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kevynf

AKBridge MCP Server

by kevynf

article_oman_rv_short

Read-onlyIdempotent

Retrieve daily realized volatility measures for major indices such as FTSE, DAX, and S&P 500 from the Oxford-Man Institute's Realized Library. Specify a symbol to get historical volatility data for analysis.

Instructions

Oxford-Man Institute of Quantitative Finance Realized Library 的数据 :param symbol: str FTSE: FTSE 100, GDAXI: DAX, RUT: Russel 2000, SPX: S&P 500 Index, STOXX50E: EURO STOXX 50, SSEC: Shanghai Composite Index, N225: Nikkei 225 :return: pandas.DataFrame

The Oxford-Man Institute's "realised library" contains daily non-parametric measures of how volatility financial assets or indexes were in the past. Each day's volatility measure depends solely on financial data from that day. They are driven by the use of the latest innovations in econometric modelling and theory to design them, while we draw our high frequency data from the Thomson Reuters DataScope Tick History database. Realised measures are not volatility forecasts. However, some researchers use these measures as an input into forecasting models. The aim of this line of research is to make financial markets more transparent by exposing how volatility changes through time.

This Library is used as the basis of some of our own research, which effects its scope, and is made available here to encourage the more widespread exploitation of these methods. It is given 'as is' and solely for informational purposes, please read the disclaimer.

The volatility data can be visually explored. We make the complete up-to-date dataset available for download. Lists of assets covered and realized measures available are also available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoFTSE
Behavior3/5

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

Annotations already declare read-only/idempotent behavior, so the bar is lower. The description adds context that the data is daily non-parametric measures, which helps interpret the output. However, it doesn't state behavior like invalid symbol handling or whether the 'short' version truncates data, leaving some gaps.

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

Conciseness2/5

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

The description includes a long boilerplate paragraph about the Oxford-Man library, its research, and disclaimers that is not needed for tool invocation. Key info (param, return) appears early, but the essay-like content inflates the description unnecessarily.

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

Completeness2/5

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

The tool has one optional parameter and no output schema. The description explains what realized measures are conceptually but doesn't specify the DataFrame structure, date range, or what differentiates the 'short' version from the full version. This is a meaningful gap.

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 has zero description coverage, so the description compensates by listing valid symbol values (FTSE, GDAXI, RUT, SPX, STOXX50E, SSEC, N225) with index names. This is directly useful for parameter selection. The default is not mentioned, but the param explanation is solid for the single parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource (Oxford-Man Realized Library) and states the return type, but lacks an explicit verb like 'retrieve' or 'get'. It also doesn't clarify what 'short' means relative to the sibling tool article_oman_rv, so the tool's specific function is ambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to choose this tool over article_oman_rv or article_rlab_rv. The long text describes the library's background but never mentions use cases, alternatives, or exclusions.

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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