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ajragusa

perfsonar-mcp

by ajragusa

get_test_status

Check the current status of a scheduled network performance test run in perfSONAR to monitor throughput, latency, or packet loss measurements.

Instructions

Get status of a pScheduler test run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runUrlYesRun URL from test scheduling

Implementation Reference

  • The primary implementation of the get_test_status tool using the fastmcp framework.
    async def get_test_status(runUrl: str) -> str:
        """Get status of a pScheduler test run.
    
        Args:
            runUrl: Run URL from test scheduling response
    
        Returns:
            JSON string with test status information
        """
        result = await pscheduler_client.get_run_status(runUrl)
        return json.dumps(result.model_dump(by_alias=True), indent=2)
  • Tool registration in the MCP server.
    Tool(
        name="get_test_status",
        description="Get status of a pScheduler test run.",
        inputSchema={
            "type": "object",
            "properties": {
                "runUrl": {
                    "type": "string",
                    "description": "Run URL from test scheduling",
                },
            },
  • Tool execution logic for get_test_status in the main MCP server handler.
    elif name == "get_test_status":
        result = await self.pscheduler_client.get_run_status(arguments["runUrl"])
        return CallToolResult(
            content=[
                TextContent(
                    type="text",
                    text=json.dumps(result.model_dump(by_alias=True), indent=2),
                )
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. It states the tool retrieves status but doesn't explain what 'status' entails (e.g., running, completed, failed), whether it's read-only or has side effects, or any constraints like rate limits or authentication needs, leaving key behavioral traits unspecified.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly.

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?

Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns status details. It doesn't explain what information the status includes (e.g., progress, errors) or how to interpret results, leaving gaps in understanding the tool's full context and output.

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?

The input schema has 100% description coverage, with 'runUrl' documented as 'Run URL from test scheduling'. The description adds no additional meaning beyond this, such as format examples or context about where to obtain the URL, so it meets the baseline for high schema coverage without enhancing parameter understanding.

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 action ('Get status') and resource ('pScheduler test run'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_test_result' or 'get_measurement_data', which might provide related information about test outcomes or data.

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, such as needing a scheduled test run, or clarify its role compared to siblings like 'get_test_result' or 'get_measurement_data', leaving usage context ambiguous.

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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