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 annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds crucial behavioral details: sequential querying per connection, rate-limit spacing, and the return format `{ results, errors }` per connection. 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 sentences effectively front-load the purpose, then explain parameter usage and alternative behavior. No wasted words, and every sentence provides essential 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 no output schema, the description still covers return format, handling of multiple connections, and optional parameter behavior. It is fully adequate for a simple list tool with one parameter.
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?
Although schema coverage is 0%, the description thoroughly explains the `items` parameter: its value types (item_id uuid, connector_id, or connector_name) and the effect of omitting it (list across all linked banks). This adds significant meaning beyond the bare schema type 'array of strings'.
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 the exact resource ('loan contracts per bank connection') and HTTP method ('GET /loans'), distinguishing it from sibling 'openfinance_get_loan_detail' which provides detail on a single loan.
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 clearly explains how to use the `items` parameter to target specific connections or omit it for all banks, and notes sequential querying with rate-limit spacing. It does not explicitly mention when not to use this tool, but the context is clear enough.
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.
Tools are largely distinct: openfinance_* tools cover specific resources (accounts, transactions, bills, loans, investments) with clear boundaries. Some overlap exists between list_transactions and list_transactions_by_item, and between status/sync tools (get_item_status, force_sync, provider_status), but descriptions are detailed enough to guide selection.
The openfinance_* prefix provides strong consistency for the bulk of tools, with clear verb_noun patterns (list, get, update, force_sync). The platform tools (authenticate, connect, marketplace, report_bug, etc.) break the pattern but are few and their names are intuitive. Overall, minor mixing of conventions but readable.
25 tools is on the higher side but appropriate for a comprehensive Open Finance and platform management server. The count includes both data access (accounts, transactions, bills, loans, investments) and platform utilities (authentication, connection state, marketplace). No redundant tools; each serves a clear purpose.
The surface covers the core read operations for connected banks (accounts, transactions, bills, loans, investments), connection management (sync, status, disconnect), and category correction. Minor gaps include no get-transaction-by-id and no update for account metadata, but these are not critical for the typical use case of a banking data aggregator.