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deslicer

MCP Server for Splunk

user_agent_info

Debug applications by retrieving HTTP request headers and context metadata, with sensitive values automatically masked.

Instructions

Return request headers and context details for debugging.

Includes all HTTP headers (with sensitive values masked) and core context metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that sensitive values are masked, which is a key behavioral trait. It also mentions that it includes headers and core context metadata. However, it does not elaborate on what 'core context metadata' includes or any potential side effects, though for a read-only debug tool, this is largely sufficient.

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 two sentences, front-loading the purpose. Every sentence adds value: the first states the core function, the second provides specific details about what is included (headers masked, context metadata). No wasted words.

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

Completeness5/5

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

Given the tool has no parameters and an output schema exists, the description sufficiently explains the return contents. It covers both the type of data (headers and context) and a key behavior (masking sensitive values). The low complexity of a parameterless debug tool means the description is complete.

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

Parameters4/5

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

The tool has no parameters, so schema description coverage is 100% trivially. The description adds value by explaining what the tool returns, which compensates for the lack of parameter info. With zero parameters, the baseline is 4, and the description meets it.

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 returns request headers and context details for debugging. It identifies a specific verb ('Return') and resource ('request headers and context details'). Among sibling tools like get_configurations, get_metadata, etc., this tool is distinctively about debugging request info.

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 implies usage for debugging but does not explicitly state when to use this tool versus alternatives or when not to use it. No alternative tools are mentioned. The sibling tools are quite different, so the usage context is implicit but not explicit.

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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