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deslicer

MCP Server for Splunk

get_cim_reference

Retrieve detailed Splunk CIM data model documentation, including field specifications, mappings, and tagging requirements for implementation guidance.

Instructions

Get detailed Splunk CIM data model documentation with field specifications and configuration examples. Returns comprehensive reference including field mappings, tagging requirements, and implementation guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesCIM data model name. Use list_cim_data_models() to see all available models. Examples: 'authentication', 'network-traffic', 'malware'
versionNoCIM version (default: 'latest'). Options: '6.1', '6.0', '5.3', '5.2', '5.1', 'latest'latest
Behavior3/5

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

No annotations are provided, so the description bears full responsibility for behavioral transparency. It describes the return content (field mappings, tagging requirements, implementation guidance) but does not discuss side effects, performance, error states, or limitations. The version parameter suggests version-specific output, but the description does not clarify behavior across versions or the output format.

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 with two sentences: the first states the primary action and included elements, the second elaborates on the return content. No redundant or extraneous information, and it is well structured for quick understanding.

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?

The tool has two parameters, no output schema, and no annotations. The description covers the return content (field specs, examples, mappings, tagging, implementation guidance) but omits details like output format, prerequisites, or how to use the returned documentation. It is largely complete given the tool's simplicity, but could mention the textual nature of the output.

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

Parameters3/5

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

Schema coverage is 100%, with both parameters (model and version) having detailed descriptions in the schema. The description does not add any additional meaning beyond what the schema already provides about the parameters; it only describes the overall return content. Baseline score of 3 is appropriate as the schema carries the load.

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 it gets detailed Splunk CIM data model documentation with field specifications, configuration examples, field mappings, tagging requirements, and implementation guidance. The verb 'Get' and resource 'Splunk CIM data model documentation' are specific, and the tool is well-distinguished from siblings like list_cim_data_models (which lists available models) and get_spl_reference (for SPL commands).

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 does not explicitly state when to use this tool versus alternatives like get_spl_reference or other documentation tools. The input schema mentions using list_cim_data_models to see available models, but this guidance is not in the description itself. Usage is implied but lacks explicit context or exclusion criteria.

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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