MCP Server for Splunk

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the return content ('comprehensive reference including field mappings, tagging requirements, and implementation guidance'), which adds value beyond basic function. However, it lacks details on potential errors, rate limits, or authentication requirements, leaving gaps in behavioral context.

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

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

The description is appropriately sized and front-loaded, starting with the core purpose in the first sentence. The 'Args' section is well-structured with bullet-like formatting for parameters, and every sentence adds necessary information without waste, making it efficient and easy to parse.

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

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, usage guidance, and parameter details effectively. However, without an output schema, it could benefit from more specifics on the return format (e.g., structure of the 'comprehensive reference'), leaving a minor gap in completeness.

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

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

The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains the 'model' parameter with examples ('authentication', 'network-traffic', 'malware') and usage guidance ('Use list_cim_data_models() to see all available models'). For the 'version' parameter, it lists options ('6.1', '6.0', etc.) and specifies the default ('latest'), fully compensating for the schema's lack of documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 verbs ('Get detailed Splunk CIM data model documentation') and resources ('field specifications and configuration examples'). It distinguishes itself from sibling tools like 'list_cim_data_models' (which lists models) by focusing on detailed documentation retrieval, not just listing.

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

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

The description provides clear context for usage by mentioning that 'list_cim_data_models()' should be used to see available models, which helps guide parameter selection. However, it does not explicitly state when to use this tool versus alternatives like 'get_splunk_documentation' or 'discover_splunk_docs', leaving some ambiguity in sibling differentiation.

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