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hmc_get_pcm_preferences

Read-only

Get Performance and Capacity Monitoring (PCM) preferences for a managed system or logical partition, returning flags such as LongTermMonitorEnabled and AggregationEnabled to show current monitoring configuration.

Instructions

Get PCM monitoring preferences for a resource.

category is the resource type, e.g. 'ManagedSystem' or 'LogicalPartition'; resource_name_or_uuid is the name or UUID of that resource (a SystemName or UUID from hmc_systems, or a PartitionName or UUID from hmc_lpars). Returns flags like LongTermMonitorEnabled, AggregationEnabled, ShortTermMonitorEnabled, ComputeLTMEnabled, EnergyMonitorEnabled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYes
resource_name_or_uuidYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

The readOnlyHint annotation already indicates a safe read operation. The description adds value by listing the return flags (e.g., LongTermMonitorEnabled, AggregationEnabled), which gives the agent expectations about the response beyond the annotation. It does not mention errors or permissions, but the annotation plus return-value summary are sufficient.

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 concise, front-loaded with the primary purpose, and every sentence adds value. It avoids redundant phrasing and uses line breaks for readability. The examples are useful without being verbose.

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

Completeness5/5

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

Given the tool's moderate complexity, the description covers the key elements: what it returns, how to specify the resource, and where to get valid identifiers. The presence of an output schema reduces the need to document exact return fields, so this is complete for an agent to select and invoke correctly.

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 compensates. It gives semantic meaning for both parameters: 'category' is the resource type with examples, and 'resource_name_or_uuid' is explained as a name or UUID, with instructions on where to obtain them (from hmc_systems or hmc_lpars).

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 opens with 'Get PCM monitoring preferences for a resource' – a specific verb and resource. It clearly distinguishes itself from sibling tools like hmc_set_pcm_preferences (the setter) and metrics tools by focusing on retrieving preferences.

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

Usage Guidelines4/5

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

It explains how to use the tool by defining both parameters with concrete examples ('ManagedSystem' or 'LogicalPartition') and referencing other tools (hmc_systems, hmc_lpars) for valid resource identifiers. It does not explicitly state when not to use it, but the context makes the intended use clear.

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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