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get_service_details

Retrieve detailed status and configuration information for a specific service in an Ambari cluster to monitor health, troubleshoot issues, and audit setup.

Instructions

Retrieves detailed status and configuration information for a specific service in the Ambari cluster.

[Tool Role]: Dedicated tool for retrieving comprehensive service details, including state, components, and configuration.

[Core Functions]:

  • Retrieve service state, component list, and configuration availability

  • Provide formatted output for LLM automation and troubleshooting

[Required Usage Scenarios]:

  • When users request detailed service info or breakdown

  • When troubleshooting service health or auditing service setup

  • When users mention service details, service summary, or configuration status

Args: service_name: Name of the service to check (e.g., "HDFS", "YARN", "HBASE")

Returns: Detailed service information (success: comprehensive details, failure: English error message)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
service_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses that the tool provides 'formatted output for LLM automation and troubleshooting' and specifies return behavior: 'success: comprehensive details, failure: English error message'. However, it doesn't mention rate limits, authentication needs, or whether this is a read-only operation (though implied by 'retrieves').

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized but has some structural issues. The core purpose is clear upfront, but the section headers ([Tool Role], [Core Functions], etc.) create redundancy. Sentences like 'Provide formatted output for LLM automation and troubleshooting' earn their place, but the structure could be more streamlined.

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?

Given 1 parameter with 0% schema coverage but an output schema exists, the description provides good context. It explains the parameter, gives usage scenarios, and describes return behavior. However, it doesn't mention what 'comprehensive details' includes or potential side effects, leaving some gaps despite the output schema.

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?

With 0% schema description coverage and 1 parameter, the description compensates well by explaining the service_name parameter with examples ('HDFS', 'YARN', 'HBASE') and clarifying it's 'Name of the service to check'. This adds meaningful context beyond the bare schema.

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 the tool's purpose with specific verb ('retrieves') and resource ('detailed status and configuration information for a specific service in the Ambari cluster'). It distinguishes from siblings like get_service_status (likely simpler status) and get_service_components (focused on components only) by emphasizing comprehensive details including state, components, and configuration.

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

Usage Guidelines5/5

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

The description provides explicit usage scenarios in a dedicated section: 'When users request detailed service info or breakdown', 'When troubleshooting service health or auditing service setup', and 'When users mention service details, service summary, or configuration status'. This gives clear context for when to use this tool versus alternatives.

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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