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openfinance_list_transactions

Read-onlyIdempotent

Returns transactions for a bank account (BANK or CREDIT type). For CREDIT (credit card) accounts, this is the ONLY way to get itemized transactions (purchases, subscriptions, etc.). Each credit card transaction MAY carry creditCardMetadata.billId pointing at a bill from openfinance_list_credit_card_bills, but this is a per-connector HINT, not authoritative: some connectors (e.g. Nubank) populate it sparsely (many transactions and installments arrive with no billId) or inconsistently (the same payment tagged to more than one bill). Do NOT reconstruct a bill's total by summing transactions by billId — the bill's own totalAmount from openfinance_list_credit_card_bills is the source of truth. CREDIT PENDING vs POSTED varies by connector: where the bank exposes future-dated status:'PENDING' installments, those represent the OPEN bill plus future bills (future months); where it does NOT, only the last closed bill's POSTED items appear until ~closing. Same query, different coverage per bank (upstream). To get a standardized open-bill total / total debt regardless, use openfinance_list_credit_card_bills (open_bill / total_pending_debt). SCHEDULED (future-dated) ROWS: results are ordered by date DESCENDING, and on a card with long installment plans the TOP of the list is the FUTURE — rows dated months ahead are scheduled installments of purchases already made, not new purchases. Every such row is flagged scheduled:true, the response carries scheduled_count and a notice naming the most recent row that actually happened. NEVER read the first row as 'the latest purchase' without checking scheduled. To list only what already happened, pass to = today. Supports from/to date filters (ISO YYYY-MM-DD) and an optional keyword filter via search_queries (case- and accent-insensitive substring match against description and merchant name, OR semantics across multiple terms). When search_queries is set the tool aggregates up to 5000 transactions within from/to before filtering — narrow from/to if truncated:true is returned. PAGINATION: OMIT both page and page_size (the default) to get ALL transactions in the from/to range in one call — the tool auto-paginates the upstream and returns them under a single logical page (page:1, totalPages:1), up to a 5000 ceiling (truncated:true + warning if exceeded, then narrow from/to). Passing page and/or page_size switches to MANUAL pagination: you get one page (page_size items, default 50, max 500; page defaults to 1) with the REAL total/totalPages, so page_size:5 alone returns the first 5 with totalPages telling you how many pages remain. On upstream errors, returns { total:0, results:[], warning, error } instead of throwing. detail controls how much per-row data you get (default 'compact' = slim, cheap). Use detail:'rich' to enrich each row (when the bank connector provides it) with merchantInfo (estabelecimento: businessName/razão social, cnpj, cnae, category — useful for auto-classifying spending) and extra creditCardMetadata fields: billId (a per-connector HINT toward the transaction's bill — sparse/inconsistent on some connectors like Nubank, so do NOT sum by it to get a bill total; use the bill's totalAmount instead), billForecastDate, cardNumber, purchaseDate, payeeMCC, feeType/feeTypeAdditionalInfo, otherCreditsType/otherCreditsAdditionalInfo. billForecastDate ("YYYY-MM") is the counterpart of billId for the OPEN cycle: PENDING transactions have NO billId (the bank only mints it once the bill closes), so this is the only field telling you which bill a pending purchase will land in — its month OFFSET is per-connector (some banks month+1, others month+0), so surface it as-is and do not derive a due date from it. cardNumber (last 4 digits) separates the primary cardholder's charges from an additional card's when several cards share one account_id. Use detail:'raw' to get the FULL untouched Pluggy transaction object (everything Pluggy returns, un-normalized — heaviest, for when you need a field we don't project). 'rich'/'raw' add tokens per row and coverage varies by bank/Open Finance, so keep the default for normal listings. For the card's statement closing/due dates use openfinance_list_accounts (creditData.balanceCloseDate / balanceDueDate). The response opens with an account echo block ({ account_id, bank, name, number, type, item_id }) identifying WHICH account/bank these transactions belong to. When more than one bank is connected, ALWAYS cross-check the echo against the account you intended to query and name the bank when presenting results — never attribute one bank's transactions to another. If total is 0 for a CREDIT account, check the connection health via openfinance_get_item_status — statusDetail.creditCards.isUpdated: false means the credit card sync failed and a force sync (openfinance_force_sync) or reconnection may be needed. May include a provider_incident block when the Open Finance provider has an OPEN incident affecting a connected bank: transactions may come back incomplete or wrong until the provider recovers, and reconnecting does not fix it.

Bulk support: accepts account_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo
fromNo
pageNo
detailNo
page_sizeNo
account_idYes
account_idsNo
search_queriesNo

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description reveals a great deal of behavior not captured by the annotations: auto-pagination behavior, sorted by date descending with scheduled rows, truncation at 5000 transactions, error return shape, provider_incident blocks, and per-connector inconsistencies like sparse billId. The annotations already signal read-only/idempotent, and the description adds extensive side-effect-free operational context without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence delivers the core purpose, and the description is organized into semantic chunks: credit-card caveats, filtering, pagination, detail modes, response echoes, and sibling-tool referrals. It is quite long and repeats the billId warning and 'do not sum by billId' guidance in more than one place, so it is not maximally concise—but the complexity and per-bank caveats justify most of the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description is remarkably complete about return contents, including the account echo, scheduled_count, notice, truncated flag, provider_incident block, and graceful-error structure. It also covers connector variability and how to recover when a credit card sync breaks. An agent has everything needed to select, invoke, and interpret this tool safely.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description does substantial work to explain parameters: from/to use ISO YYYY-MM-DD, search_queries uses case-insensitive OR matching, page/page_size switch between auto and manual pagination, detail level semantics are fully documented. The required account_id, however, is only implied by context rather than explicitly defined as 'the ID of the target account', and account_ids is explained only as a terse 'bulk support' line.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb-object: 'Returns transactions for a bank account (BANK or CREDIT type)', clearly identifying the resource and its scope. It also distinguishes the tool from openfinance_list_credit_card_bills and openfinance_list_accounts by explaining which sibling to use for bill totals and statement dates. This goes beyond the generic title and disambiguates the tool effectively.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance: 'this is the ONLY way to get itemized transactions' for credit cards, and directs agents to openfinance_list_credit_card_bills when they need a standardized open-bill total or total debt. It also explicitly warns against reconstructing bill totals from transactions and points to openfinance_get_item_status when a credit total is zero, giving precise routing and remediation paths.

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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TDQS

A4.2/5.0
Disambiguation5/5

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).

Naming Consistency4/5

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.

Tool Count3/5

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.

Completeness5/5

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.