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Get Task Metrics

get_task_metrics
Read-onlyIdempotent

Retrieve comprehensive task-level execution metrics across all workflows to gain insights into performance, application usage, and statistics for automation monitoring and optimization.

Instructions

Get all aggregate task metrics from the Workflow Engine.

Retrieves comprehensive task-level execution metrics across all workflows, providing detailed insights into task performance, application usage patterns, and execution statistics for automation monitoring and optimization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesResponse model for task metrics collection endpoints. This Pydantic RootModel provides a standardized response format for API endpoints that return collections of task-level metrics from the Itential Platform workflow engine. It wraps a list of TaskMetricElement objects, enabling type-safe handling of task performance data across automation workflows. The root model pattern allows the response to be treated as a list while maintaining proper validation and serialization capabilities for the contained task metric elements, supporting comprehensive workflow monitoring and analysis. Args: root: List of TaskMetricElement objects containing task performance data. Defaults to an empty list if not provided. Attributes: root (List[TaskMetricElement]): Collection of task metric elements with application usage patterns and execution statistics for workflow analysis Example: Creating a response with multiple task metrics: >>> task1 = TaskMetricElement(taskType="automatic", name="validate-config", ... metrics=[], app="validator") >>> task2 = TaskMetricElement(taskType="manual", name="approve-deploy", ... metrics=[], app="approval-service") >>> response = GetTaskMetricsResponse([task1, task2]) >>> print(len(response.root)) # 2 >>> print(response.root[0].task_type) # "automatic" >>> print(response.root[1].name) # "approve-deploy" Notes: - Uses default_factory=list to create empty collections when needed - Supports iteration and indexing through the root attribute - Maintains type safety for all contained TaskMetricElement objects - Enables filtering and analysis of tasks by application, workflow, or type
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds context about what the metrics contain (task performance, application usage patterns, execution statistics), which goes beyond the annotations. It does not contradict annotations.

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?

Two sentences with front-loaded purpose. The second sentence is somewhat verbose ('comprehensive', 'detailed insights', 'automation monitoring and optimization') but generally efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only tool with an output schema, the description provides adequate context about the data source and content. However, it could more explicitly distinguish itself from the scoped siblings.

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?

The tool has zero parameters, so the schema is fully covered. The description adds no parameter-specific info, but none is needed; per rubric, 0 params = baseline 4.

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 uses a specific verb ('Get') with a clear resource ('aggregate task metrics from the Workflow Engine') and scope ('across all workflows'). This differentiates it from sibling tools like get_task_metrics_for_app and get_task_metrics_for_workflow, which are scoped.

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 global scope ('across all workflows') but does not explicitly state when to use this tool versus the scoped siblings. It lacks direct 'use X instead' guidance, so usage is only implied.

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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