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Zyberno stock valuation

by com.zyberno

Find US-listed companies by valuation and quality criteria

screen_stocks
Read-onlyIdempotent

Searches Zyberno's database of roughly 10,000 US-listed companies and returns those matching the numeric criteria you supply, ranked by a field you choose. All metrics are computed from SEC filings.

Use when the user wants to find, filter, rank, or count companies by their characteristics rather than asking about one company by name. Omit any filter you do not want applied; omitting all of them ranks the whole covered universe. Do not use it for a single known ticker (use get_stock_valuation), and do not use it to reconstruct the published monthly lists, which apply their own fixed thresholds, sector exclusions and curation (use list_flagged_stocks).

Returns at most 25 companies plus the total number that matched, so a query that is too broad or too narrow reports its own breadth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many companies to return, 1 to 25. Defaults to 10. The total number that matched is reported regardless.
sectorNoRestrict to one sector, spelled as Zyberno stores it, for example Technology, Healthcare, Industrials, Energy, Consumer Cyclical, Financial Services, Real Estate, Utilities, Basic Materials, Communication Services, Consumer Defensive.
roe_minNoMinimum return on equity in percent.
sort_byNoField to rank the matches by, largest first. Defaults to market_cap.
exchangeNoRestrict to one listing venue.
roic_minNoMinimum return on invested capital in percent. Pass 15 for 15 percent.
eps_sue_maxNoMaximum standardised earnings surprise (SUE), range -4 to +4.
eps_sue_minNoMinimum standardised earnings surprise (SUE), a winsorized z-score bounded to the range -4 to +4. Positive means the latest reported earnings beat the trend-based expectation. Pass 1 for a one standard deviation beat.
pb_ratio_maxNoMaximum price to book ratio.
pe_ratio_maxNoMaximum trailing price to earnings ratio. Companies with no meaningful P/E, including loss makers, are excluded when this is set.
brina_gap_maxNoMaximum Brina Gap in percentage points. Use a negative value to isolate companies whose price implies more growth than fundamentals support.
brina_gap_minNoMinimum Brina Gap in percentage points. Positive means the growth the business can fund exceeds the growth its price implies; negative means the price implies faster growth than the fundamentals support. Pass 3 for 3 percentage points.
fcf_yield_minNoMinimum free cash flow yield in percent. Pass 5 for 5 percent.
peg_ratio_maxNoMaximum PEG ratio, price to earnings divided by growth.
market_cap_maxNoMaximum market capitalisation in US dollars.
market_cap_minNoMinimum market capitalisation in US dollars, for example 2000000000 for 2 billion.
eps_cagr_3yr_minNoMinimum 3 year diluted EPS compound annual growth rate in percent.
current_ratio_minNoMinimum current ratio. Pass 1.5 for 1.5x.
momentum_12_1_maxNoMaximum 12 minus 1 price momentum in percent. Pass a negative value to isolate fallers.
momentum_12_1_minNoMinimum 12 minus 1 price momentum in percent: total return including dividends over the last 12 months, skipping the most recent month. Pass 20 for 20 percent, or -30 for a 30 percent fall. Values are unbounded above, and the strongest names in the universe can read in the hundreds of percent. Companies listed under 13 months have no window and are excluded whenever any momentum filter is set.
zyberno_score_minNoMinimum Zyberno quality score, on a 0 to 100 scale combining profitability, balance sheet strength and earnings consistency.
debt_to_equity_maxNoMaximum debt to equity ratio, as a ratio not a percent. Pass 1.5 for 1.5x.
earnings_yield_minNoMinimum earnings yield in percent, the inverse of P/E. Pass 8 for 8 percent.
net_margin_ttm_minNoMinimum trailing twelve month net margin in percent.
ev_ebitda_ratio_maxNoMaximum enterprise value to EBITDA ratio.
market_cap_categoryNoRestrict by size band, as an alternative to explicit market cap bounds. Bands are micro under $300M, small $300M to $2B, mid $2B to $10B, large $10B to $200B, mega $200B and above. Note that large excludes mega, so for the very largest companies use mega, and to cover both give market_cap_min instead.
gross_margin_ttm_minNoMinimum trailing twelve month gross margin in percent.
margin_of_safety_maxNoMaximum Margin of Safety in percentage points. Pass 10 for 10 percent.
margin_of_safety_minNoMinimum Margin of Safety in percentage points, where positive means the price sits below the discounted cash flow estimate. Pass 10 for 10 percent, not 0.1. Negative values are allowed.
revenue_cagr_3yr_minNoMinimum 3 year revenue compound annual growth rate in percent.
momentum_12_1_pct_maxNoMaximum cross-sectional momentum percentile, 0 to 100.
momentum_12_1_pct_minNoMinimum cross-sectional momentum percentile, 0 to 100, where 100 is the strongest momentum in the covered universe. Prefer this over the raw percentage when the user asks for strong or weak momentum in relative terms. Percentiles refresh on a monthly recompute, so they can lag the raw figure.
price_to_52w_high_maxNoMaximum ratio of current price to the 52 week high. Pass 0.7 to find stocks at least 30 percent below their high.
price_to_52w_high_minNoMinimum ratio of current price to the 52 week high, where 1.0 means the stock is sitting at its high. Pass 0.95 for within 5 percent of the high.
revenue_yoy_growth_minNoMinimum year over year revenue growth in percent.
operating_margin_ttm_minNoMinimum trailing twelve month operating margin in percent.
owner_earnings_yield_minNoMinimum owner earnings yield in percent. Owner earnings is the cash figure the discounted cash flow behind Margin of Safety is built on.
fundamental_growth_rate_maxNoMaximum fundamentally fundable growth rate in percent.
fundamental_growth_rate_minNoMinimum fundamentally fundable growth rate in percent, defined as ROIC times reinvestment rate. This is the first half of the Brina Gap on its own.
interest_coverage_ratio_minNoMinimum interest coverage ratio, operating income over interest expense.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds substantial non-obvious behavior beyond these hints: it returns at most 25 companies plus a total match count, ranks by a selectable field, and behaves breadth-reporting on too-broad/narrow queries. This is valuable transitive context not captured in annotations.

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 concise and well-structured: first sentence states the operation, second paragraph gives usage guidance with exclusions, third explains return behavior. Each sentence contributes distinct value, and the most important information is front-loaded.

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?

For a tool with 40 parameters and no output schema, the description covers the essential context: universe size, data source, return cap, total count, and sibling differentiation. It falls slightly short of a 5 by not describing the exact format of the returned companies (e.g., ticker list vs. full entity), but this is a minor gap given the schema richness.

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?

The input schema covers 100% of parameters with thorough descriptions, so no compensation is needed from the tool description. The description itself does not add parameter-level semantics beyond the schema, which is acceptable at the baseline for complete schema coverage.

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 searches a database of ~10,000 US-listed companies by numeric criteria and ranks results by a chosen field. It distinguishes itself from siblings by explicitly naming alternatives (get_stock_valuation for single ticker, list_flagged_stocks for curated monthly lists), making its purpose unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says exactly when to use it ('when the user wants to find, filter, rank, or count companies by their characteristics') and when not to, with named alternative tools. It also explains filter-omission behavior and the consequence of broad queries, giving clear decision rules for the agent.

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

A4.6/5.0
Disambiguation5/5

Each tool targets a clearly distinct purpose: single-company valuation (get_stock_valuation), market-level indicator (get_us_market_valuation), custom screening (screen_stocks), published lists (list_flagged_stocks), user-driven DCF arithmetic (calculate_dcf_value), and portfolio simulation (simulate_portfolio_outcomes). Descriptions even cross-reference to prevent misselection, making boundaries crisp.

Naming Consistency4/5

Most tools follow a verb_object snake_case pattern (calculate_dcf_value, get_stock_valuation, get_us_market_valuation, list_flagged_stocks, screen_stocks, simulate_portfolio_outcomes). All are consistent in style, though verbs vary somewhat between 'get', 'list', 'screen', 'calculate', and 'simulate', which is acceptable given the domain diversity.

Tool Count5/5

Six tools appropriately cover single-company analysis, market-level analysis, screening, published lists, DCF calculation, and portfolio simulation. Each tool holds clear territory without redundancy, and six is well within the ideal 3-15 range for a valuation-focused server.

Completeness4/5

The surface covers individual valuation, market valuation, screening, published lists, DCF modeling, and portfolio outcomes—covering the core analytics workflows. Minor gaps include no dedicated sector/index analysis, no price quotes or charts, and no explanation-of-framework tool, but these are explicitly noted as out of scope rather than dead ends, and the documented coverage is coherent for the stated purpose.

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