MCP Server for Splunk

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

With no annotations provided, the description carries full burden. It discloses behavioral traits: parallel execution with dependency management, real-time progress tracking, detailed results with performance metrics, and integration with existing infrastructure. It mentions 'optimal performance' but lacks specifics on rate limits, authentication needs, or error handling. However, it provides substantial context beyond basic functionality.

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 sections (Core Capabilities, Key Parameters, Supported Workflows, Benefits, When to use, Arguments, Outputs) but is overly verbose. Sentences like 'Perfect for executing specific workflows...' are redundant after the 'When to use' section. It could be more front-loaded; the first sentence captures the essence, but subsequent sections add bulk without always earning their place.

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 complexity (9 parameters, no annotations, no output schema), the description is largely complete. It explains purpose, usage, parameters, supported workflows, and outputs (detailed execution results with timing). However, without an output schema, it could better detail the structure of 'detailed execution results' (e.g., format, keys). It compensates well for missing structured data but has minor gaps in output specifics.

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?

Schema description coverage is 0%, so the description must compensate. It includes a 'Key Parameters' section explaining all 9 parameters with semantics: workflow_id (required, use list_workflows to discover), problem_description (context for investigation), time ranges (for diagnostic searches), focus parameters (for targeted analysis), complexity_level (analysis depth options), and enable_summarization (AI-powered summarization). It adds meaning beyond the bare schema, though some details like format examples could be enhanced.

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: 'Execute any available workflow by ID with comprehensive parameter control and parallel execution.' It specifies the verb ('execute'), resource ('workflow by ID'), and distinguishes from siblings like 'list_workflows' (for discovery) and 'workflow_builder' (likely for creation). The opening sentence is specific and comprehensive.

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 includes an explicit 'When to use' section with three bullet points: use when you know the workflow ID (discover via list_workflows), use for executing core/contrib workflows with custom parameters, and use in automation pipelines. It clearly distinguishes from sibling tools by referencing list_workflows for discovery and provides context for when this tool is appropriate.

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