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markuskreitzer

PicoScope MCP Server

export_waveform

Export captured waveform data from PicoScope oscilloscopes to CSV, JSON, or NumPy files for analysis and sharing.

Instructions

Export captured waveform data to file.

Args: format: Export format (csv, json, or numpy). channels: List of channels to export. filename: Output filename (without extension).

Returns: Dictionary containing export status and file path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNocsv
channelsNo
filenameNowaveform

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function for the 'export_waveform' tool. It defines the input parameters (serving as schema via type hints), docstring, and placeholder logic for exporting waveform data.
    def export_waveform(
        format: Literal["csv", "json", "numpy"] = "csv",
        channels: list[str] = ["A"],
        filename: str = "waveform",
    ) -> dict[str, Any]:
        """Export captured waveform data to file.
    
        Args:
            format: Export format (csv, json, or numpy).
            channels: List of channels to export.
            filename: Output filename (without extension).
    
        Returns:
            Dictionary containing export status and file path.
        """
        # TODO: Implement waveform export
        return {
            "status": "not_implemented",
            "format": format,
            "channels": channels,
            "filename": filename,
        }
  • Registers the advanced tools module, which includes the 'export_waveform' tool, on the MCP server instance.
    register_advanced_tools(mcp)
  • Imports the registration function for advanced tools, which defines and registers 'export_waveform'.
    from .tools.advanced import register_advanced_tools
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is an export operation (implying data output) but doesn't describe what happens to the original waveform data (preserved or consumed?), whether file creation requires specific permissions, or any rate limits/constraints. The return value format is mentioned but lacks detail on error conditions or response structure beyond the basic dictionary description.

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 clear purpose statement followed by organized sections for arguments and returns. Every sentence serves a functional purpose. While slightly longer than minimal, the structure enhances readability without unnecessary verbosity. The information is front-loaded with the core function stated first.

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 3 parameters with 0% schema coverage and no annotations, the description provides basic but incomplete context. The presence of an output schema means the description doesn't need to detail return values, but it should better address behavioral aspects and usage prerequisites. For a data export tool in an instrumentation context, more guidance about data availability and file system interactions would be valuable.

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%, so the description must compensate. It provides basic semantic meaning for all three parameters: 'format' specifies export options, 'channels' indicates which data channels to include, and 'filename' defines the output name. However, it doesn't explain channel naming conventions, file location defaults, or format-specific behaviors. The description adds value beyond the bare schema but leaves important practical details unspecified.

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 verb 'Export' and the resource 'captured waveform data to file', making the purpose immediately understandable. It distinguishes itself from siblings like 'capture_block' or 'get_streaming_data' by focusing on data export rather than acquisition or analysis. However, it doesn't explicitly differentiate from potential data export alternatives that might exist in the broader context.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether waveform data must be captured first using 'capture_block'), nor does it suggest when other export formats or methods might be preferable. The agent receives no contextual usage instructions beyond the basic function.

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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