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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. 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"
      +}
  4. Added
  5. Removed
  6. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=true, destructiveHint=false), the description discloses error handling behaviors (returns structured response on 403), data integrity checks, and warning flags (data_integrity_warning, integrity:'suspect_zeroed'). This adds significant value.

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 description is well-structured with clear paragraphs and front-loaded purpose. However, it is somewhat lengthy due to detailed data integrity notes, which could be condensed. Still, no wasted sentences.

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 the tool's complexity (6 parameters, no output schema), the description is remarkably complete. It explains the return format, error handling, data integrity warnings, and bulk support. An AI agent can effectively use this tool with the provided information.

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?

Schema description coverage is 0%, so the description must compensate. It only briefly mentions item_ids for bulk support. Other parameters (page, page_size, type, item) are not explained. The description does not add meaning beyond the schema, leaving the agent guessing about parameter formats and usage.

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 the tool returns investment portfolios for a connection, listing specific asset types and fields. It uses a specific verb ('returns') and resource ('investment portfolio'), distinguishing it from sibling tools like openfinance_list_investment_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 specifies that it returns portfolios for a connection and mentions error handling (returns fallback instead of throwing). It also notes bulk support via item_ids. However, it does not explicitly contrast with alternatives or state when not to use this tool.

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

A3.9/5.0
Disambiguation3/5

Most openfinance_* tools are clearly separated by resource and action, and the long descriptions help, but several pairs can trip up an agent: authenticate/connect both deal with login/connection state, openfinance_list_transactions and openfinance_list_transactions_by_item sound nearly identical, and marketplace internally exposes report_bug/list_tools functions that also exist as top-level tools. This is more than a single ambiguous edge.

Naming Consistency3/5

The 19 openfinance_* tools follow a clean get_/list_/update_ pattern and are easy to navigate, but the platform-level tools break the convention: authenticate, connect, marketplace, toolkit_info, report_bug, and show_version mix bare verbs, nouns, and noun-noun compounds. The pattern is not chaotic, but it is definitely mixed.

Tool Count3/5

25 tools is on the heavy end of the borderline range and is a large working set for an agent. The openfinance tools are individually justified and support batching, but the extra platform/marketplace tools add scope and some redundancy with report_bug and toolkit_info.

Completeness5/5

For a bank-data aggregation server, the surface is complete: connector discovery, linking/reconnecting/disconnecting, account lists and details, balances, transactions, categorization, credit-card bills, investments, loans, sync status, and provider health are all covered. There are no obvious dead ends in the main workflows.