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stock_screener

Filter Nifty 50 or S&P 500 stocks by financial metrics like P/E ratio, ROE, market cap, dividend yield, and sector to identify investment opportunities.

Instructions

Screen stocks by multiple financial criteria. [PRO]

Filter Nifty 50 or S&P 500 stocks by P/E ratio, ROE, market cap, dividend yield, debt/equity ratio, and sector.

Args: exchange: "NSE" for Indian stocks, "US" for US stocks (default: NSE) pe_max: Maximum P/E ratio (e.g., 15 for value stocks). 0 = no filter. pe_min: Minimum P/E ratio. 0 = no filter. roe_min: Minimum Return on Equity in % (e.g., 20). 0 = no filter. market_cap_min: Minimum market cap in USD (e.g., 1000000000 for $1B). 0 = no filter. dividend_yield_min: Minimum dividend yield in % (e.g., 2). 0 = no filter. debt_equity_max: Maximum debt-to-equity ratio (e.g., 50). 0 = no filter. sector: Filter by sector name (e.g., "Technology", "Financial"). Empty = all. limit: Max number of results (default: 15)

Examples: stock_screener("NSE", pe_max=15, roe_min=20) → Value stocks with high ROE stock_screener("NSE", dividend_yield_min=3) → High dividend yield stocks stock_screener("US", pe_max=20, sector="Technology") → Cheap US tech stocks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
exchangeNoNSE
pe_maxNo
pe_minNo
roe_minNo
market_cap_minNo
dividend_yield_minNo
debt_equity_maxNo
sectorNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden. It successfully documents the '0 = no filter' convention and exchange options, but fails to explain the '[PRO]' tag, rate limits, or behavior when no matches are found.

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?

Well-structured with clear sections (description, Args, Examples). Despite length needed to document 9 parameters, every sentence earns its place; the front-loaded purpose statement followed by granular args and illustrative examples is optimal for agent comprehension.

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 output schema exists (absolving the description from detailing return values), the description is complete. It covers all 9 parameters, provides usage examples, and explains the filtering logic, making it sufficient for invocation.

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?

Excellent compensation for 0% schema description coverage. The Args section provides detailed semantics for all 9 parameters with units (USD, %), valid values ('NSE' vs 'US'), and concrete examples (e.g., '15 for value stocks', '1000000000 for $1B').

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 'Screen stocks by multiple financial criteria' and specifies the exact universe (Nifty 50 or S&P 500) and filterable metrics (P/E, ROE, etc.), distinguishing it from sibling tools like stock_quote or nse_quote which handle single-stock lookups.

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?

While it lacks explicit 'use this instead of X' comparisons, the Examples section provides strong usage patterns ('Value stocks with high ROE', 'Cheap US tech stocks') that implicitly guide when to use the screener versus single-instrument lookups.

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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