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markuskreitzer

PicoScope MCP Server

by markuskreitzer
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Python
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compute_fft

Perform Fast Fourier Transform analysis on PicoScope oscilloscope signals to convert time-domain waveforms into frequency-domain spectra for identifying signal components.

Instructions

Compute FFT (Fast Fourier Transform) for frequency domain analysis.

Args: channel: Channel to analyze. window: Window function to apply.

Returns: Dictionary containing frequency bins and magnitude spectrum.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelYes
windowNohann

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/picoscope_mcp/tools/analysis.py:142-157 (handler)
    The main handler function for the 'compute_fft' tool. Includes inline schema via type hints for parameters 'channel' and 'window', and the execution logic (currently a stub). Decorated with @mcp.tool() for registration.
    @mcp.tool()
def compute_fft(
    channel: Literal["A", "B", "C", "D"],
    window: Literal["hann", "hamming", "blackman", "rectangular"] = "hann",
) -> dict[str, Any]:
    """Compute FFT (Fast Fourier Transform) for frequency domain analysis.

    Args:
        channel: Channel to analyze.
        window: Window function to apply.

    Returns:
        Dictionary containing frequency bins and magnitude spectrum.
    """
    # TODO: Implement FFT computation
    return {"status": "not_implemented", "channel": channel, "window": window}
  • src/picoscope_mcp/server.py:18-18 (registration)
    The registration point where register_analysis_tools is called on the MCP instance, which in turn registers the compute_fft tool.
    register_analysis_tools(mcp)
  • src/picoscope_mcp/tools/analysis.py:9-9 (registration)
    The registration function that defines and registers multiple analysis tools, including compute_fft, using @mcp.tool() decorators.
    def register_analysis_tools(mcp: Any) -> None:

Tool Definition Quality

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral context. It mentions the tool returns a dictionary with frequency bins and magnitude spectrum, but doesn't disclose computational requirements, data size limitations, whether it processes real-time or stored data, or any performance characteristics.

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 efficiently structured with a brief purpose statement followed by Args and Returns sections. However, the 'Compute FFT (Fast Fourier Transform) for frequency domain analysis' sentence could be more specific about what data is being transformed.

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?

Given the tool has an output schema (though not shown here), the description doesn't need to fully document return values. However, for a computational tool with no annotations and 0% schema description coverage, it should provide more context about data requirements, transformation specifics, and typical use cases to be complete.

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?

Schema description coverage is 0%, but both parameters have enums that define valid values. The description adds minimal semantics by naming the parameters (channel, window) and stating their purpose ('Channel to analyze', 'Window function to apply'), but doesn't explain what the channel represents or how the window affects the analysis.

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 tool computes FFT for frequency domain analysis, which is a specific verb (compute) and resource (FFT). However, it doesn't differentiate from sibling tools like measure_frequency or measure_thd, which might also perform frequency-related analyses.

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 use this tool versus alternatives. The description doesn't mention prerequisites like needing connected devices or configured channels, nor does it explain how this differs from other frequency measurement tools in the sibling list.

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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