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 effectively describes what the tool does (enumerates data sources) and the response format, including status and data structure. However, it lacks details on potential side effects, rate limits, authentication requirements, or error handling, which are important for a tool interacting with a Splunk instance.

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 well-structured with clear sections for purpose, use cases, and response format, making it easy to scan. It is appropriately sized for the tool's complexity, though it could be slightly more concise by integrating the use cases into the main description rather than as a separate list.

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 has no input parameters, no annotations, and no output schema, the description provides sufficient context by explaining the tool's purpose, use cases, and response format. It covers the essential aspects needed for an AI agent to understand and invoke the tool correctly, though adding more behavioral details (e.g., performance or error handling) could enhance 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 tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description appropriately does not discuss parameters, focusing instead on functionality and output. This meets the baseline for tools with no parameters, as it avoids unnecessary detail.

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 explicitly states the tool's purpose: 'Discover and enumerate all available data sources from the configured Splunk instance using the metadata command.' It specifies the verb ('discover and enumerate'), resource ('data sources'), and method ('metadata command'), clearly distinguishing it from siblings like list_indexes or list_sourcetypes by focusing on data source origins rather than indexes or sourcetypes.

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 when to use this tool through a 'Use Cases' section, listing scenarios like data discovery, troubleshooting missing sources, and security analysis. However, it does not explicitly state when not to use it or name specific alternatives among siblings, such as get_metadata or list_sourcetypes, which might overlap in functionality.

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