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rolling_stats

Read-onlyIdempotent

Compute rolling window statistics for any indicator to smooth noise and highlight trends. Choose mean, standard deviation, min, max, or sum over a window of 2 to 100 periods.

Instructions

Rolling window statistics (mean/std/min/max/sum) for an indicator. Smooths noise, reveals trends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityYes
indicatorYes
windowNoWindow size in periods (2-100)
opNomean | std | min | max | sum
timeNo
Behavior3/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds minimal behavioral context beyond that, only mentioning 'smooths noise, reveals trends'. It does not disclose any additional behavioral traits or limitations such as handling of missing data or window boundary effects.

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 extremely concise, consisting of two sentences that front-load the key action and purpose. Every word contributes to understanding, with no fluff or repetition.

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?

For a tool with 5 parameters, no output schema, and simple functionality, the description covers the core purpose but lacks details about the time parameter, return format, and prerequisites (e.g., data alignment). Annotations fill some gaps, but overall completeness is moderate.

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?

The description mentions 'indicator' (mapping to the indicator parameter) and lists the supported operations (mean, std, min, max, sum) which aligns with the op parameter. However, with 40% schema coverage, the description does not explain the entity or time parameters, leaving them underspecified. The window parameter is partially covered by the schema's description and the tool's name.

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 that the tool computes rolling window statistics (mean/std/min/max/sum) for an indicator, and mentions noise smoothing and trend revelation. This effectively distinguishes it from siblings like lag_analysis or pct_change by specifying the rolling window operation.

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

Usage Guidelines3/5

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

The description implies usage for smoothing noise and revealing trends, which suggests time series analysis, but it does not explicitly state when to use this tool versus alternatives like lag_analysis or pct_change. No when-not-to-use guidance is provided.

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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