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perfsonar-mcp

by ajragusa

schedule_throughput_test

Schedule network throughput tests between hosts to measure data transfer capacity using pScheduler. Configure source, destination, and duration parameters for performance analysis.

Instructions

Schedule a throughput test using pScheduler.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoSource host (optional)
destYesDestination host
durationNoTest duration (e.g., PT30S)

Implementation Reference

  • FastMCP tool definition for schedule_throughput_test, which calls the underlying pScheduler client.
    async def schedule_throughput_test(
        dest: str,
        source: Optional[str] = None,
        duration: str = "PT30S",
        slip: str = "PT10M",
    ) -> str:
        """Schedule a throughput test using pScheduler.
    
        Args:
            dest: Destination host for the test
            source: Optional source host (if not specified, uses pScheduler host)
            duration: Test duration in ISO 8601 format (e.g., 'PT30S' for 30 seconds)
            slip: Schedule slip time in ISO 8601 format (e.g., 'PT10M' for 10 minutes)
    
        Returns:
            JSON string with test details including run URL for status checks
        """
        result = await pscheduler_client.schedule_throughput_test(source, dest, duration, slip)
        return json.dumps(result.model_dump(), indent=2)
  • Actual implementation of the throughput test scheduling logic in the pScheduler client.
    async def schedule_throughput_test(
        self,
        source: Optional[str],
        dest: str,
        duration: str = "PT30S",
        slip: str = "PT10M",
    ) -> PSchedulerTaskResponse:
        """
        Schedule a throughput test
    
        Args:
            source: Source host (None for local)
            dest: Destination host
            duration: Test duration in ISO 8601 format (e.g., PT30S for 30 seconds)
            slip: Schedule slip time in ISO 8601 format (e.g., PT10M for 10 minutes)
    
        Returns:
            Task response
        """
        logger.info(
            f"Scheduling throughput test from {source or 'local'} to {dest} with duration {duration}"
        )
    
        # Determine which node to schedule on (prefer source if available)
        scheduler_node = source or dest
        scheduler_url = f"https://{scheduler_node}/pscheduler"
        logger.info(f"Using pScheduler at: {scheduler_url}")
    
        test_spec = ThroughputTestSpec(source=source, dest=dest, duration=duration)
    
        task_request = PSchedulerTaskRequest(
            test=PSchedulerTestSpec(
                type="throughput", spec=test_spec.model_dump(exclude_none=True)
            ),
            schedule={"slip": slip},
        )
    
        # Create a temporary client for this specific scheduler
        client = PSchedulerClient(scheduler_url)
        try:
            return await client.create_task(task_request)
        finally:
            await client.close()
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 schedules a test, implying it's a write/mutation operation, but doesn't cover permissions, side effects, rate limits, or what happens after scheduling (e.g., how results are accessed). This is inadequate for a tool that likely initiates network tests.

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 with no wasted words. It front-loads the key action and tool context, 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 complexity of scheduling network tests, lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., a test ID), how to check status/results, or error handling. For a mutation tool with siblings, more context is needed.

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 100%, so the schema fully documents parameters. The description adds no additional meaning beyond what's in the schema (e.g., no examples of typical values or constraints). Baseline 3 is appropriate since the schema handles parameter documentation.

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 ('Schedule a throughput test') and specifies the tool used ('using pScheduler'), which distinguishes it from general scheduling tools. However, it doesn't explicitly differentiate from sibling tools like 'schedule_latency_test' or 'schedule_rtt_test' beyond the 'throughput' keyword in the name.

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 'get_throughput' (which likely retrieves results) or other scheduling siblings. The description lacks context about prerequisites, timing, or when this tool is appropriate compared to direct measurement tools.

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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