Lists loan contracts per bank connection (GET /loans). Pass items as an array of connection selectors (item_id uuid, connector_id, or connector_name) — one entry per connection to fetch; multiple connections are queried sequentially with rate-limit spacing. OMIT items to list loans across ALL linked banks. Returns { results, errors } per connection.
| Name | Required | Description | Default |
|---|---|---|---|
| items | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnly/idempotent hints, the description adds meaningful behavior: sequential queries with rate-limit spacing, and the return format `{ results, errors }` per connection. This is valuable context not present 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?
Three sentences pack purpose, parameter usage, and return format with zero filler. The description is efficiently front-loaded with 'Lists loan contracts per bank connection' and each subsequent sentence adds necessary detail.
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 optional parameter and no output schema, the description is complete: it explains the parameter, the two invocation modes, and the response shape. Sibling tools for details and other lists are easily differentiated by the clear 'Lists loan contracts' scope.
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 only shows `items` as an array of strings, but the description explains that each string is a connection selector (item_id uuid, connector_id, or connector_name) and how multiple entries affect behavior. This fully compensates for the 0% schema description 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 lists loan contracts, scoped per bank connection, with the option to list across all linked banks. The verb 'Lists' is specific, and the resource 'loan contracts' is unambiguous, distinguishing it from detail-oriented siblings like get_loan_detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is given for both usage modes: pass `items` for specific connections, and omit it to list all banks. The description also clarifies that multiple connections are queried sequentially with rate-limit spacing, which is practical usage context.
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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Each tool targets a specific resource/action (balance, transactions, bills, loans, investments, connections, categories, provider status), with clear boundaries. Minor overlap exists between openfinance_list_transactions and openfinance_list_transactions_by_item, and among the multiple account-related tools, but the descriptions are detailed enough to disambiguate.
Almost all tools follow an openfinance_<verb>_<noun> snake_case pattern (list_accounts, get_credit_card_bill, update_transaction_category). Minor deviations include openfinance_provider_status (noun_noun) and openfinance_list_transactions_by_item (extra preposition), but the overall convention is predictable and consistent.
19 tools is on the heavier side but fits the broad scope of an Open Finance banking integration covering connections, accounts, transactions, credit cards, loans, investments, and provider health. Each tool appears justified; the count does not feel bloated.
The surface covers the full lifecycle: connection discovery/search/list/sync/disconnect/status, account and transaction retrieval, credit card bill summaries and detail, loans, investments, transaction categorization, and provider diagnostics. No critical dead ends are apparent for the stated banking data domain.