured but remains 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 what the tool returns (facility types) but lacks output schema and details on response format. Adequate but not comprehensive.

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 the parameter 'lookup' described as 'Company name to retrieve facilities profile for'. The description adds no extra 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 uses a specific verb 'Retrieve' and resource 'profile of a company's corporate facilities' with detailed examples of facility types, clearly distinguishing it from sibling tools.

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

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

The description mentions cost ('Premium API. Cost: $0.25 USDC via x402.') but provides no guidance on when to use this tool versus alternatives, nor any conditions or 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?

The description discloses cost ($0.01 USDC via x402), a behavioral trait beyond annotations. Annotations declare destructiveHint=true, which aligns with the cost implication. No contradiction. The description adds value by clarifying the non-idempotent nature (charging per call).

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: first states core purpose, second provides concrete examples and pricing. Every sentence earns its place with no fluff or redundant information.

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

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

Given only one parameter and no output schema, the description covers the tool's function, examples, and cost. It does not explain the key format or usage beyond matching, but it is sufficient for an agent to decide to invoke. Slightly incomplete regarding return values but 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 description coverage is 100%. The parameter 'fullname' is described as 'Full individual name' in the schema. The description adds overall context (handles variations, produces a key) but does not specify format or constraints beyond the schema's brief description. 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 uses a specific verb ('generate') and resource ('similarity key for individual/person name matching'), and includes examples ('Bob Smith', 'Robert Smith', etc.) that clearly distinguish it from siblings like interzoid_fullname_match_score which likely returns a score.

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 states the tool is for handling name variations and generating a matching key, but does not explicitly advise when to use it vs. alternatives (e.g., interzoid_fullname_match_score). Usage context is implied but not fully explicit.

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 portrays a read-only operation (compare names, return score), but annotations set 'destructiveHint: true', suggesting possible side effects or state changes. This contradiction undermines transparency. Cost disclosure is helpful but not sufficient.

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

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

The description is extremely concise: two sentences, no fluff. The first sentence defines the primary action and output, making it efficient for quick comprehension.

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

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

For a simple comparison tool with only two parameters and no output schema, the description provides necessary context: similarity score range, handling of variations, and cost. Missing details about error handling or response format, but adequate given low complexity.

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

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

The schema provides 100% coverage with descriptions for both parameters. The description adds useful context that the tool handles nicknames and abbreviations, enhancing understanding beyond raw 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 compares two names and returns a match score from 0-100, handling nicknames and abbreviations. It distinguishes from the sibling 'interzoid_fullname_match' by including 'score' in the name, implying a numeric output.

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 does not explicitly state when to use this tool vs alternatives like 'interzoid_fullname_match'. It mentions cost, which may imply usage considerations, but lacks direct guidance on tool selection.

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

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

The description adds cost information ($0.01 via x402) and international support. However, it does not disclose potential side effects or response format. Annotations indicate destructiveHint=true, which seems mismatched but not directly contradicted.

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 only two sentences, front-loaded with the core purpose, and includes additional useful information (international support and cost) without unnecessary details.

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 tool with one parameter and no output schema, the description lacks details about the return format (e.g., male/female/unknown). It is adequate but not 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?

The input schema covers the parameter with a description, and the description adds that the tool supports international names, enhancing the semantic meaning beyond the schema's 'first name' label.

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 verb 'determine' and resource 'gender' associated with a name. It clearly states the tool's purpose and distinguishes it from siblings like interzoid_name_origin by focusing on gender.

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 mentions support for international names but does not provide explicit guidance on when to use this tool versus alternatives, nor does it state when not to use it.

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

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

Annotations already indicate non-read-only and destructive behavior. The description adds useful context: it is AI-powered, handles international formats, and costs $0.01 USDC. No contradiction with annotations.

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

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

Three concise sentences: first states purpose, second adds context, third mentions cost. No unnecessary words, well 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?

For a simple tool with one parameter and no output schema, the description covers purpose, scope, and cost. Could mention return format of the similarity key, but not essential.

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

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

Schema description coverage is 100% with a clear description for the 'address' parameter. The tool description repeats the parameter name but adds no extra semantic meaning beyond the schema.

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

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

The description clearly states the tool generates a similarity key for global/international address matching, using a specific verb. It distinguishes from siblings by focusing on global addresses, but does not explicitly differentiate from similar address 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 implies usage for international address matching but does not specify when not to use it or mention alternative tools. No explicit exclusions or conditions are provided.

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

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

The description claims to 'measure' page load performance, implying a read operation, but annotations set destructiveHint=true, which contradicts the read-only nature. The description does not explain potential side effects (e.g., making an HTTP request to the target URL) nor the cost mechanism beyond a brief mention. This contradiction undermines trust.

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

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

Three sentences: first defines action and result, second details return values, third lists use cases and cost. No wasted words, logically structured, and front-loaded with the core purpose.

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

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

For a simple measurement tool with two parameters and no output schema, the description covers the core functionality, return values, use cases, and cost. Lacks details on prerequisites, error handling, or rate limits, but is largely sufficient 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 input schema already provides 100% coverage with clear descriptions for both parameters (url and origin). The description adds no additional parameter-level information, sticking to describing the return value. 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 measures real-world page load performance (response time) for any URL from a chosen global location. The verb 'measure' and resource 'page load performance' are specific, and the tool is easily distinguished from its siblings which focus on addresses, business info, weather, etc.

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

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

The description notes usefulness for global latency monitoring, CDN validation, and uptime/performance checks. It does not explicitly state when not to use or compare to alternatives, but given the sibling tools are entirely different domains, the usage context is clear. Mentioning cost provides some practical guidance.

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

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

The description describes a read-only operation, but annotations set readOnlyHint=false and destructiveHint=true, creating a contradiction. The description does not clarify or correct this.

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: one for functionality, one for cost. No unnecessary words, well-structured.

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

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

Lists expected output fields (temperature, conditions, wind speed), which is helpful given no output schema. Missing details on response format or errors, but adequate for a simple tool.

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

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

Schema coverage is 100% with description for 'location'. The tool description adds 'any city worldwide', providing useful scope beyond the schema's example list.

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 retrieves current weather for any city, listing specific outputs (temperature F/C, conditions, wind speed). No sibling tool offers weather data, so differentiation is inherent.

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

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

The description implies use for weather queries but does not provide explicit guidance on when to use this tool versus alternatives or any conditions for 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?

The description states 'Retrieve' which suggests a read-only operation, but the annotations set 'destructiveHint: true', indicating potential mutation or destruction. This is a direct contradiction. No additional behavioral context is provided to resolve the inconsistency.

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 conveys the core purpose, the second adds pricing context. It is front-loaded and concise, with no redundant information. However, it could be slightly more structured to separate purpose from cost.

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 only one parameter, no output schema, and annotations that conflict with the description, the description fails to fully explain the tool's behavior. The destructive hint is unexplained, and the return format is not mentioned. For a paid API, more detail on what the output contains would be beneficial.

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

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

The input schema already provides full coverage (100%) for the single parameter 'lookup' with a description. The tool description does not add any additional semantic meaning beyond what is in the schema, so baseline score of 3 is appropriate.

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

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

The description clearly specifies the action: 'Retrieve US government contract information for a company.' It lists example data points (active contracts, agencies, contract values, award history), making the resource and scope explicit. Sibling tools cover different domains, so this tool is well-distinguished.

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

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

The description implies usage context (for government contract data) and mentions it's a premium API with cost, but does not provide explicit guidance on when to use this tool versus alternatives, nor any when-not criteria. The implied usage is sufficient but not thorough.

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

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

Annotations already indicate it's not read-only and is destructive (likely due to cost). The description adds cost information ($0.01 USDC via x402), which is useful beyond annotations. However, other behavioral traits like output format are missing.

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 clear front-loading of purpose. The second sentence adds value by noting support for numerous languages. The third sentence adds cost info. No wasted words.

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

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

Given the simple input and lack of output schema, the description is adequate but lacks specifics on supported languages or output format. It provides enough context for basic use but could be more 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% for the single parameter 'text'. The description adds no additional meaning beyond what the schema already provides for the parameter.

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

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

The description clearly states the tool's purpose: 'Identify the language of a given text string.' It uses a specific verb and resource, and distinguishes from sibling tools like translation or address matching.

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?

No explicit guidance on when to use this tool versus alternatives. There is no mention of context, prerequisites, or when not to use it.

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

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

Description implies a read-only query (identify/categorize), but annotations set destructiveHint=true, creating a contradiction. No explanation of the destructive behavior or whether it modifies data. Cost disclosure is helpful but insufficient to resolve the inconsistency.

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, clear and front-loaded. 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?

Despite no output schema, the description lists expected outputs (NAICS, SIC, sector, etc.). However, the destructiveHint contradiction is unresolved, and no mention of error handling or rate limits.

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 'lookup' has schema coverage 100%, and the description repeats the schema's description ('Company name to classify'). Does not add meaning beyond the schema.

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

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

The description clearly states the tool's purpose: 'Identify and categorize a company's primary industry classification with standardized NAICS and SIC codes, sector and subsector details, business activity description, and a confidence score.' This is specific and distinct from sibling tools (e.g., company matching, verification).

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?

No guidance on when to use this versus sibling tools like interzoid_business_info or interzoid_company_verification. The only context is the cost and premium nature, but no usage scenarios or 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?

The description claims a read-only action ('Get'), while annotations indicate destructiveHint=true and readOnlyHint=false, suggesting potential write or destructive behavior. This contradiction undermines trust, and the description does not clarify the discrepancy. The cost info adds value but fails to address behavioral traits disclosed by annotations.

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

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

The description is two sentences, front-loaded with purpose and key details, followed by cost context. 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?

For a single-parameter tool with no output schema, the description covers purpose and included data, but lacks details on output format, error handling, or authentication. The cost mention is helpful but not fully complete for a premium API.

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

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

There is only one parameter with a schema description ('IPv4 or IPv6 address to profile'), achieving 100% coverage. The description adds no further parameter information, so it meets but does not exceed the baseline.

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 verb (Get), resource (comprehensive profile for an IP address), and includes specific details like geolocation, ISP, organization, CIDR block, and reputation assessment. It is distinct from sibling tools, none of which focus on IP profiling.

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 mentions it's a 'Premium API' with a cost, implying usage consideration, but does not explicitly state when to use it versus alternatives or provide exclusions. The context is clear but lacks direct guidance for tool selection.

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

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

Annotations indicate destructiveHint=true, and the description reinforces this by stating 'Premium API. Cost: $0.25 USDC via x402', disclosing the financial cost. The description also adds behavioral info about classifying locations as High-Cost/Low-Cost with separate components. No contradiction with annotations.

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

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

The description is two sentences plus a cost line, all front-loaded. The first sentence states the action and resource, the second adds classification details, and the third notes pricing. Every sentence earns its place with no extraneous 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?

Given the simple one-parameter input and no output schema, the description adequately conveys the tool's behavior and output (classification with lodging and M&IE components). However, it does not detail exact return fields or error handling, which could be beneficial for a paid API.

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

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

The input schema covers 100% of the single parameter with a description. The tool description repeats that the lookup can be a full address, ZIP, city, county, or state (CONUS), adding little beyond the schema. However, the schema description already provides the same information, so there is no extra value, meeting the baseline.

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 'Retrieve' and the resource 'IRS high-low method per diem rates for any US location', and specifies the purpose 'to support accountable-plan travel reimbursement (Revenue Procedure 2019-48)'. It also distinguishes from siblings by describing the unique classification into High-Cost/Low-Cost with lodging and M&IE components, which no other tool does.

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 this tool: for retrieving IRS per diem rates for US locations for travel reimbursement. It cites the specific revenue procedure, providing clear context. However, it does not explicitly mention when not to use this tool or list alternatives among siblings, but given the niche functionality, this 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?

While annotations indicate destructive and non-idempotent behavior, the description says 'retrieve', implying a read-only operation, which is partially clarified by mentioning cost. However, it lacks explicit disclosure of side effects beyond cost.

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 core purpose, and every word contributes meaning without redundancy.

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

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

For a simple single-parameter tool, the description covers its operation, output, and cost. It could be improved by noting error handling or issuer not found scenarios, but overall it is 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?

The input schema covers the single parameter fully, and the description adds value by detailing the output fields, giving the agent a clear expectation of what the tool returns.

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 retrieves a research profile on US municipal securities issuers and lists specific data points (issuer type, credit standing, etc.), distinguishing it from siblings that focus on addresses, companies, or other domains.

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 context by specifying the scope (US municipal issuers) and cost (Premium API, $0.25 USDC), but does not explicitly state when not to use or mention alternatives.

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

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

Description discloses the cost ($0.01 USDC via x402), which is a behavioral trait beyond the annotations. Annotations already indicate destructiveHint=true, so the cost information adds specific value.

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: the first defines purpose, the second adds use cases and cost. No wasted words, information is front-loaded.

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

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

The description explains purpose and cost but lacks information about the return format or error behavior. Given the absence of an output schema, this is a notable gap for a simple lookup tool.

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

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

Schema coverage is 100% with a clear parameter description ('Full name to determine origin for'). The tool description adds no additional semantic value beyond using the word 'individual', which is already implied by 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 the action: 'Determine the likely cultural or geographic origin of an individual name.' The verb-resource combination is specific and distinct from sibling tools, which cover addresses, companies, and other data domains.

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 provides clear usage context ('demographic analysis and internationalization'), but does not specify when not to use this tool or mention alternatives among the many sibling tools.

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

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

Annotations include destructiveHint=true, which contradicts the tool's non-destructive purpose. The description does not clarify any destructive behavior or other side effects. The cost mention adds some transparency but fails to address the contradiction.

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

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

Two concise sentences with no superfluous information. 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 simplicity (one parameter, no output schema), the description adequately states what is returned. However, it lacks specifics like distance units or limitations, which are minor 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%, and the description adds no new meaning beyond the existing parameter description. Baseline score of 3 applies.

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

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

The description clearly states the tool finds nearest coffee shops to an address, including names, addresses, distances, and details. This is a specific verb+resource and is distinct from sibling tools like address match or company info.

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 mentions it is a Premium API costing $0.25 USDC via x402, indicating paid usage. While it doesn't explicitly state when to use vs siblings, the tool's purpose is clearly different from siblings.

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

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

Annotations indicate destructiveHint=true and readOnlyHint=false, suggesting potential mutation, but the description does not clarify if the API modifies data. It mentions 'Premium API' implying cost but no further behavioral context beyond what annotations provide.

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

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

The description is two sentences, front-loading the purpose and listing outputs concisely with 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?

The description covers purpose, inputs, outputs (list of specific fields), and use cases. Given the lack of output schema, it adequately describes return values, though format details are 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?

The description adds significant meaning beyond the schema by specifying acceptable input forms: common name, brand, abbreviation, ticker, local-language name, or near-match with typos. Schema coverage is 100%.

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 resolves organization names to official English legal names and other details, listing specific outputs and use cases (KYB, supplier verification, sanctions screening). It distinguishes from sibling tools by focusing on official name resolution.

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 use cases (KYB, supplier verification, sanctions screening, dataset normalization) but does not specify when not to use or suggest alternative tools. This is clear but lacks 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?

The description discloses the cost ($0.01 USDC), which is a behavioral trait beyond annotations. However, it does not explain the destructiveHint true annotation or idempotentHint false. Annotations already cover read-only and destructive hints, so the description adds limited context.

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

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

The description is very concise with two sentences. The first sentence front-loads the primary action, and every sentence adds value. No wasted words.

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

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

With no output schema, the description implies the return is a match score but does not specify the exact format (e.g., JSON). It lacks details on error handling or edge cases. For a simple tool, it is adequate but not 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% and both parameters are clearly described in the schema. The description adds no extra meaning beyond stating they are organization names, so baseline 3 applies.

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 compares two organization names and returns a match score from 0-100. It uses a specific verb, resource, and outcome, and distinguishes from siblings like address or fullname matching 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 provides a use case ('determining if two company names refer to the same entity') but does not mention when not to use it or compare to alternative siblings like interzoid_company_match_advanced. Guidance is implied rather than explicit.

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 says 'Standardize' which implies a non-destructive transformation, but annotations mark destructiveHint=true and readOnlyHint=false. The mention of cost via x402 hints at mutability, but no details on side effects. This contradiction reduces 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?

Two sentences effectively convey the purpose and an example. No wasted words, front-loaded with the core action.

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

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

The description explains what the tool does and gives a cost hint, but with no output schema, it omits what the return value looks like (e.g., is it just the standardized string?). This is a notable gap for a simple tool.

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

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

The lone parameter 'org' is described in the schema, but the tool description adds semantic context: it normalizes abbreviations, suffixes, and formatting with an example. This adds value beyond the schema's bare parameter description.

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

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

The description clearly states it standardizes organization names to canonical form, with normalization of abbreviations and suffixes. The example 'b.o.a.' -> 'Bank of America' demonstrates the behavior. This distinguishes it from siblings that handle addresses, companies, or other entities.

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?

No guidance on when to use this vs other org-related tools like interzoid_company_match_advanced or interzoid_org_match_score. It mentions cost but not usage context or alternatives.

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

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

Description implies a read-only operation (retrieve), but annotations set destructiveHint=true, creating a contradiction. Additionally, no behavioral details like prerequisites or side effects are disclosed.

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

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

Two concise sentences plus cost line; front-loaded with purpose and immediately useful 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?

Lacks usage guidelines, output description, and fails to resolve the annotation contradiction. Cost information is helpful but insufficient for 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 covers the single parameter completely; description adds no extra meaning beyond the schema definition.

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

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

The description clearly states it retrieves parent company information and identifies corporate ownership hierarchies, which distinctly sets it apart from sibling tools like company verification or match.

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?

No guidance on when to use this tool versus alternatives; cost is mentioned but not usage 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?

Description indicates a read operation ('Get profile'), but annotations have destructiveHint: true and readOnlyHint: false, contradicting the description. The cost disclosure is the only transparency, but the contradiction is severe.

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 and output details, followed by cost information. Every sentence adds value without redundancy.

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

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

For a simple one-parameter tool, the description adequately covers inputs and key outputs. However, lacks information on error handling, rate limits, or response structure (no output schema provided).

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

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

Schema has 100% description coverage for the single 'lookup' parameter. Description adds no further detail about the parameter beyond what is 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?

Description clearly states 'Get profile for a phone number' and lists specific fields (carrier, line type, geographic location, etc.). This uniquely identifies the tool among siblings, none of which are phone profile 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?

Mentions premium cost ($0.25), implying cautious use, but does not provide explicit when-to-use or when-not-to-use guidance, nor alternatives.

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

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

There is a clear contradiction: the description states 'Retrieve' (read operation) while annotations set destructiveHint=true, implying possible side effects. This inconsistency undermines transparency. Additionally, no further behavioral details (e.g., authentication, rate limits) are provided beyond the annotations.

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

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

The description is concise with two sentences. The first sentence front-loads the core purpose and content. The second sentence adds cost information, which is relevant but not strictly necessary. No redundant information.

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

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

Given the absence of an output schema, the description should at least hint at the return structure (e.g., JSON fields). It also lacks prerequisites (e.g., need for exact company name) or limitations. The cost mention is useful but does not compensate for missing operational 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 has one parameter ('lookup') described as 'Private company name'. The description adds context about the retrieved data types but does not elaborate on parameter constraints (e.g., case sensitivity, minimum length). Schema coverage is 100%, so baseline is 3.

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

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

The description clearly states the verb 'Retrieve' and the resource 'private company deal intelligence', listing specific data types (funding rounds, valuations, investors, M&A activity, ownership changes). It effectively distinguishes this tool from sibling tools that retrieve other types of data.

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 no guidance on when or when not to use this tool vs. alternatives. With many sibling data retrieval tools, explicit usage context is missing.

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

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

Discloses cost ($0.01 USDC via x402), adding transparency beyond annotations. However, does not explicitly mention destructive nature (already indicated by destructiveHint=true) or what the similarity key is.

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: first states purpose, second adds cost and capabilities. Efficient and front-loaded with no waste.

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

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

Covers core functionality and cost, but lacks output format details (no output schema). Fine for a simple tool, but could be more 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?

Description reinforces schema for 'product' parameter (variations) but adds nothing for 'algorithm'. Schema coverage is 100%, so baseline is 3; description adds marginal value.

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

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

Clearly states the tool generates a similarity key for product name matching, handling variations. Distinct from sibling tools which focus on addresses, companies, etc.

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

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

No explicit when-to-use or alternatives mentioned. Context implies use for product name matching, but lacks guidance on prerequisites or 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?

The description claims a read operation ('Retrieve'), but annotations set destructiveHint=true, indicating mutation or deletion. This contradiction undermines transparency. The cost disclosure is helpful but does not offset the inconsistency.

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 efficiently deliver the core purpose and cost information. No redundant or irrelevant content.

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

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

The description lists key return fields (recall date, hazard, remedy, authority) and the cost model, which is sufficient for a simple retrieval tool with one parameter. However, lacking an output schema, a bit more detail on response structure would be beneficial.

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

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

Schema coverage is 100% with a clear description for the only parameter 'lookup'. The description adds context about return fields but does not enhance understanding of the parameter itself. 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 identifies the tool's function: retrieving product recall information by product, brand, or category, and specifies the type of data returned (recall date, hazard description, etc.). It is distinct from sibling tools which focus on addresses, companies, or other domains.

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?

No guidance is provided on when to use this tool versus alternatives or when not to use it. The sibling list is large but no comparative advice is given.

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 contradicts the annotations: it describes a read-only operation ('Retrieve property transaction history'), yet annotations set destructiveHint=true and readOnlyHint=false. Additionally, while it mentions cost and payment method ($0.25 USDC via x402), the contradiction undermines trust and 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?

The description is a single paragraph that lists many data points, making it somewhat lengthy. While it includes important cost information, it could be more concise. It is adequately structured but not exceptionally 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?

Despite the contradiction, the description provides a comprehensive list of returned data (last sale, prior transactions, etc.), which compensates for the lack of an output schema. The tool has only one parameter, so the description is nearly complete for an agent to understand what to expect.

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

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

The only parameter 'address' is described as 'US property street address' in the schema, and the description does not add further semantic detail. With schema coverage at 100%, the description provides no additional value beyond the schema, meeting the baseline.

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 retrieves property transaction history for a US address, listing specific data points such as last sale date, price, and ownership chain. The verb 'retrieve' and resource 'property transaction history' are unambiguous. Among the long list of sibling tools, none appear to offer the same functionality, making it distinct.

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

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

The description implies usage when property transaction history for a US address is needed, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The context is clear but not fully explicit.

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 says 'Retrieve' (read operation) but annotations set destructiveHint=true, indicating potential data destruction. This contradiction confuses the agent; no behavioral disclosure beyond annotations.

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

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

The description is two sentences plus cost info, front-loaded with the action and resource. Every sentence adds value 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 one parameter and no output schema, the description explains the source and cost but omits return format. The destructiveHint contradiction reduces completeness. Adequate but with clear 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 one parameter 'lookup' described. The description adds 'AI-powered aggregation from multiple real-time sources' but does not significantly enhance parameter clarity beyond the schema.

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

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

The description clearly states the tool's function: 'Retrieve recent news and developments for a company or topic.' It distinguishes from siblings (many Interzoid tools focus on other data like addresses or business info) by specifying news aggregation from real-time sources.

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

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

The description implies usage for news retrieval but does not explicitly state when to use versus alternatives. The 'Premium API' and cost mention suggest careful usage, but no direct guidance on exclusions or context.

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

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

The description states 'Retrieve' implying a read-only operation, but the annotations indicate destructiveHint=true, creating a contradiction. The description does not disclose any behavioral traits beyond what annotations provide, and in fact contradicts them.

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

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

The description is a concise three-sentence paragraph, front-loading the main purpose and including key details (decomposition, cost) without extraneous words. Every sentence earns its place.

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

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

Given the single parameter and no output schema, the description fully covers the tool's functionality, including input types, output components, and cost. It is complete enough for an agent to use correctly.

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

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

Schema coverage is 100% for the single parameter. The description adds value by recommending a full street address for accuracy, which is not in the schema description. This enhances the agent's understanding of how to use the parameter effectively.

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 retrieves US sales and use tax rates for various inputs, distinguishing it from sibling tools which handle addresses, names, companies, etc. The verb 'retrieve' and specific resource 'sales and use tax rates' are explicit 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?

The description advises submitting a full street address for the most accurate rate assignment, providing useful guidance. However, it does not explicitly state when not to use this tool or mention alternatives, though the sibling list shows no other tax rate tools.

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

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

The description adds the cost ($0.01 USDC via x402) as a behavioral trait beyond annotations. However, annotations indicate destructiveHint=true and openWorldHint=true, but the description does not elaborate on what destructive means or other side effects. The cost information is helpful but limited.

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

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

Two efficient sentences: first defines purpose and behavior, second gives examples and cost. No filler or repetition. Front-loaded and easily scannable.

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-param tool with no output schema, the description covers purpose, example transformations, and cost. It lacks details on output format (though implied by example) and error handling. Given simplicity, it is mostly complete but could specify the output structure more explicitly.

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

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

Schema coverage is 100% (both parameters documented). The description adds value for the 'state' parameter by providing input examples and normalizing behavior. However, the optional 'algorithm' parameter is not explained, so the description improves understanding but is incomplete for that param.

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: standardize US state/province names to full name plus abbreviation. It provides concrete examples (e.g., 'Calif', 'CA', 'Cal' -> 'California' / 'CA'), and the tool is distinct from siblings which focus on addresses, matching, etc.

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

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

The description implies usage for standardizing US state/province names but does not explicitly guide when to use this tool vs the many siblings. There is no mention of alternatives or exclusions, leaving the agent to infer context from sibling names.

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

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

The description describes a read operation ('Get... analysis'), but the annotations have destructiveHint=true, creating a direct contradiction. Additionally, the description does not clarify the discrepancy or disclose any other behavioral traits like error handling or rate limits.

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

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

The description is extremely concise—two sentences covering purpose and cost—with no wasted words. The most critical information (what it does, what it provides) is front-loaded.

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

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

The description lists key outputs but lacks details on error handling, response format, or what happens for invalid tickers. Since there is no output schema, some additional context about the response would be beneficial, but the description is minimally adequate for a simple tool.

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

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

The input schema already fully describes the only parameter ('lookup' with description 'Stock ticker symbol or company name'). The description adds no additional semantics beyond listing the outputs, so it meets the baseline for high schema coverage.

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

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('AI-powered stock analysis for a ticker symbol'), listing specific data points (price, market cap, etc.). It distinguishes itself from the many other interzoid tools by focusing solely on stock analysis.

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?

No guidance is provided on when to use this tool vs. alternatives. The description only mentions cost and premium nature, but does not specify prerequisites, limitations, or scenarios where other sibling tools would be more appropriate.

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 claims a non-destructive lookup, but annotations set destructiveHint: true, a direct contradiction. Additionally, while cost is mentioned, no side effects or permission requirements are disclosed, so behavioral transparency is poor.

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

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

The description is a single, efficient sentence that immediately states the tool's purpose and key output, plus cost info. No extraneous text; front-loaded 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?

Although the description lists technology categories, it does not explain the output format or structure, and there is no output schema. For a tool with moderate complexity and no output schema, the description should provide more detail on return values, leaving it incomplete.

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

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

Schema coverage is 100% with the parameter well-described in the schema. The description adds the same information ('domain name or company website') but no additional format, examples, or constraints, so baseline score of 3 is appropriate.

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

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

The description clearly states the tool identifies the complete technology stack from a domain lookup, listing numerous technology categories. This verb+resource combination is specific and distinct from sibling tools which cover addresses, companies, and other data.

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

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

The description implies usage for tech stack analysis, and sibling tools are clearly different in purpose, so usage context is clear. However, it lacks explicit guidance on when to use this versus alternatives or any when-not conditions, which prevents a higher score.

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

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

Annotations include 'destructiveHint: true', but the description does not explain why it is potentially destructive (e.g., cost implications or state changes). The only behavioral note is 'Cost: $0.01 USDC via x402.', which addresses some external consequence but not destruction. No contradiction, but significant gap given the annotation.

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

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

The description is very concise with two sentences. It front-loads the main action and includes cost information. However, it omits usage guidelines and behavioral details, which would improve it.

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 2-parameter tool with no output schema, the description lacks explanation of return values or format. With no output schema, the agent needs to know what the tool returns. Still, the core purpose is clear.

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

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

Schema description coverage is 100%, and the description adds no further semantics beyond what the schema already provides. 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 states 'Detect the language of input text and translate it to any specified target language.' This gives a clear verb (detect and translate) and resource (input text), and the name implies support for any target language, distinguishing it from sibling tools like 'interzoid_translate_to_english'.

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 does not provide guidance on when to use this tool versus alternatives like 'interzoid_identify_language' or 'interzoid_translate_to_english'. It only states what it does, not when to choose it over siblings.

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

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

Annotations include destructiveHint=true and openWorldHint=true. The description adds 'AI-powered' and cost '$0.01 USDC via x402', but does not explain why the tool is marked destructive or what side effects exist. Some additional context beyond annotations, but insufficient depth.

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

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

Description is three short sentences, front-loaded with the core purpose. No unnecessary words or repetition. Efficiently conveys purpose, capability, and cost.

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 tool with one required param and no output schema, the description covers detection, translation, and cost. It does not detail output format, but that is acceptable given the tool's straightforward nature. Slightly missing context about supported languages or use of external API.

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

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

Schema coverage is 100% with the 'text' parameter described as 'Text in any language to translate to English'. The description adds no new semantics beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states the tool detects language and translates to English ('Detect the language of input text and translate it to English'). It distinguishes from sibling 'interzoid_translate_to_any' by specifying translation target as English.

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

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

The description implies usage for translating to English, but does not explicitly state when to use this vs. 'interzoid_translate_to_any' or any exclusions. The sibling list provides contrast but the description lacks direct guidance.

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

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

The description claims the tool is for retrieval ('Retrieve detailed information'), but annotations set destructiveHint=true and readOnlyHint=false, contradicting the read-only nature implied by the description. This misleads about the tool's safety profile.

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

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

The description is concise with two sentences. The first sentence clearly defines the tool's purpose, and the second adds cost information. No unnecessary words, but the cost detail could be moved to a separate section or annotation.

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 lists typical output fields, helpful given no output schema. However, it lacks usage context (e.g., prerequisites or response format) and the annotation contradiction undermines completeness. Adequate but with 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 provides 100% coverage for the single parameter 'lookup' with a brief description. The tool description adds context about the output fields but does not enhance parameter meaning beyond the schema. Baseline 3 is appropriate.

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

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

The description clearly states the tool retrieves detailed information about universities/colleges, listing specific data types (location, type, enrollment, etc.). It distinguishes from sibling tools which focus on addresses, companies, or other domains.

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 mentions it is a premium API with a cost, implying usage requires payment, but does not specify when to use this tool versus alternatives among siblings. No explicit exclusions or when-not-to-use guidance.

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

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

The description describes the tool as 'Retrieve' implying a read-only operation, yet annotations set destructiveHint=true, indicating potential modification. This contradiction undermines transparency. No additional behavioral context is provided.

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 stating the purpose and output, plus a cost note. No superfluous information.

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

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

For a simple tool with one parameter and no output schema, the description covers the key aspects: input types, output content (handle + confidence score). However, the annotation contradiction reduces completeness.

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

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

Schema description coverage is 100% with the parameter 'lookup' clearly described in the schema. The description adds no further detail beyond what the schema provides, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool retrieves an X handle for entities like persons or organizations, and specifies the output includes a confidence score. It differentiates from sibling tools like interzoid_x_profile and interzoid_x_last_three_posts by focusing solely on handle lookup.

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 pricing information but no guidance on when to use this tool versus alternatives (e.g., interzoid_x_profile for more profile data). There is no mention of prerequisites or when not to use it.

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

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

Description claims this is a read operation ('Retrieve'), but annotations set destructiveHint=true, indicating potential side effects. This contradiction undermines transparency. No explanation of any destructive behavior.

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

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

Two concise sentences, front-loaded with key information, no fluff.

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

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

Describes return content partially but lacks full specification (e.g., format, pagination). No output schema, so description should be more complete. Also missing behavioral context due to annotation contradiction.

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

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

Schema covers 100% of parameters with a clear description. The tool description adds nothing beyond the schema's parameter description.

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

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

Description clearly states the action (Retrieve), the resource (three most recent posts from X handle), and the output (full text content and date). It distinguishes itself from siblings like interzoid_x_profile and interzoid_x_handle by focusing on posts.

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?

No guidance on when to use this tool versus others like interzoid_x_profile. Cost is mentioned but no alternatives or context for choosing.

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 says 'retrieve' suggesting a read-only operation, but annotations have destructiveHint: true, indicating possible side effects. This contradiction is not addressed in the description. Cost information is provided but no disclosure of side effects or authentication needs.

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: first specifies the action and lists return fields, second states cost. Both are directly valuable and well-structured.

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

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

The description lists return fields in the absence of an output schema, which is helpful. However, it does not explain error conditions, rate limits, or the contradiction with the destructiveHint annotation. Adequate for a simple retrieval but missing context for the annotation discrepancy.

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

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

The input schema provides 100% coverage for the single parameter 'handle' with a clear description. The tool description adds return field information but no additional parameter semantics beyond the schema.

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

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

The description clearly states the action (retrieve) and resource (comprehensive profile snapshot for an X handle), listing key data fields. It distinguishes itself from sibling tools like interzoid_x_handle and interzoid_x_last_three_posts by specifying a 'comprehensive profile snapshot'.

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

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

The description implies usage for obtaining a full profile but does not explicitly state when to use this tool versus alternatives like interzoid_x_handle or interzoid_x_last_three_posts. No when-not-to-use guidance is provided.

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

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

The description implies a read-only operation ('Get detailed info'), but annotations set destructiveHint=true and readOnlyHint=false, indicating potential side effects. This contradiction undermines transparency. No additional behavioral traits (e.g., rate limits, auth needs) are disclosed.

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

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

The description is a single, concise sentence that efficiently communicates the tool's purpose and cost. Every word adds value.

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

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

Given no output schema, the description should explain the return format but only lists fields. The destructiveHint contradiction is unresolved. For a simple one-parameter tool, this is insufficiently 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 input schema already describes the parameter 'zip' as a 'US ZIP code (5-digit)'. The description adds no further semantic detail beyond what the schema provides. With 100% schema coverage, the baseline is 3.

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

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

The description clearly states the tool retrieves detailed information for a US ZIP code, listing specific data points like city, state, county, etc. This distinguishes it from sibling tools that focus on addresses, businesses, or other entities.

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 no guidance on when to use this tool versus alternatives. While the cost is mentioned, there is no explicit context for appropriate use cases or exclusions.

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