Skip to main content
Glama

rolling_average

Calculate a moving average for a column in a workbook sheet, using a configurable window size to analyze trends and filter out short-term variation.

Instructions

Calculate the rolling average 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'calculate,' which implies a read operation, but it does not state whether the tool writes to the sheet, returns a value, or handles edge cases like missing data or invalid windows. This ambiguity is notable given sibling tools like write_formulas and write_output.

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, front-loaded sentence with no fluff or redundant wording. It is concise and easy to parse, though it sacrifices important detail for brevity.

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 four parameters, no annotations, and no parameter documentation, yet the description leaves out window semantics, output behavior, and selection guidance among several closely related sibling tools. While an output schema exists, the description alone is not enough for an agent to understand when and how to invoke this tool correctly.

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 for undocumented parameters. It mentions 'column' and 'sheet' but does not explain the meaning of 'window,' the role of 'file_path,' or the default behavior. The parameter names are somewhat self-explanatory, but the description adds little semantic value 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 clearly states the action ('calculate') and the resource ('rolling average of a column in a workbook sheet'). It is specific enough to be understood, though it does not explicitly differentiate itself from the sibling rolling_volatility or summary_statistics tools.

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?

There is no guidance on when to use this tool versus alternatives such as rolling_volatility or summary_statistics. No exclusions, prerequisites, or selection criteria are provided, so an agent must infer the appropriate context from the name alone.

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