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 ('creates a complete transaction with nested spans'), its purpose ('verify that tracing is working'), and the optional error-triggering behavior. However, it does not mention side effects, permissions, or rate limits, leaving some behavioral aspects unspecified.

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 and front-loaded, with the first sentence stating the core purpose. Subsequent sentences efficiently explain the tool's behavior, parameters, and returns without redundancy. Every sentence adds value, and the bullet-point format for parameter details enhances readability.

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, no annotations, and the presence of an output schema (which handles return values), the description is complete. It covers purpose, behavior, parameter semantics, and expected outcomes, providing sufficient context for an agent to understand and invoke the tool correctly without over-explaining.

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 purpose of 'trigger_error' ('triggers a test exception to verify error tracking') and details the 'test_type' parameter with specific enum values and their effects ('full', 'trace', 'error', 'message'), 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 specific action ('Test Sentry integration by sending traces, spans, and optionally errors') and resource ('Sentry integration'), distinguishing it from sibling tools focused on Splunk operations. It provides a concrete verb ('test') with specific outcomes, making the purpose unambiguous.

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 implies usage context ('to verify that tracing is working correctly in your Sentry dashboard') but does not explicitly state when to use this tool versus alternatives or exclusions. It lacks direct comparison to sibling tools, though the purpose is distinct enough to infer appropriate usage scenarios.

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