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 adds valuable context beyond basic functionality: it specifies that HTTP headers are included with 'sensitive values masked' and mentions 'core context metadata,' which helps the agent understand privacy and output scope. However, it doesn't detail response format, error handling, or performance characteristics, leaving some behavioral aspects unclear.

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 highly concise and well-structured: two sentences that front-load the core purpose and follow with specific details. Every sentence adds value—the first states the action and intent, the second clarifies output content—with zero waste or redundancy, making it efficient for agent comprehension.

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 low complexity (0 parameters, no annotations) and the presence of an output schema, the description is largely complete. It covers the debugging purpose and output scope (headers and metadata), which suffices for basic understanding. However, it could slightly enhance completeness by hinting at the output structure or common use cases, though the output schema mitigates this gap.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on output semantics. This meets the baseline for tools with no parameters, as it avoids unnecessary details and aligns with schema completeness.

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: 'Return request headers and context details for debugging.' It specifies the verb ('return') and resource ('request headers and context details'), and distinguishes it from siblings by focusing on debugging metadata rather than configuration, data retrieval, or management operations. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_metadata'), keeping it at a 4.

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 ('for debugging') but doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_metadata' or other diagnostic tools. There's no mention of prerequisites, exclusions, or specific scenarios where this tool is preferred over siblings, leaving usage somewhat ambiguous.

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