Skip to main content
Glama

screen_stocks

Screen Brazilian stocks by fundamental metrics like P/E, ROE, and dividend yield. Filter by sector and sort results to find investment opportunities.

Instructions

Screen ALL Brazilian stocks by fundamental metrics. Scans ~264 companies in one call.

Args: filters: Comma-separated filters like "pl_lt=15,roe_gt=10,dividend_yield_gt=5". Supported metrics: pl, pvp, ev_ebitda, roe, roa, roic, net_margin, gross_margin, ebitda_margin, dividend_yield, debt_equity, net_debt_ebitda, market_cap, lpa, vpa, current_ratio, p_sr, cagr_revenue_5y, cagr_earnings_5y. Use _gt (greater than) or _lt (less than) suffix. sector: Sector filter (e.g. "Bancos", "Energia Elétrica", "Petróleo e Gás") sort: Sort by metric (default: market_cap). Any filterable metric works. order: "asc" or "desc" (default: desc) limit: Max results (default 20)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNomarket_cap
limitNo
orderNodesc
sectorNo
filtersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Description implies a read-only operation (screening), which is consistent with no annotations. It explains the scope and filter behavior but does not detail rate limits or error handling.

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?

Well-structured with clear sections for args, but slightly verbose by repeating default values already present in the schema.

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?

Covers input semantics thoroughly; output schema exists so return values are handled. However, lacks details on pagination or behavior with empty results.

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

Parameters5/5

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

Input schema has 0% description coverage, but the description provides extensive details on each parameter, including filter format, supported metrics, and default values.

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?

Clearly states it screens all Brazilian stocks by fundamental metrics, scanning ~264 companies. Distinguishes from sibling tools like compare_stocks and get_fundamentals.

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?

Provides clear context for use (screening by fundamental metrics across all stocks) but does not explicitly exclude alternatives or mention when to use this tool versus siblings like search_companies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/viniciuslazzari/bolsai-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server