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equibles

by io.github.daniel3303

Largest Short Volume by Day

GetLargestShortVolume
Read-only

Get the exact listed securities, including ETFs, 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 operating-stock squeeze candidates; use GetShortVolume for one listed security'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)

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / offset
      Added value: +{
+  "default": 0,
+  "description": "Number of ranked results to skip before returning rows — pass the previous call's last row number to page past the maxResults cap (default: 0)",
+  "type": "integer"
+}
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate a read-only, non-destructive operation, and the description adds valuable behavioral detail beyond that: the data comes from FINRA daily short sale volume files, results are sorted by short volume descending, and Short % is defined as the share of FINRA-facility (off-exchange/TRF) volume sold short with a normal market-making baseline of 40-50%. It also explicitly corrects a common misunderstanding by stating this is NOT short interest.

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 dense sentences carry substantial information without redundancy. The primary purpose is front-loaded, followed by the necessary short-interest distinction, sibling routing, and a parameter usage tip. Every sentence earns its place.

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 list tool with six fully documented optional parameters, the description is complete: it covers data source, scope, default behavior, sorting, metric interpretation, alternatives, and a caveat about ranking by short intensity. No output schema exists, but the task is straightforward and the description provides enough context for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents parameters. The description adds meaning beyond the schema by explaining when to use sortBy=shortPercent, why a minTotalVolume floor is needed with it, and warning that illiquid names dominate otherwise. This is actionable parameter guidance rather than repetition.

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 names a specific verb and resource: retrieving the exact listed securities with the largest daily short sale volume for a single trading day. It further distinguishes itself from siblings by noting it covers ETFs and defaults to the latest day, and by explicitly listing sibling tools for short interest, squeeze scores, and single-security short volume.

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: use GetShortInterest/GetShortInterestSnapshot for positions, GetShortSqueezeScores for squeeze candidates, and GetShortVolume for one security's daily history. It also instructs when to use sortBy=shortPercent with a minTotalVolume floor, making the call path clear.

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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