Insight Digger MCP

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 key traits: authentication requirements ('🔒 [Requires Authentication]'), caching behavior ('🔄 Auto-Cached'), and workflow integration ('granular step in the analysis workflow'). It doesn't mention rate limits, error handling, or response format, but covers essential operational aspects.

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 key information: authentication requirement, purpose, and caching behavior. Every sentence adds value—no wasted words. The use of emojis and formatting (bold, warnings) enhances readability without sacrificing conciseness.

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 complexity (3 parameters, nested objects, no output schema, no annotations), the description does a good job covering authentication, workflow role, and parameter sourcing. However, it lacks details on what the tool returns or how errors are handled. For a creation tool with no output schema, explaining the result would improve completeness.

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 mentions the three parameters ('question', 'columnAnalysis', 'strategy') and states they're 'automatically provided from previous steps' and 'typically don't need to be provided.' This adds context about parameter sourcing but doesn't explain what each parameter represents or their expected formats, leaving significant gaps.

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: 'Create dashboard configuration from question, column analysis, and strategy.' It specifies the verb ('create') and resource ('dashboard configuration'), and distinguishes it from siblings like 'create_dashboard' by focusing on configuration rather than the dashboard itself. However, it doesn't explicitly differentiate from 'generate_config', which might be similar.

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 provides explicit guidance on when to use this tool: 'This is a granular step in the analysis workflow' and 'You typically don't need to provide any parameters for this tool.' It also specifies prerequisites: 'Please authenticate first by calling the `setup_authentication` tool above.' This clearly defines the context and exclusions.

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