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Largest Short Volume by Day

GetLargestShortVolume
Read-only

Get the stocks with the largest daily short sale volume for a single trading day (defaults to the latest available), from FINRA's daily short sale volume files, sorted by short volume descending. Short % is the share of that day's FINRA-facility (off-exchange/TRF) volume sold short — 40-50% is a normal market-making baseline — NOT short interest (the open short position; use GetShortInterest/GetShortInterestSnapshot for positions and GetShortSqueezeScores for squeeze candidates; use GetShortVolume for one stock's daily history). Pass sortBy=shortPercent with a minTotalVolume floor to rank by short intensity instead of raw size.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoTrading day in YYYY-MM-DD format (defaults to the latest available day)
offsetNoNumber of ranked results to skip before returning rows — pass the previous call's last row number to page past the maxResults cap (default: 0)
sortByNoSort key: shortVolume (default) or shortPercent — with shortPercent set a minTotalVolume floor, otherwise illiquid names dominateshortVolume
maxResultsNoMaximum number of results to return (default: 50, max: 500)
minShortVolumeNoMinimum short volume filter (default: 0)
minTotalVolumeNoMinimum total FINRA-reported volume filter, in shares (default: 0 = no floor)

TDQS

A4.7/5.0
Behavior5/5

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

The description explains semantic nuances beyond the readOnlyHint/destructiveHint annotations: what 'Short %' means, a normal market-making baseline (40-50%), and clarifies that this is not short interest. It also discloses the default date behavior, sort order, and data source. No contradiction with 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?

Three information-dense sentences cover the core purpose, clarify a potentially confusing metric (short % vs short interest), and provide usage guidance. The main action is front-loaded, and every clause adds value 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 read-only ranked list tool, the description is complete: it states the data source, default date, sort ordering, output semantics, and when to use alternatives. No output schema is present, but the description sufficiently implies the return shape (a sorted list of stocks with volume/short % metrics) for reliable 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 parameters are already well-documented. The description adds contextual guidance for sortBy and minTotalVolume (e.g., the need for a floor when using shortPercent), but it does not deeply elaborate on each parameter beyond what the schema provides. 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 uses a specific verb ('Get') and clearly identifies the resource: stocks with the largest daily short sale volume for a single trading day, sourced from FINRA. It explicitly distinguishes this from sibling tools like GetShortVolume and GetShortInterest, making the tool's unique purpose unambiguous.

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 provides explicit guidance on when to use this tool versus alternatives, naming GetShortInterest/GetShortInterestSnapshot for positions, GetShortSqueezeScores for squeeze candidates, and GetShortVolume for single-stock history. It also gives a concrete usage tip for ranking by shortPercent with a minTotalVolume floor.

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.