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equibles

by io.github.daniel3303

Fails-to-Deliver Data

GetFailsToDeliver
Read-only

Get fails-to-deliver (FTD) data for an exact listed stock or exchange-traded fund from the SEC's twice-monthly FTD files. Quantity is the aggregate net fail-to-deliver position OUTSTANDING on each settlement date — a balance, not that day's new fails, so never sum Quantity across dates. Price is the previous trading day's closing price (SEC file convention, not a settlement price) and Value = Quantity × Price. Within the covered window (the output names the earliest fully covered settlement date), dates absent from the table had no reported fails; earlier dates are only partially covered, so their absence is not evidence of no fails. The SEC publishes each half-month batch with roughly a two-week lag, so the newest rows trail today. High or persistent FTD balances may indicate naked short selling or settlement issues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesExact stock or ETF ticker symbol (e.g., AAPL, GME, SPY)
endDateNoEnd date in YYYY-MM-DD format (defaults to latest available)
startDateNoStart date in YYYY-MM-DD format (defaults to 3 months ago)
maxResultsNoMaximum number of records to return — keeps the most recent N settlement dates in the range, displayed oldest to newest (default: 90, max: 500)

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / properties / ticker / description
      Previous value: -"Stock ticker symbol (e.g., AAPL, GME, AMC)"New value: +"Exact stock or ETF ticker symbol (e.g., AAPL, GME, SPY)"
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The annotations already mark this as read-only and non-destructive, and the description adds substantial non-obvious behavior: Quantity is an outstanding balance rather than new fails and must not be summed, Price follows the SEC prior-day close convention, coverage windows explain missing dates, and publication lag means newest rows trail today. This goes well beyond annotation signals.

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 first sentence front-loads the core purpose, and every subsequent sentence adds a distinct, necessary caveat or definition. Though lengthy, it is dense with useful information and contains no filler or 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?

With no output schema, the description compensates by explaining Quantity, Price, Value, date coverage, missing-date semantics, and data lag. It provides enough interpretive context for an agent to call the tool and correctly understand its results.

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?

The input schema has 100% description coverage for all four parameters, so the description does not need to restate them. It adds no new input-parameter meaning beyond the schema, and the baseline of 3 applies because the schema handles the burden.

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 states a specific verb and resource: retrieving fails-to-deliver data for an exact listed stock or ETF from the SEC's twice-monthly FTD files. It is clearly distinguishable from related short-selling tools like GetShortInterest or GetShortVolume because it anchors the data source and metric.

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

Usage Guidelines4/5

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

The description makes the intended use clear: analyzing SEC-reported FTD balances for a single ticker, with coverage and lag caveats. It does not explicitly name alternatives or say when not to use this tool, but the FTD-specific framing leaves little ambiguity about its niche.

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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