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?
Annotations indicate readOnly, idempotent, and non-destructive. The description adds important behavioral details: items accept connection selectors, multiple connections are queried sequentially with rate-limit spacing, and the return format is { results, errors } per connection.
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 concise with two sentences. It front-loads the purpose, then provides parameter and usage details, with no wasted words.
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 different usage patterns, return format, and rate-limit behavior. It lacks pagination details, but for a list tool with no output schema, it is largely complete.
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 0%, so the description fully compensates by explaining the items parameter: array of connection selectors (item_id uuid, connector_id, or connector_name), with option to omit for all connections.
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 it lists loan contracts per bank connection, specifies the HTTP endpoint, and explains different behaviors for providing vs. omitting the items parameter. It distinguishes this tool from siblings like openfinance_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?
The description explains when to use the items parameter (to fetch specific connections) and when to omit it (list all), including sequential querying with rate-limit spacing. However, it does not explicitly state when not to use this tool versus alternatives.
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.
Every tool has a clearly distinct purpose: accounts, transactions, credit card bills, loans, investments, connections, sync, categories, provider status, and platform meta-tools are all separable. Even the two transaction tools differ (per-account list vs consolidated analysis) and the two status tools differ (connection vs provider health).
The openfinance_* prefix is consistently applied across the financial domain, and most follow a verb_noun pattern (list_accounts, get_balance, update_category). However, there are non-prefixed tools (authenticate, connect, marketplace, toolkit_info) and one outlier like openfinance_provider_status (noun instead of verb) that slightly break the pattern.
25 tools is at the upper boundary of what feels heavy for a single server, even for a comprehensive financial aggregation toolkit. The number is justified by the breadth of domains covered (accounts, credit, loans, investments, connections, platform features), but it requires careful agent selection and might be better split into separate servers.
The surface covers the full financial data lifecycle: listing and fetching details for all asset types, updating transaction categories, managing connections (list, sync, disconnect, reauth), checking provider health, and searching connectors. There are no obvious dead ends—every domain has read and appropriate write/update operations.