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Pague Veloz Serasa MCP

openfinance_list_investments

Read-onlyIdempotent

Returns the investment portfolio for a connection (broker or bank with INVESTMENTS product enabled): FIIs, stocks, ETFs, fixed income (CDB/LCI/LCA/Tesouro), mutual funds, retirement (previdência) and COE. Each row carries balance, amount, amountOriginal, amountProfit, lastMonthRate / annualRate / lastTwelveMonthsRate (when available), dueDate, issuer, ISIN, etc. Returns { total:0, results:[], warning } instead of throwing when INVESTMENTS isn't enabled (403) or other upstream errors. DATA INTEGRITY: when MULTIPLE positions come back as TOTAL_WITHDRAWAL with balance/quantity 0 at once (mass zeroing), the tool cross-checks each position's own transaction history upstream; if the zeroing is contradicted (BUY with no sale/redemption/transfer) the response carries data_integrity_warning and the affected rows are flagged integrity:'suspect_zeroed' — treat those balances as UNAVAILABLE (likely a temporary connector failure publishing zeros), never as real R$0, and do NOT sum them into the portfolio.

Bulk support: accepts item_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemNo
pageNo
typeNo
item_idNo
item_idsNo
page_sizeNo

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. Changed2 schema fields changed
    • addedInput schema / properties / item_id
      Added value: +{
      +  "type": "string"
      +}
    • addedInput schema / properties / item_ids
      Added value: +{
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
  8. Added
  9. Removed
  10. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint), the description adds critical behavioral details: error handling returns empty instead of throwing 403, and a detailed data integrity mechanism for mass zeroing with suspect_zeroed flags. This significantly enriches agent understanding.

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

Conciseness3/5

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

The description is verbose and includes a lengthy data integrity section that, while important, could be condensed. It front-loads the purpose but becomes dense. Some redundancy exists (e.g., listing fields again).

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

Completeness4/5

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

Given no output schema, the description adequately covers return structure (total, results, warning) and the special data_integrity_warning. It explains the main fields returned. However, it could better describe pagination behavior and the 'item' parameter.

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

Parameters2/5

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

With 0% schema description coverage, the description should explain parameters. While it implies item_id/item_ids for connections, and type for filtering, it fails to define the 'item' and 'page'/'page_size' parameters clearly. This leaves ambiguity for an AI agent.

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 clearly states it returns investment portfolios for a connection, listing specific asset types (FIIs, stocks, ETFs, etc.) and detailed fields. It distinguishes itself from sibling tools like openfinance_list_investment_transactions by focusing on portfolio positions rather than transactions.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool (for investment portfolio data) and mentions bulk support via item_ids. However, it does not explicitly exclude cases or compare with other tools like openfinance_list_accounts, though the scope is well-defined.

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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