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Open-interest changes (Pro)

get_oi_changes

Day-over-day open-interest change per symbol (total, calls, puts) - fresh positioning being built or unwound. Pass a symbol for its OI-change series; omit it for market-wide gainers/losers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoTrading day, YYYY-MM-DD. Defaults to the latest available day.
sideNo
limitNo
symbolNoSingle ticker for its OI-change series; omit for the market-wide view.
min_prev_oiNoMinimum prior-day OI to filter low-base noise (default 1000).
min_change_pctNoMinimum absolute day-over-day change, e.g. 0.5 = 50%.

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It implicitly indicates a read-only get operation and adds interpretive context ('fresh positioning being built or unwound'), but it does not explicitly discuss safety, authorization, rate limits, or return format. The behavior is adequately sketched but not fully disclosed.

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 description is concise and well-structured, with two sentences. The first sentence states the core function and the breakdown, and the second explains the two invocation modes. Every word adds value, with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations and no output schema, the description relies on its own wording to complete the picture. It covers the primary use cases but leaves out return shape, definition of gainers/losers, and how parameters like side or min_change_pct interact. It is adequate for a simple query but not fully self-contained.

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 descriptions cover 4 of 6 parameters (67%), which is moderate. The description adds meaningful clarification for the symbol parameter by explaining the pass-vs-omit behavior, but it does not help with the side, limit, min_prev_oi, or min_change_pct parameters beyond what the schema already provides. The overall parameter semantics are acceptable but not enhanced.

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 clearly states the tool's purpose: day-over-day open-interest change per symbol with a breakdown by total, calls, and puts. It also distinguishes from siblings by highlighting the symbol-specific and market-wide gainers/losers modes, which is unique among the listed tools.

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 gives practical guidance on when to use the tool: pass a symbol for its OI-change series or omit it for market-wide gainers/losers. It does not explicitly name alternative tools or state when not to use it, but the provided context is clear enough for selection.

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

A4/5.0
Disambiguation4/5

Each tool targets a distinct analytical view (contract scan, per-symbol detail, history, sentiment, etc.), with clear boundaries. The only minor overlap is between get_symbol_flow and get_unusual_activity when filtering by a single symbol, but descriptions clarify the difference (single-symbol detail vs. broad scanner).

Naming Consistency5/5

All tool names follow a consistent get_<object> pattern (e.g., get_expiry_concentration, get_oi_changes), with ping as the standard exception for liveness checks. The naming is predictable and uniform.

Tool Count5/5

13 tools is well within the ideal range for a specialized data analytics server. Each tool covers a distinct query type and earns its place without redundancy.

Completeness5/5

The tool surface comprehensively covers the domain of unusual options flow discovery and analysis: data discovery, contract-level scans, per-symbol views, time series, sentiment, and market-wide aggregations. No obvious gaps or dead ends.