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equibles

by io.github.daniel3303

Stock Screener

ScreenStocks
Read-only

Screen listed stocks with optional min/max bounds for price, market cap, institutional ownership, short data, insider activity, valuation, growth, margins, liquidity and earnings. Exact sector, industry, covered-index membership and going-concern filters are also available. A stock missing a bounded metric is excluded. Results use the requested sort (market cap descending by default), are paged, and include each dataset's vintage. Filtering or sorting on a fundamental metric adds that metric to the result table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoResult page (default 1) — combine with maxResults to walk past the first page of a large match set.
indexNoKeep only members of one covered index, by slug or name (sp-500, S&P 500, nasdaq-100, Russell 2000). An unknown name returns the accepted list.
maxPeNoMaximum trailing-twelve-month price-to-earnings ratio (e.g. 15 for value screens).
minPeNoMinimum trailing-twelve-month price-to-earnings ratio.
sectorNoExact sector name (e.g. Technology, Healthcare). An unknown name returns the accepted list.
sortByNoSort key: marketcap, ticker, name, price, filers, filerdelta, sipct, dtc, squeeze, sentiment, insiderbuy, pe, divyield, revgrowth, grossmargin, dollarvol or netincome. Default marketcap. An unknown key is rejected, never silently ignored.marketcap
tickersNoOptional list of up to 200 tickers to restrict the screen to, for scoring stocks the user already holds or follows instead of searching the whole market. Every other bound still applies and sortBy still orders the result. Class-share dots (BRK.B) resolve to the listed form, a secondary listing resolves to its issuer, and any symbol outside the covered universe is named back to you.
industryNoExact industry name (e.g. Semiconductors). Prefer sector for broad groups.
maxPriceNoMaximum share price in dollars.
minPriceNoMinimum share price in dollars.
maxResultsNoMaximum rows to return (default 50; clamped to 1-200).
maxMarketCapNoMaximum market capitalization in dollars.
maxNetIncomeNoMaximum trailing-twelve-month net income in dollars.
minMarketCapNoMinimum market capitalization in dollars.
minNetIncomeNoMinimum trailing-twelve-month net income in dollars (0 keeps profitable companies only).
maxFilerCountNoMaximum number of 13F institutional filers holding the stock.
maxFilerDeltaNoMaximum quarter-over-quarter change in filer count.
minFilerCountNoMinimum number of 13F institutional filers holding the stock.
minFilerDeltaNoMinimum quarter-over-quarter change in filer count.
sortAscendingNoSort ascending instead of descending.
maxDaysToCoverNoMaximum days to cover.
maxGrossMarginNoMaximum gross margin in percent (0-100).
minDaysToCoverNoMinimum days to cover.
minGrossMarginNoMinimum gross margin in percent (0-100).
maxDollarVolumeNoMaximum trailing-3-month average daily dollar volume in dollars.
maxSqueezeScoreNoMaximum composite short-squeeze score (0-100, peer-relative).
minDollarVolumeNoMinimum trailing-3-month average daily dollar volume in dollars (e.g. 5000000 = $5M/day).
minSqueezeScoreNoMinimum composite short-squeeze score (0-100, peer-relative; higher = more squeeze-prone).
maxDividendYieldNoMaximum trailing dividend yield in percent.
maxNetInsiderBuyNoMaximum net insider buying in dollars over the trailing 90 days.
maxRevenueGrowthNoMaximum revenue growth in percent, latest quarter vs the same quarter a year earlier.
minDividendYieldNoMinimum trailing dividend yield in percent (e.g. 3 = 3%).
minNetInsiderBuyNoMinimum net insider buying in dollars over the trailing 90 days.
minRevenueGrowthNoMinimum revenue growth in percent, latest quarter vs the same quarter a year earlier.
maxInsiderSentimentNoMaximum composite insider-sentiment score (0-100, peer-relative).
minInsiderSentimentNoMinimum composite insider-sentiment score (0-100, peer-relative; higher = more aggressive insider accumulation).
hasGoingConcernDoubtNoTrue keeps only companies whose latest filing states unalleviated going-concern doubt; false keeps only companies without the flag.
maxShortInterestPercentNoMaximum short interest as a percent of shares outstanding (0-100).
minShortInterestPercentNoMinimum short interest as a percent of shares outstanding (0-100).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / tickers
      Added value: +{
+  "default": null,
+  "description": "Optional list of up to 200 tickers to restrict the screen to, for scoring stocks the user already holds or follows instead of searching the whole market. Every other bound still applies and sortBy still orders the result. Class-share dots (BRK.B) resolve to the listed form, a secondary listing resolves to its issuer, and any symbol outside the covered universe is named back to you.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  2. Changed1 schema field changed
    • addedInput schema / properties / index
      Added value: +{
+  "default": null,
+  "description": "Keep only members of one covered index, by slug or name (sp-500, S&P 500, nasdaq-100, Russell 2000). An unknown name returns the accepted list.",
+  "type": "string"
+}
  3. First observed

TDQS

A3.9/5.0
Behavior5/5

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

Annotations already mark the operation as read-only and non-destructive, but the description adds substantial behavioral detail beyond that: stocks missing a bounded metric are excluded, results respect the requested sort with a default of market cap descending, results are paged, each dataset's vintage is included, and filtering/sorting on a fundamental metric dynamically adds that metric to the result table. These are non-obvious behaviors that materially affect how an agent interprets results.

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 compact but information-dense, covering the tool's scope, behavior, defaults, and dynamic output characteristics in three sentences. Every sentence contributes unique value, and the most important behavioral rules (exclusion of missing metrics, dynamic metric inclusion) are stated explicitly without redundancy.

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?

For a complex tool with 39 optional parameters and no output schema, the description covers the crucial behavioral context an agent needs: exclusion semantics, sorting and paging defaults, vintage inclusion, and dynamic result expansion. The schema handles per-parameter detail, so nothing essential is missing for correct invocation.

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?

Schema description coverage is 100%, so the baseline is 3; every parameter already has a detailed description including units, defaults, and examples. The tool description adds only a high-level category summary without introducing parameter-specific meanings, so it neither harms nor improves on the schema.

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

Purpose4/5

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

The description uses a specific verb ('Screen') and resource ('listed stocks') and clearly enumerates the filter categories (price, market cap, institutional ownership, short data, insider activity, valuation, growth, margins, liquidity, earnings). It does not explicitly distinguish itself from sibling tools by name, but its role as a multi-criteria screener is unambiguous, so it earns a 4 rather than a 5.

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?

The description explains what the tool does but provides no guidance on when to use it versus alternative tools or when not to use it. There are no exclusions, prerequisites, or references to sibling tools. The usage context is only implied by the tool's purpose, not explicitly stated.

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

B3.4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with detailed descriptions that cross-reference related alternatives. A few near-duplicate names could cause misselection, notably SearchDocument versus SearchDocuments and GetCftcPositioning versus GetLatestCftcPositioning.

Naming Consistency5/5

Tool names consistently follow a VerbNoun camelCase pattern: Get for retrievals, Search for discovery, List/Read for document access, and Add/Close/Remove/Update/Watch/Create/Delete for portfolio mutations. Despite the large count, there is no mixing of naming conventions or unpredictable verb styles.

Tool Count1/5

108 tools is an extreme surface area, far beyond the 3-15 well-scoped range and well past the 25+ threshold. Even for a broad financial data platform, this creates a heavy selection burden and substantial context overhead for agents.

Completeness4/5

The server covers an unusually wide domain: prices, fundamentals, SEC filings, options, insider activity, 13F holdings, short interest, macro data, funds, IPOs, and full portfolio lifecycle management. Notable gaps remain, such as a basic company profile/ticker-resolution tool, dividend history, and analyst estimates, so it is not a perfect 5.

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