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openfinance_get_credit_card_bill

Read-onlyIdempotent

Returns bill-level detail for one or more credit card bills by id (GET /bills/:id): dueDate, billClosingDate (when the cycle closed — the boundary that defines which purchases belong to this bill), totalAmount, financeCharges and payments[] (id, paymentDate, amount, valueType, paymentMode). ITEMIZED PURCHASES (OPT-IN): the bank's bill payload has no transactions in it — they live on the card ACCOUNT. Pass include_transactions:true (plus account_id of the credit card, since the bill itself carries no account reference) and each row also gets transactions[], transactions_count, transactions_sum and reconciles_with_total, already matched to that bill. Always check transactions_basis: bill_id = exact (the bank tagged each transaction with this bill — the normal case for CLOSED bills), date_window = ESTIMATE (confidence:'low', window echoed in transactions_window) used when the connector tags no billId or the bill is still open (PENDING lines get no billId until the cycle closes), unavailable = no link possible. Opt-in because it costs an extra full transaction scan of the account. Whatever the basis, the bill's own totalAmount is authoritative — do NOT rebuild it by summing transactions. Without the opt-in the response carries a transactions_hint; you can also fetch them yourself via openfinance_list_transactions with the credit card account_id and a from/to range ending at billClosingDate. Pass bill_ids as an array — use openfinance_list_credit_card_bills first to discover ids. { results, errors } batch shape. NOTE: Pluggy does NOT return a paid/status field. In Brazilian Open Finance, payments[] reflects payments registered during THIS bill's billing cycle — typically the payment of the PREVIOUS bill (do NOT assume this bill was paid just because payments[] is non-empty). To check paid status, prefer openfinance_list_credit_card_bills which derives payment_status via cross-bill match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bill_idsYes
account_idNo
transactions_detailNo
include_transactionsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. Added
  6. Removed
  7. Changed3 schema fields changed
    • addedInput schema / properties / account_id
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / include_transactions
      Added value: +{
      +  "type": "boolean"
      +}
    • addedInput schema / properties / transactions_detail
      Added value: +{
      +  "enum": [
      +    "compact",
      +    "rich",
      +    "raw"
      +  ],
      +  "type": "string"
      +}
  8. Added
  9. Removed
  10. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent, so the description goes further with valuable context: the bank payload has no embedded transactions, the opt-in costs a full account scan, transactions_basis semantics are explained, totalAmount is authoritative, and Pluggy does not return a paid/status field. These are exactly the non-obvious behaviors an agent needs.

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

Conciseness5/5

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

The description is dense but every sentence earns its place, and the core action is front-loaded before caveats. It uses formatting and all-caps to highlight critical warnings such as 'do NOT rebuild it by summing transactions.' Despite its length, it reads as a well-packed specification rather than filler.

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?

For a tool with no output schema and a complex domain, the description covers response shape, batch semantics, parameter interplay, transaction matching basis, payment-cycle pitfalls, and alternative tools. There are no glaring gaps that would prevent an agent from calling this tool correctly and interpreting the result accurately.

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 description coverage, the description compensates well by explaining bill_ids, account_id, and include_transactions, including why account_id is required for enrichment. It does not explain the transactions_detail enum (compact/rich/raw), so the agent has no way to know the semantic difference between those values. A minor but real gap prevents a 5.

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 and resource: 'Returns bill-level detail for one or more credit card bills by id.' It names the main output fields and explains the optional transaction enrichment, making the tool's scope unmistakable. It also implicitly distinguishes itself from openfinance_list_credit_card_bills by saying that list should be used first to discover ids.

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 and when-not-to-use guidance: use openfinance_list_credit_card_bills to discover ids and to check paid status, use openfinance_list_transactions to fetch transactions manually, and do NOT derive total by summing transactions. This makes alternatives and exclusions highly actionable.

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

A4/5.0
Disambiguation3/5

The openfinance_* tools are mostly distinct resource/action pairs, but several boundaries blur: openfinance_list_transactions vs openfinance_list_transactions_by_item vs openfinance_get_credit_card_bill(include_transactions) all return transaction data, and openfinance_get_item_status / openfinance_provider_status / openfinance_list_connections all concern connection health. The monolithic marketplace tool also bundles search/describe/invoke/install/prompt-library operations, adding further ambiguity.

Naming Consistency4/5

The 19 openfinance_* tools follow a clean snake_case verb_noun pattern (list_accounts, get_item_status, update_transaction_category), but the six platform tools break it with bare verbs (authenticate, connect) and noun-style names (marketplace, toolkit_info). The split is namespace-based and still readable, so it is only a minor inconsistency.

Tool Count3/5

25 tools is on the heavy side, but the server spans two domains: an Open Finance banking surface (accounts, bills, loans, investments, connections) and a marketplace/platform layer (auth, search, prompts, bug reporting). Many openfinance tools are necessary for that breadth, though the count is high enough to feel bloated.

Completeness4/5

The Open Finance surface is nearly complete: connections can be searched, listed, disconnected, force-synced, and health-checked; accounts, transactions, bills, loans, and investments all have read/detail paths; transaction categories can be updated. Minor gaps exist, such as no granular marketplace tools outside the monolithic marketplace tool and no single-transaction detail endpoint, but core workflows do not dead-end.