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rolling_volatility

Calculate rolling volatility (standard deviation of percentage change) for a specified column in an Excel sheet, using a defined window to assess price or metric variability over time.

Instructions

Calculate the rolling volatility (standard deviation of percentage change) of a column in a workbook sheet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnYes
windowNo
file_pathYes
sheet_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It discloses the calculation method (std dev of percentage change) but does not state whether the window is trailing/centered, how missing values are handled, whether the result is added as a new column or returned, or whether the operation modifies the workbook. These are material behavioral gaps for a calculation tool.

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?

The description is a single, focused sentence that front-loads the core purpose and formula. It is concise and readable, though it could add a brief usage note without becoming bloated.

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 4 parameters, no annotations, and an output schema, but the description does not explain the return value, the window behavior, or data requirements. For a calculation tool with no annotation coverage, an agent needs more context to invoke it correctly and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains 'column' and 'window' implicitly via the formula, but it does not clarify the meaning of 'window' (e.g., number of periods), the expected format of file_path, or the role of sheet_name. The description adds only minimal meaning beyond the schema.

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

Purpose4/5

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

The description states a specific verb ('Calculate') and resource ('rolling volatility ... of a column in a workbook sheet'), and the formula is clarified as standard deviation of percentage change. It is distinguishable from siblings like rolling_average and percentage_change, though it does not explicitly name them.

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 given on when to use this tool versus rolling_average, percentage_change, or summary_statistics. The description implies a financial/time-series context but does not state prerequisites, such as needing a date column or sorted data, nor when an alternative would be preferable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.