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screen_companies

Find US public companies whose latest-fiscal-year fundamentals match filters (minimum revenue, margins, ROE, growth; sector; profitable-only), sorted and limited. Returns a ranked list of companies with their key figures. Data traces to SEC EDGAR filings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoMatch ticker prefix or company-name substring
sortNoSort column; prefix with - for descending. e.g. -revenue (default), net_margin, -return_on_equity, revenue_growth
limitNoMax results, 1-100 (default 25)
sectorNoOne of: Agriculture, Mining, Construction, Manufacturing, Transportation & Utilities, Wholesale Trade, Retail Trade, Finance & Real Estate, Services, Public Administration
roe_minNoMinimum return on equity, percent
profitableNoOnly companies with positive net income
revenue_minNoMinimum annual revenue, USD (e.g. 1000000000 for $1B)
net_income_minNoMinimum annual net income, USD
net_margin_minNoMinimum net margin, percent
gross_margin_minNoMinimum gross margin, percent (e.g. 40)
total_assets_minNoMinimum total assets, USD
debt_to_equity_maxNoMaximum debt-to-equity ratio
revenue_growth_minNoMinimum year-over-year revenue growth, percent
operating_margin_minNoMinimum operating margin, percent
Behavior3/5

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

With no annotations, the description carries full burden. It discloses data source (SEC EDGAR) and that it uses latest-fiscal-year data, but does not detail output structure or any potential side effects. Some behavioral traits are missing.

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?

The description is two sentences that efficiently convey purpose, filters, output, and data source with no unnecessary words.

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

Completeness3/5

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

Given 14 parameters and no output schema, the description should provide more detail on return fields and behavior. It states 'ranked list of companies with their key figures' but does not specify which figures, leaving ambiguity.

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

Parameters3/5

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

All 14 parameters have descriptions in the schema (100% coverage), so the description adds minimal extra meaning beyond summarizing filter categories. Baseline 3 is appropriate.

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 verb (screen/find) and resource (US public companies), and distinguishes from the sibling tool 'get_fundamentals' by focusing on filtering across companies rather than retrieving data for a single company.

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 implicitly suggests usage for filtering companies by fundamentals, and the sibling tool name provides context, but it lacks explicit guidance on when to choose this tool over alternatives.

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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