Search 1,800+ editorial FAQs for a direct answer to a specific ITIN finance question (EN/ES). Each answer carries its source article URL.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Answer language: en (default) or es (Spanish) | |
| query | Yes | A specific ITIN finance question, e.g. 'can I get a mortgage with an ITIN' |
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.
Add one secure layer between your agents and this server.
Most tools target distinct content types, but there is meaningful overlap between can_i_get_this_loan and find_itin_lenders, and between faq_lookup and search_guides. The descriptions help clarify boundaries, but an agent could still hesitate when choosing the right search/retrieval tool.
Tool names do not follow a consistent verb_noun pattern: can_i_get_this_loan and how_to_get_an_itin are question-style phrases, while others use get_, find_, search_, or noun-only names like itin_state_info. All names are readable, but the conventions are too mixed to predict new tool names.
Eight tools is well-scoped for an ITIN finance information service. Each tool covers a distinct aspect of the domain—eligibility, lenders, guides, FAQs, state context, and ITIN application—without feeling bloated or thin.
The tool surface covers the core user journeys: finding guides, searching FAQs, checking loan eligibility, discovering lenders, getting lender details, learning how to get an ITIN, and understanding state-level context. No major dead ends or obvious missing operations are apparent for this informational domain.