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Stock Screener

stock_screener
Read-onlyIdempotent

Stock screener (paid).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
isEtfNo"true" | "false"
limitNoMax rows (default 100). At least one filter should be set, or this is a slice of the whole exchange rather than a screen.
sectorNoe.g. "Technology", "Healthcare", "Energy", "Financial Services".
countryNo2-letter country code, e.g. "US".
exchangeNoe.g. "NASDAQ", "NYSE".
industryNoe.g. "Semiconductors", "Biotechnology".
betaMoreThanNoMinimum beta.
betaLowerThanNoMaximum beta.
priceMoreThanNoMinimum share price.
priceLowerThanNoMaximum share price.
volumeMoreThanNoMinimum average volume.
volumeLowerThanNoMaximum average volume.
dividendMoreThanNoMinimum dividend yield.
dividendLowerThanNoMaximum dividend yield.
isActivelyTradingNo"true" | "false"
marketCapMoreThanNoMinimum market cap in USD, e.g. 1000000000 for $1B+.
marketCapLowerThanNoMaximum market cap in USD.

TDQS

C2.3/5.0
Behavior3/5

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

The annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds only the word 'paid', which is a cost/access note, but lacks details on rate limits, output structure, or any nuances beyond the schema. With annotations present, this small addition warrants a mid-range score, but no contradiction exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three words cannot adequately describe a tool with 17 parameters and rich filtering options. While there is no redundancy, the text is under-specified; it sacrifices necessary detail for brevity.

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

Completeness1/5

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

For a complex screener with 17 parameters, a one-phrase description is completely inadequate. It does not explain what results look like, how filters work, or any prerequisites. The schema and annotations cover the data model, but the description itself fails to provide holistic context.

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 17 parameters have descriptions in the schema, giving 100% coverage. The tool description itself mentions none of the parameters, but the schema fully documents them, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Stock screener (paid)' essentially restates the tool's title with a parenthetical cost note. It lacks a verb and does not explain what the tool does (e.g., 'filters stocks by criteria'). This is a tautology rather than a functional description.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus any sibling tools like 'quote', 'search_symbol', or 'intraday'. The description only mentions that it is paid, which is a cost constraint, not a usage recommendation.

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

C2.5/5.0
Disambiguation2/5

Multiple tools overlap in purpose: quote/quote_short/historical_price/intraday for price data; balance_sheet/income_statement/cash_flow for financials; search_symbol/search_name/discover_tools for lookup; and a cluster of Pipeworx routers (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim) with unclear boundaries. Agents will frequently select the wrong tool.

Naming Consistency3/5

All tool names use consistent snake_case, but naming conventions vary widely: noun phrases (balance_sheet, entity_profile), bare verbs (forget, subscribe), verb+noun (compare_entities, resolve_entity), and adjective+noun (historical_price, recent_alerts). No single pattern dominates, making it harder to guess tool names.

Tool Count2/5

55 tools is excessive for a server labeled 'Fmp'. The core financial data tools are perhaps 20-25, while the rest are unrelated: memory utilities, prediction market analyzers, web scraping, and meta-routing tools. This bloated set dilutes the server's purpose and burdens the agent with irrelevant options.

Completeness2/5

For the declared domain (FMP financials), the set covers the main statements but lacks tools like segment data, insider trades (listed as paid), or ownership details (also paid). Conversely, it includes many tools for prediction markets and general data retrieval that don't belong here, creating a mismatch between server name and actual capability.