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 and does well: it discloses authentication requirements ('🔒 **[Requires Authentication]**'), caching behavior ('🔄 Auto-Cached'), and that it returns a 'dict (markdown configuration).' It doesn't mention rate limits, error handling, or side effects, but covers key behavioral aspects for a tool with no annotations.

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 front-loaded with key information (authentication, purpose) but includes some redundancy (e.g., repeating authentication instructions) and could be more streamlined. Sentences like 'Returns: dict (markdown configuration).' are brief, but overall it's moderately efficient with room for improvement in structure.

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 (2 parameters, nested objects, no output schema, no annotations), the description is fairly complete: it covers purpose, prerequisites (authentication), parameter context, and return type. It lacks details on error cases or exact output structure, but for a tool with no annotations or output schema, it provides sufficient context for basic use.

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 explains that 'sourceStructure' is 'automatically provided from analyze_source_structure step' and that 'Only provide the 'question' parameter from the user,' adding context about parameter origins and usage. However, it doesn't detail the structure or format of 'sourceStructure' or what 'question' should contain, leaving gaps in parameter understanding.

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: 'Generate dashboard config (markdown) from question and source structure.' It specifies the verb ('generate'), resource ('dashboard config'), and output format ('markdown'), though it doesn't explicitly differentiate from siblings like 'create_configuration' or 'create_dashboard'.

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 usage guidance: it states '⚠️ **Please authenticate first** by calling the `setup_authentication` tool above' and mentions that 'sourceStructure' is auto-cached from 'analyze_source_structure' step, while 'apiUrl' and 'jwtToken' come from authentication. It also specifies 'Only provide the 'question' parameter from the user,' clarifying what inputs are needed versus automated.

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