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 mentions the tool returns 'comprehensive documentation with examples, schema details, and best practices', which gives some insight into output behavior. However, it lacks details on error handling, authentication needs, or rate limits that would be important for a documentation retrieval tool.

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 appropriately sized with two clear sentences: one stating the purpose and output characteristics, and another providing parameter guidance. The Args section is well-structured but could be more integrated into the main description flow. Every sentence adds value without redundancy.

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?

For a single-parameter tool with no annotations and no output schema, the description provides adequate context about what the tool does and how to use it. However, it lacks information about the return format structure, potential error conditions, or any limitations of the documentation retrieval process that would help the agent use it effectively.

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 value beyond the input schema, which has 0% description coverage. It explains that the 'topic' parameter should be a documentation topic, provides guidance on how to discover valid values using 'list_dashboard_studio_topics()', and gives concrete examples like 'cheatsheet' and 'definition'. This compensates well 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 tool's purpose with specific verb ('Get') and resource ('Dashboard Studio documentation for a specific topic'), and distinguishes it from siblings like 'get_splunk_documentation' by specifying the documentation scope. It also mentions the comprehensive nature of the returned documentation.

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 explicitly provides when-to-use guidance by naming an alternative tool ('list_dashboard_studio_topics()') to discover available topics, and includes examples of valid topics. This helps the agent understand the prerequisite step before using this tool.

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