Cotação de ações, FIIs e BDRs da B3 em lote (até 20 tickers numa chamada), com opção de dados fundamentalistas (via modules: balanceSheetHistory, incomeStatementHistory, cashflowHistory, etc.), dividendos e histórico de preços.
| Name | Required | Description | Default |
|---|---|---|---|
| range | No | ||
| modules | No | ||
| tickers | Yes | ||
| interval | No | ||
| dividends | No | ||
| fundamental | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so basic safety is known. The description adds operational constraints like a batch limit of 20 tickers and the availability of modules for fundamental data, which adds useful context. However, it does not disclose return formats, rate limits, or behavior when optional parameters are omitted. This aligns with the calibration example where the description adds some value but not rich behavioral context.
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?
The description is a single, dense sentence that front-loads the primary purpose (quotes for B3 instruments) and then enumerates optional capabilities. No wasted words; every clause provides relevant information. It is highly concise and well-structured.
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?
The tool has 6 parameters, no output schema, and zero parameter descriptions, so the description carries a heavy burden. It covers the core function, batch limit, fundamental data modules, dividends, and price history, but does not specify defaults, parameter combinations, or response structure. This is adequate but incomplete for a tool with this complexity.
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?
Schema description coverage is 0%, so the description must compensate. It explains 'modules' as fundamental data modules (with examples), 'dividendos' as an option, and 'histórico de preços' hints at range/interval usage. However, the description does not clarify the exact role of 'range' and 'interval' beyond price history, nor the relationship between 'fundamental' and 'modules'. It adds partial meaning but leaves several parameters underspecified.
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 tool's function: providing quotes for B3 stocks, FIIs, and BDRs in batch mode, with additional options for fundamental data, dividends, and price history. It distinguishes from sibling tools like mercado_crypto and mercado_currency by specifying the B3 equities context.
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 gives clear context for when to use the tool: for B3 equity/FII/BDR quotes, fundamental data, dividends, and historical prices. While it does not explicitly list exclusions or name alternative tools, the specificity ('B3', 'ações, FIIs e BDRs') implies when not to use it (e.g., for crypto or currency quotes). This is clear context but lacks explicit alternative references.
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 tool has a clearly distinct purpose: authenticate and connect are separate (login vs status), the mercado_* tools each target a specific asset class or function (crypto, currency, listing, macro, quote, ticker search), and platform tools like marketplace, report_bug, show_version, and toolkit_info are unambiguous. There is no meaningful overlap that would cause an agent to select the wrong tool.
The naming is mixed: financial tools consistently use the 'mercado_' prefix, but platform tools use a variety of conventions—single words (authenticate, connect, marketplace), verb_noun with underscores (report_bug, show_version), and nouns (toolkit_info). While readable, this inconsistency is noticeable and not as uniform as a strong verb_noun pattern.
At 12 tools, the count is within a reasonable range, but roughly half of the tools are platform-management concerns (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) rather than financial data. This makes the set feel heavier and less focused than a pure market-data server, though it's not excessive.
The financial data tools cover a broad range: quotes, screening, crypto, exchange rates, macro indicators, and ticker discovery—sufficient for a Brazilian market data server. Some potential gaps like news or portfolio management are out of scope, and the platform tools add extra utility, leaving no critical missing operations for the core purpose.