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scoutapp

Scout Monitoring MCP

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get_app_job_traces

Get recent traces for a specific background job in your app. Filter by job ID and time range to identify performance issues.

Instructions

Get recent traces for an app filtered to a specific background job.

Each trace includes: id, time, duration, name, queue, metric_name, context.

Args:
    app_id (int): The ID of the Scout APM application.
    job_id (str): The Base64-encoded job ID.
    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
from_Yes
toYes
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description must disclose behavioral traits. It states traces are 'recent' and filtered to a job, but does not clarify recency bounds, pagination, response limits, or error states. Listing trace fields adds some value but edges are missing.

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 well-structured with a purpose sentence, trace field list, and parameter docs. It is front-loaded and efficient, though the 'Each trace includes' line could be integrated with output schema info.

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 4 required parameters, no annotations, and an output schema, the description provides adequate parameter semantics but misses overall context like usage scenarios, pagination, or error handling. It is sufficient but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully documents each parameter: app_id ('ID of the Scout APM application'), job_id ('Base64-encoded job ID'), from_ and to (ISO 8601 datetime). This adds meaning beyond schema names.

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 recent traces for an app filtered to a specific background job,' specifying the verb (get), resource (traces), and scope (app and job). This distinguishes it from siblings like get_app_trace (single trace) and get_app_jobs (list jobs).

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 lacks guidance on when to use this tool versus alternatives. No mention of prerequisites, fallbacks, or context like 'use for debugging job performance' or 'for a single trace use get_app_trace instead.'

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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