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scoutapp

Scout Monitoring MCP

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get_job_metrics

Retrieve a specific timeseries metric for a background job in your Scout APM application. Choose from throughput, execution time, latency, errors, or allocations.

Instructions

Get a single timeseries metric for a specific background job in an application.

Valid job metrics: throughput, execution_time, latency, errors, allocations.

Args:
    app_id (int): The ID of the Scout APM application.
    job_id (str): The Base64-encoded job ID.
    metric (str): The metric to retrieve (e.g., "execution_time", "throughput").
    from_ (str): The start datetime in ISO 8601 format.
    to (str): The end datetime in ISO 8601 format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_idYes
job_idYes
metricYes
from_Yes
toYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations provided, so the description must disclose behaviors. It only states it retrieves a single timeseries metric but does not mention authorization needs, rate limits, error handling, or what happens if the job is missing. The return format is also not described despite an output schema existing.

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 concise with a clear first sentence and a brief list of valid metrics. The Args block is slightly verbose but acceptable given the lack of schema descriptions. No unnecessary sentences.

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?

With 5 required parameters and an output schema, the description covers the purpose and parameters adequately. However, it omits details about the output format (e.g., data points or single value) and error scenarios, leaving gaps for a data-retrieval tool.

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 coverage is 0%, so the description adds value by listing and describing each parameter (app_id, job_id, metric, from_, to) and providing valid metric values. However, from_ and to lack format details beyond 'ISO 8601'. Overall, it compensates partially for the missing schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get a single timeseries metric for a specific background job', specifying the verb and resource. It lists valid metrics, distinguishing it from sibling tools like get_app_jobs (list jobs) and get_app_job_traces (traces).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (when a specific job's metric is needed) but lacks explicit when-not-to-use or alternatives. No mention of when to choose this over get_app_metrics or other siblings.

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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