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scoutapp

Scout Monitoring MCP

Official
by scoutapp

get_app_job_traces

Retrieve recent traces for a specific background job in an app, filtered by time range, to inspect job performance and diagnose bottlenecks.

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

NameRequiredDescriptionDefault
toYes
from_Yes
app_idYes
job_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.1

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the return shape (id, time, duration, name, queue, metric_name, context), which is genuine added information even though an output schema exists. It says nothing about whether the call is read-only, how many traces 'recent' returns, or whether results are paginated or truncated — material gaps for a list tool.

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 one-line purpose is front-loaded, the trace field list is compact, and the Args block maps directly onto the required parameters. Mild redundancy with the schema titles (app_id, to, from_) is acceptable because the description adds types and formats the schema lacks.

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?

An output schema exists, so the return-field list is arguably redundant and return values needn't be re-explained. The missing pieces are the ones that actually affect correct invocation: result count limits for 'recent', pagination, and how from_/to interact with that window.

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?

Schema coverage is 0%, so the description must compensate, and it largely does: it names all four parameters with types and formats (int app ID, Base64-encoded job ID, ISO 8601 from_/to). It does not explain timezone expectations or whether from_/to are inclusive, which prevents a full 5.

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?

States a specific verb and resource ('Get recent traces') plus a scoping qualifier ('filtered to a specific background job'), so the agent knows what it returns. It does not distinguish itself from the near-identical sibling get_app_trace (singular) or get_app_endpoint_traces, which is the one gap keeping this below a 5.

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?

There is no guidance on when to use this versus get_app_trace, get_app_endpoint_traces, or get_app_jobs, nor any prerequisites. The word 'recent' combined with required from_/to args is not reconciled, leaving the agent to infer whether the date window or the 'recent' cap governs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.