ITIN Finance

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds the caveat 'Informational only — not a recommendation or referral,' which clarifies that the output is editorial and not personalized advice. It also mentions language support (EN/ES), adding value beyond the structured annotations.

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

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

The description is a single, well-structured sentence that front-loads the purpose, lists the key output components, and includes a crucial disclaimer without redundancy. Every clause earns its place, making it concise and immediately informative.

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 an informational tool with three well-documented parameters and no output schema, the description adequately covers what the tool returns (quick answer, requirements, institutions), optional state filtering, language options, and its non-recommendation nature. It is sufficiently complete for the agent to know when and how to use it.

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

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

The input schema covers all three parameters with descriptions, including enums for loan_type and lang. The description adds minor semantic context like 'optionally state-filtered' and implies loan_type relevance, but this does not significantly exceed the schema's own documentation. Given 100% coverage, 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 answers 'can I get a(n) X with an ITIN?' and specifies the output: editorial quick answer, typical requirements, and institutions with documented ITIN programs. It distinguishes from sibling tools like find_itin_lenders (which focuses on lenders) by emphasizing the direct answer and informational nature.

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 context is clear: it's for getting an informational answer, optionally filtered by state and language. It explicitly notes it's not a recommendation or referral, but it does not name alternative tools or state when NOT to use it. Since it's one of several ITIN tools, explicit exclusions would improve distinction, but the current description offers sufficient context 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?

Annotations already establish the tool is read-only and non-destructive. The description adds useful behavioral context: it returns a direct answer along with the source article URL, and supports both English and Spanish. It doesn't explain any rate limts or errors, but for a semplic read lookup with safe annotations, this is adequate.

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

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

Two tightly written sentences with zero waste. The core search purpose and scope ('1,800+ editorial FAQs') are front-loaded, and the return-value detail is kept to one concise second sentence.

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 two-parameter lookup with read-only annotations and no output schema, the description covers the essential return behavior (direct answer + source URL). It lacks explicit differentiation from sibling search_guides, but the overall definition is complete enough for reliable invocation.

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

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

Schema description coverage is 100%, so both query and lang parameters are fully documented in the schema. The description only reinforces the language hint (EN/ES) and doesn't add meaningful detail beyond what the schema already provides, warranting the baseline score.

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 ('Search') with a concrete resource ('1,800+ editorial FAQs') and a precise purpose ('direct answer to a specific ITIN finance question'). It clearly distinguishes itself from broader guide or lender lookup siblings by emphasizing 'direct answer' and English/Spanish coverage.

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

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

The phrase 'direct answer to a specific ITIN finance question' conveys when to use the tool: for targeted, factual lookups rather than broad guides or lender searches. It doesn't explicitly exclude alternatives or name siblings, but the context is clear enough for an agent to route correctly.

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

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

Annotations already declare readOnlyHint, openWorldHint, and destructiveHint=false, so the description doesn't need to repeat that. It adds value by noting entries include verification status with citation URLs and dates, which is a behavioral/output trait beyond annotations.

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

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

Two sentences, no fluff, front-loaded with the main purpose. The second sentence adds essential detail about output verification. Efficient 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 tool is simple with 3 parameters, all described. The description covers the core functionality and output characteristics. Without an output schema, it could mention response format, but the verification detail mitigates that. Adequate for the complexity.

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

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

Schema coverage is 100%, so the schema documents all parameters. The description reiterates 'loan or card type' and 'optional state filter' but adds no new meaning beyond the schema, hence baseline 3.

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

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

The description clearly states the tool lists institutions accepting ITIN for a loan or card type, with an optional state filter. It distinguishes from siblings like get_lender_details (which focuses on specifics) by emphasizing the list and verification aspect.

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

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

The description implies when to use it (for listing institutions) but does not explicitly name alternatives like get_lender_details for details. It provides clear context without exclusions, so a 4 is 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 annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds value by explicitly listing what the response includes (quick answer, FAQs, related guides, canonical URL), which is useful behavioral transparency beyond the annotations.

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

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

The description is a single, well-structured sentence that front-loads the purpose and concisely lists the key return components. No filler 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?

The tool is simple, with only two parameters and a single required one. The description covers the key output components (quick answer, FAQs, related guides, canonical URL), compensating for the lack of an output schema. It lacks mention of possible error conditions, but this is not critical for a read-only fetch 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?

Since schema description coverage is 100%, the description does not need to add parameter details. It only reiterates that slug can be an approximate title, which is already stated in the schema. No additional semantics beyond schema are provided, so a baseline of 3 is appropriate.

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

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

The description clearly states the action ('Get one guide') and the resource (guide) and differentiates it from sibling tools by specifying it returns a quick answer, FAQs, related guides, and canonical URL for a single guide identified by slug or approximate title. This distinguishes it from search_guides (which likely returns multiple).

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

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

The description implies when to use it (to fetch a specific guide) but does not explicitly contrast with alternatives like search_guides or mention when not to use it. It provides no exclusions or conditions, making it minimally viable but not explicitly guiding the agent to choose this over other tools.

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

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

Annotations already establish read-only, non-destructive behavior. The description adds meaningful context by specifying the scope (one institution) and the verified/full nature of the returned profile, even though it does not cover edge cases like unknown institution names.

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, information-dense sentence that front-loads the key purpose and then lists the exact content areas returned. There is no redundant or unnecessary wording.

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

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

For a simple one-parameter, read-only lookup with no output schema, the description is reasonably complete. It enumerates the return content and clearly delimits the scope to one institution, though it could have been slightly stronger with a note about how this differs from the sibling lender-search tools.

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

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

The single parameter `name` is fully documented in the schema with an example, and the description reinforces that it applies to a single institution. However, the textual description adds no additional semantic detail beyond what the schema already provides.

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

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

The description clearly states this tool returns a full verified profile for a single institution and enumerates its contents (ITIN policy, states, membership rules, published terms, citations, editorial coverage). This distinguishes it from the sibling tools that search for lenders or answer eligibility questions.

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

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

The phrase "for one institution" establishes the core use case: retrieve comprehensive details about a specific lender. It does not explicitly name alternatives or exclusions, but the description implicitly contrasts with list/search-oriented sibling tools.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about the guide's content and mentions a full guide URL, but it does not clarify the return format, whether live/external data is fetched, or any limitations.

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

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

The description is one efficient sentence that front-loads the tool's purpose and then lists the key content areas. There is no filler or redundant explanation, and the trailing 'EN/ES' is brief and useful for indicating language support.

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 informational tool with strong annotations, the description adequately covers the topic, language options, and the presence of a guide URL. It does not fully specify the return structure, but the content list and guide URL mention are sufficient for basic selection and invocation.

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

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

The single parameter 'lang' is fully described in the schema with an enum and default note, and the description's 'EN/ES' only echoes that. The schema carries the parameter documentation burden, so the description adds no additional semantic value beyond 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 provides instructions for applying for an ITIN via IRS Form W-7, listing specific content areas: process, documents, timelines, and common mistakes. It is specific about the resource, but it does not explicitly distinguish itself from sibling tools like get_guide or faq_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?

No guidance is provided about when to use this tool versus its siblings such as faq_lookup, search_guides, or get_guide. The 'how to apply' phrasing implies a use case, but there are no explicit when-to-use, when-not-to-use, or alternative recommendations.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds that it returns specific data points (ITEP 2022 taxes, rate, law, URL) but does not disclose response format, pagination, or any side effects. Since annotations cover the read-only nature, this is adequate but not exceptional.

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, information-dense sentence listing all key data points (taxes, rate, law, URL) without waste. It is front-loaded with the main purpose and perfectly 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?

Given the single parameter and the listing of all returned data types in the description, the tool is adequately specified. There is no output schema, but the description tells the agent exactly what fields to expect, making it sufficiently complete for a 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 has 100% coverage with description 'US state name or 2-letter code' for the single parameter. The tool description does not add further meaning beyond the schema, but the coverage is complete, 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 provides state-level context for ITIN holders, listing specific data points (taxes paid, effective rate, driver's-license law, state guide URL). It distinguishes itself from sibling tools like search_guides and get_guide by specifying the exact content returned, making its purpose unambiguous.

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

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

The description implies usage for when state-specific ITIN tax and policy information is needed, but does not explicitly state when not to use it or name alternatives. However, the clarity of the data scope makes it obvious this is for state-level factual lookup, distinct from broader guide tools. It lacks explicit exclusions but is clear enough for an agent.

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

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

Annotations already cover safety (readOnlyHint=true, destructiveHint=false) and open-world behavior. The description adds meaningful behavioral context beyond annotations: it discloses the output as 'quick answers with canonical article URLs', tells the agent this is a search over a fixed set of 290+ guides, and signals that results are summaries rather than full articles. 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?

A single sentence packs scope, content type, language coverage, and output format with zero filler. The most decision-relevant fact ('Search 290+ editorial guides') is front-loaded, and every clause 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 description covers what the tool searches, which topics, which languages, and what it returns (answers with canonical URLs), which is enough for correct invocation given no output schema. It could additionally mention that it is limited to editorial guides rather than other content types, but the phrase 'editorial guides' and sibling names make this reasonably inferable.

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

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

Schema description coverage is 100%, so the parameters are already well documented in the input schema, including defaults and enum meanings. The description adds top-level context (topics, language availability, network sites) but does not deepen parameter semantics beyond what the schema 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 uses a specific verb ('Search') and a precise resource ('290+ editorial guides across the ITIN finance network'), and clearly scopes the domains (loans, mortgages, credit cards, credit scores) and languages (English and Spanish). This distinguishes it from siblings like get_guide (retrieval of a specific guide), faq_lookup (FAQ answers), and find_itin_lenders (lender discovery) without ambiguity.

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

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

The description implies use when the user needs to find relevant editorial guides on these finance topics, and its scope statement rules out FAQs or lender-specific searches. However, it does not explicitly name alternatives or state when not to use this tool, so an agent must infer the boundary from sibling names rather than being told directly.

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