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equibles

by io.github.daniel3303

Short Interest History

GetShortInterest
Read-only

Get bi-monthly short interest history for a stock from FINRA. Shows the reported short position, change from the previous settlement, average daily volume, and days to cover per settlement date. Share counts are restated onto today's split basis so the series stays continuous across stock splits; days to cover is as reported (FINRA caps it at 999.99). High days-to-cover (>5) suggests a potential short squeeze — for short interest as a % of shares outstanding and an actual squeeze-candidate ranking use GetShortSqueezeScores; for the market-wide latest settlement use GetShortInterestSnapshot. FINRA publishes each file weeks after it measures the position, so the answer may also carry an estimate of the settlement that has not been reported yet — it appears BELOW the table, labelled as an estimate, and is a model prediction rather than reported data; never present it as a FINRA figure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker symbol (e.g., AAPL, GME, TSLA)
endDateNoEnd date in YYYY-MM-DD format (defaults to latest available)
startDateNoStart date in YYYY-MM-DD format (defaults to 1 year ago)
maxResultsNoMaximum number of records to return — keeps the most recent N settlements in the range, displayed oldest to newest (default: 24, max: 500)

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint/destructiveHint annotations, the description discloses critical data behaviors: share counts are restated onto today's split basis, days to cover is capped at 999.99, FINRA publishes weeks later, and the estimate for un-reported settlements is a model prediction that must not be presented as FINRA data. This is rich, non-obvious context.

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

Conciseness4/5

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

The description is longer than a typical two-sentence definition, but every sentence provides meaningful caveats or alternatives. It is front-loaded with the core purpose and then details important data quirks. Slightly verbose but earns its length.

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?

With no output schema, the description compensates by enumerating the returned columns (short position, change, average daily volume, days to cover) and explaining the estimate placement. It also covers the reporting lag and split adjustment, making the tool's behavior fully understandable without additional documentation.

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. The description does not add extra parameter-level semantics beyond the schema; it focuses on data interpretation rather than parameter syntax. No deduction is warranted, but no bonus either.

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 opens with a specific verb and resource: 'Get bi-monthly short interest history for a stock from FINRA.' It clearly distinguishes the tool from siblings by naming GetShortSqueezeScores and GetShortInterestSnapshot, making the scope 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?

Explicit usage guidance is provided: high days-to-cover suggests a short squeeze, and the description directly states which sibling tool to use for alternative metrics ('use GetShortSqueezeScores; ... use GetShortInterestSnapshot'). This gives clear when-to-use and when-not-to-use context.

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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