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Zyberno stock valuation

Valuation record for one US-listed company

get_stock_valuation
Read-onlyIdempotent

Returns Zyberno's stored valuation record for a single US-listed company: Margin of Safety against a discounted cash flow estimate, the Brina Gap (the growth rate the business can fund from its own returns minus the growth rate its current price implies), the Brina Matrix quadrant those two produce together, the Zyberno quality score, and trailing twelve month fundamentals from SEC filings.

Use when the user names a company or ticker and wants to know how it is valued. This is also the tool for questions phrased without the framework's vocabulary: what growth rate is priced into a stock, what the market expects from a company, what a reverse DCF on it implies, whether its growth expectations look too high or too low, or whether a cheap-looking stock is actually a value trap. Do not use it to find or rank companies (use screen_stocks), to retrieve the published monthly lists (use list_flagged_stocks), or for price quotes, charts, news, analyst ratings, earnings dates, or non-US listings, none of which this server holds.

Records refresh on a rolling cycle of roughly two weeks per company, so figures can lag a company's newest filing for part of that cycle. Every response states the date its data was computed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTicker symbol of a US-listed company, for example AAPL, MSFT, or BRK.B. Case insensitive. Non-US listings and most OTC ADRs are not covered and return no data.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnly, openWorld, idempotent), the description discloses that records are stored, refresh on a rolling ~2-week cycle, may lag the newest filing, and that each response states the computation date. This gives the agent a clear picture of data freshness and limitations.

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?

Though longer than many descriptions, every sentence carries useful content: return fields, use cases, exclusions, and data freshness. It is well-structured, front-loaded with the core purpose, and avoids redundancy or filler.

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 tool's moderate complexity, no output schema, and rich annotation set, the description provides a complete picture: return payload, usage guidance, exclusions, data lag caveat, and response date guarantee. The agent has enough context to invoke the tool correctly and set expectations.

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 already fully covers the single parameter 'symbol' with format, case-insensitivity, and coverage limitations (100% schema coverage). The description reinforces the US-listed scope but does not add significant new parameter-level meaning beyond the schema.

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 uses a specific verb ('Returns') and names the exact resource ('Zyberno's stored valuation record for a single US-listed company') plus the key fields included. It clearly distinguishes this tool from siblings like screen_stocks and list_flagged_stocks by scope and output.

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?

It explicitly states when to use the tool ('Use when the user names a company or ticker and wants to know how it is valued'), provides alternative phrasings, and explicitly lists when not to use it with named alternatives (screen_stocks, list_flagged_stocks) and exclusions like price quotes, news, and non-US listings.

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.

Resources