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get_fails_to_deliver

Read-only

SEC fails-to-deliver history for one ticker -- the settlement-failure side of short pressure. Returns {ticker, days, history, count, window, coverage, as_of, summary}; each row is {date (settlement date), fails (SHARES, not dollars), price (USD), description}, OLDEST-FIRST. days (default 180, hard cap 730) is anchored to the latest LOADED settlement date, not to today; end_date ends it elsewhere. An empty or thin history describes the loaded SEC files, not an absence of fails: read coverage and summary before reading a gap. Prices are NOT split-adjusted. An unreachable store REFUSES (DATA_UNAVAILABLE). Pair with ol_short_interest_trend for the other half. Source: SEC Fails-to-Deliver dataset (published twice monthly, ~3-week lag). Caveats ride the response's tool_notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoTrailing window in days (default 180, max 730), ending at `as_of` unless end_date is given
tickerYesStock ticker symbol (e.g. GME)
end_dateNoISO date (YYYY-MM-DD) the window ends on; default = the latest loaded settlement date. Pass today's date to measure against the calendar.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Adds rich behavioral context beyond readOnlyHint: returns structure, oldest-first ordering, anchoring of `days` to latest loaded settlement date (not today), coverage caveats, unadjusted prices, and an explicit refusal mode (DATA_UNAVAILABLE). This is exactly the kind of detail annotations cannot provide.

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?

Dense but front-loaded: purpose appears first, followed by return shape, then parameter behavior, then caveats. Every sentence carries useful information, though the single-paragraph format is slightly heavy.

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?

Without an output schema, the description fully covers return fields, row semantics, coverage caveats, and tool_notes placement. An agent has everything needed to interpret results and avoid misreading gaps.

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%, but the description adds meaningful nuance: `days` is anchored to the latest loaded settlement date rather than today, `end_date` can extend the window, and row values are in SHARES not dollars. This goes beyond the schema's parameter descriptions.

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?

States a specific verb ('returns history') and resource ('SEC fails-to-deliver'), plus distinguishing scope ('settlement-failure side of short pressure'). An agent can immediately tell this apart from siblings like get_13f_holdings or ol_short_interest_trend.

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?

Names the complementary sibling ('Pair with ol_short_interest_trend for the other half') and gives clear context for when the tool is useful. It does not explicitly state when not to use it, so it falls short of the full 'when/when-not' bar.

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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