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markuskreitzer

PicoScope MCP Server

by markuskreitzer
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Python
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get_statistics

Analyze signal data from PicoScope oscilloscopes to calculate statistical metrics including minimum, maximum, mean, and standard deviation values.

Instructions

Get statistical analysis of signal.

Args: channel: Channel to analyze. num_samples: Number of samples to analyze.

Returns: Dictionary containing min, max, mean, std dev, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelYes
num_samplesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/picoscope_mcp/tools/analysis.py:159-173 (handler)
    The handler function for the 'get_statistics' MCP tool. Defined as a nested function within register_analysis_tools and decorated with @mcp.tool(). Includes parameter type hints serving as input schema and a stub implementation.
    @mcp.tool()
def get_statistics(
    channel: Literal["A", "B", "C", "D"], num_samples: int = 1000
) -> dict[str, Any]:
    """Get statistical analysis of signal.

    Args:
        channel: Channel to analyze.
        num_samples: Number of samples to analyze.

    Returns:
        Dictionary containing min, max, mean, std dev, etc.
    """
    # TODO: Implement statistics calculation
    return {"status": "not_implemented", "channel": channel, "num_samples": num_samples}
  • src/picoscope_mcp/server.py:18-18 (registration)
    The registration point where register_analysis_tools is called on the MCP server instance, thereby registering the 'get_statistics' tool along with other analysis tools.
    register_analysis_tools(mcp)
  • src/picoscope_mcp/server.py:8-8 (registration)
    Import of register_analysis_tools from analysis.py, prerequisite for registering the tools including 'get_statistics'.
    from .tools.analysis import register_analysis_tools

Tool Definition Quality

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden but lacks behavioral details. It doesn't mention whether this requires a connected device, if it's a read-only operation, what happens if invalid parameters are provided, or any rate limits. The mention of 'Returns' hints at output but doesn't fully describe behavior.

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 well-structured and front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence adds value with no wasted words, making it easy to scan and understand quickly.

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's moderate complexity (2 parameters, no annotations, output schema exists), the description is somewhat complete but has gaps. It covers purpose and parameters but lacks usage context and behavioral details. The output schema existence means return values don't need explanation, but other aspects like prerequisites are missing.

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

Parameters4/5

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 adds meaning by explaining 'channel' as 'Channel to analyze' and 'num_samples' as 'Number of samples to analyze', which clarifies their roles beyond the schema's enum and default values. However, it doesn't detail the enum options (A, B, C, D) or sample constraints.

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's purpose with a specific verb ('Get statistical analysis') and resource ('of signal'), distinguishing it from measurement-focused siblings like measure_amplitude or measure_frequency. However, it doesn't explicitly differentiate from compute_fft, which might also analyze signals but differently.

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 like compute_fft or the various measurement tools. The description only states what it does, not when it's appropriate or what prerequisites might be needed (e.g., device connection).

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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