Full verified profile for one institution: ITIN policy, states, membership rules, published terms, citations, and our editorial coverage.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Institution name, e.g. 'Alterra Home Loans' |
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.
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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.