Revokes the Open Finance consent for a specific bank and deletes the connection data. The bank's data will no longer be available. Returns an add_connection_url to re-connect if needed.
| Name | Required | Description | Default |
|---|---|---|---|
| item | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already flag destructiveHint=true, and the description adds meaningful context: it revokes consent, deletes connection data, makes data unavailable, and returns a reconnection URL. This goes beyond the annotation by specifying the exact destructive effects and the fallback mechanism, without contradicting the 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?
Two sentences, front-loaded with the primary action, and no filler. Every clause adds value: what happens, the consequence, and the return value. It is appropriately sized for the tool's simplicity.
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 tool with one parameter, no output schema, and destructive behavior, the description covers the action, effects, and return value. The only gap is the lack of explicit parameter definition, but the overall context is adequate. More detail would be needed if the tool were more complex.
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 has one parameter 'item' with no description, and schema description coverage is 0%. The description mentions 'a specific bank' but does not explicitly explain that 'item' should be the bank/connection identifier. The agent must infer this from the tool name and context, which is insufficient for correct invocation.
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 action: 'Revokes the Open Finance consent for a specific bank and deletes the connection data.' This uses a specific verb and resource, and the effect is unambiguous. It distinguishes itself from sibling tools by being the only one focused on disconnecting/revoking access.
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 implies the use case: when you need to revoke consent and delete connection data for a bank. It notes the consequence ('data will no longer be available') and provides a recovery path ('Returns an add_connection_url to re-connect'). It does not explicitly mention alternatives, but the purpose is distinct enough among siblings.
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.
Each Open Finance resource has a clearly named list/get pair, and connection status vs provider status vs force sync are distinct. The main ambiguity is between list_accounts (which already carries balances) and get_account_balance, and between list_transactions and list_transactions_by_item, which requires reading the descriptions carefully.
The openfinance_* tools follow a consistent verb_noun pattern (list_*, get_*, update_*, force_sync, search_*). Exceptions like marketplace, toolkit_info, and openfinance_provider_status break the pattern slightly, but the two logical groups are predictable internally.
At 25 tools this is on the heavy end of the scale. Most tools have a real purpose, but several list/get pairs and the multi-purpose marketplace mega-tool could be consolidated without losing functionality, making the overall surface feel larger than strictly necessary.
The Open Finance surface is impressively broad: connections, accounts, balances, transactions, credit-card bills, loans, investments, categorization, sync, provider health, and connector search are all covered. Minor gaps like a single-transaction getter or a consolidated statement export force agents to assemble data with extra calls, but no critical workflow is blocked.