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Stochastic Oscillator

GetStochasticOscillator
Read-only

Stochastic Oscillator (%K and %D) for a stock. %K measures the close relative to the high/low range over the lookback window; %D is the smoothed signal line (simple moving average of %K). Useful for spotting overbought (>80) and oversold (<20) conditions. The lookback window is warmed up on price history fetched before startDate, so values do not depend on the requested range's left edge.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock ticker symbol (e.g., AAPL, MSFT). Class shares use a dash (BRK-B); the dot form (BRK.B) is also accepted.
dPeriodNoSmoothing window for %D (default: 3)
endDateNoEnd date in YYYY-MM-DD format (defaults to latest available)
kPeriodNoLookback window for %K (default: 14)
startDateNoStart date in YYYY-MM-DD format (defaults to 6 months ago)
maxResultsNoMaximum number of records to return (default: 60, max: 500); the newest rows are kept and listed newest first.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral context beyond annotations: the lookback window is warmed up on price history before startDate, so values don't depend on the range's left edge. This helps agents understand why results may differ from naive computation. It doesn't disclose return format, but for a read-only indicator with no output schema, this is solid.

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 four sentences of high-density information: what it is, formula components, use case, and a key computation nuance. Every sentence earns its place with no redundancy. It is front-loaded and easy to scan.

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

Completeness4/5

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

For a technical indicator with configurable parameters, the description covers the core semantics, usage, and a critical warm-up behavior. The absence of an output schema is mitigated by explaining the indicator's components. It could mention the return rows (e.g., date, %K, %D) or percentages, but overall it is sufficiently complete for an agent to understand what to expect.

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 coverage is 100%, so the description doesn't need to explain each parameter. The description does add conceptual meaning by defining %K and %D in terms of the lookback window and smoothing, which relates to kPeriod and dPeriod, but it doesn't directly enrich parameter syntax or constraints. Baseline 3 is appropriate.

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 'Stochastic Oscillator (%K and %D) for a stock,' clearly identifying the tool as a specific technical indicator. It then explains what %K and %D measure, distinguishing it from other indicator tools like GetAverageTrueRange or GetBollingerBands. The purpose is concrete and unambiguous.

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 states 'Useful for spotting overbought (>80) and oversold (<20) conditions,' providing clear guidance on when the tool is appropriate. It does not explicitly mention alternatives or exclusions, but the use case is well-defined, earning a 4 rather than a 5.

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.