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markuskreitzer

PicoScope MCP Server

set_signal_generator

Configure the built-in signal generator to produce waveforms with specified type, frequency, amplitude, and offset for testing and measurement applications.

Instructions

Configure the built-in signal generator (AWG).

Args: waveform_type: Type of waveform to generate. frequency_hz: Frequency in Hz. amplitude_mv: Peak-to-peak amplitude in millivolts. offset_mv: DC offset in millivolts.

Returns: Dictionary containing signal generator status and configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waveform_typeNosine
frequency_hzNo
amplitude_mvNo
offset_mvNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'set_signal_generator' tool, including decorator, parameters (schema), docstring, and logic (currently a TODO placeholder).
    @mcp.tool()
    def set_signal_generator(
        waveform_type: Literal["sine", "square", "triangle", "dc", "ramp"] = "sine",
        frequency_hz: float = 1000.0,
        amplitude_mv: float = 1000.0,
        offset_mv: float = 0.0,
    ) -> dict[str, Any]:
        """Configure the built-in signal generator (AWG).
    
        Args:
            waveform_type: Type of waveform to generate.
            frequency_hz: Frequency in Hz.
            amplitude_mv: Peak-to-peak amplitude in millivolts.
            offset_mv: DC offset in millivolts.
    
        Returns:
            Dictionary containing signal generator status and configuration.
        """
        # TODO: Implement signal generator control
        return {
            "status": "not_implemented",
            "waveform": waveform_type,
            "frequency_hz": frequency_hz,
            "amplitude_mv": amplitude_mv,
            "offset_mv": offset_mv,
        }
  • Registration call that invokes the definition and registration of advanced tools, including set_signal_generator.
    register_advanced_tools(mcp)
  • Import of the register_advanced_tools function used to register the tool.
    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 the full burden of behavioral disclosure. While 'Configure' implies a write operation, the description doesn't mention whether this requires specific device states, what happens to existing configurations, whether changes are immediate or require additional steps, or any error conditions. The return statement mentions a status dictionary but doesn't explain what it contains or how to interpret it.

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 efficiently structured with a clear purpose statement followed by well-organized parameter and return sections. Every sentence adds value without redundancy. The Args/Returns formatting helps readability while maintaining brevity.

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 complexity of configuring a signal generator with 4 parameters and no annotations, the description is minimally adequate. It explains what parameters do but lacks behavioral context about device state requirements, error conditions, or practical usage patterns. The presence of an output schema means the description doesn't need to detail return values, but it should provide more operational guidance for this write operation.

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?

The description provides clear semantic explanations for all four parameters beyond what the schema offers. The schema has 0% description coverage (only technical types and defaults), but the description adds meaningful context: 'waveform_type: Type of waveform to generate', 'frequency_hz: Frequency in Hz', etc. This compensates well for the schema's lack of descriptions, though it doesn't explain parameter interactions or 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 verb ('Configure') and resource ('built-in signal generator (AWG)'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'stop_signal_generator' or explain how this configuration differs from other configuration tools like 'configure_channel' or 'set_timebase'.

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. There's no mention of prerequisites (e.g., device connection), when this should be used instead of other configuration tools, or what happens if the signal generator is already running. The sibling tool list includes related tools like 'stop_signal_generator', but the description doesn't reference them.

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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