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power_spectrum

. Estimate the power spectral density of a signal using Welch's method. Input a signal and sample rate to analyze frequency content and reduce noise.

Instructions

Estimate the power spectral density with Welch's method.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
signalYes
npersegNo
sample_rateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing beyond the method name. It does not mention that Welch segments the signal and averages periodograms (which constrains nperseg), what is returned (frequency bins plus PSD values), or any assumptions about the input signal.

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?

A single front-loaded sentence with zero padding or repetition. It is efficiently written, though its brevity is a symptom of under-specification rather than disciplined concision.

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?

With no annotations, no output schema, and zero parameter documentation, the description leaves an agent missing the return values, the meaning of nperseg, and the signal input contract. For a three-parameter numerical tool this is materially incomplete.

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

Parameters1/5

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

Schema coverage is 0% for all three parameters, and the description offers no compensating detail. The non-obvious parameter 'nperseg' (segment length for Welch averaging) is left entirely unexplained, as are the accepted forms of 'signal' (array vs. string) and the units of 'sample_rate'.

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?

States a specific verb+resource ('Estimate the power spectral density') plus the algorithm ('Welch's method'), which is more precise than a generic 'spectrum' label. However, it does nothing to separate itself from adjacent spectral siblings such as fft_analysis or stft, so the agent gets no help choosing among 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?

There is no when-to-use guidance at all: nothing says when Welch's PSD estimate is preferable to fft_analysis or stft, nor whether a preprocessed/sampled signal is required. The agent must infer the selection criteria from domain knowledge alone.

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