Mikensey MCP Server

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe, non-destructive operation. The description adds valuable behavioral context beyond annotations: it explains the tool's signature approach ('THINKS like a consultant'), lists available frameworks with brief explanations, and describes the return format ('structured strategic analysis... with real industry benchmarks, quotes from leaders, and specific recommendations'). This compensates for the lack of an output schema.

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 and front-loaded, starting with the core purpose. Most sentences earn their place by explaining the tool's unique value, listing frameworks, and detailing returns. However, the bullet-point list of frameworks is slightly verbose, and the final sentence on returns could be more concise, preventing a perfect score of 5.

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 tool's complexity (applies frameworks to business problems) and the absence of an output schema, the description does a good job of explaining what the tool returns. However, it could be more complete by mentioning potential limitations (e.g., data recency, scope of industry benchmarks) or error cases, which would help the agent use it more effectively in varied contexts.

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 100%, so the schema already documents all parameters well. The description adds some semantic value by listing and briefly explaining the available frameworks and noting that custom_axes is 'For 2×2 only,' but it doesn't provide significant additional meaning beyond what's in the schema (e.g., no examples for situation or role). This meets the baseline of 3 for high schema coverage.

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: 'Apply a McKinsey-style consulting framework to a business problem using real estate industry data.' It specifies the verb ('apply'), resource ('framework'), and domain ('real estate industry data'), and distinguishes it from siblings by emphasizing it 'doesn't just search transcripts — it THINKS like a consultant,' contrasting with tools like mikensey_search or mikensey_get_frameworks.

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 clear context for when to use this tool: for strategic analysis of business problems in real estate using consulting frameworks. It implicitly suggests alternatives by mentioning it doesn't just search transcripts, but it doesn't explicitly name when to use sibling tools like mikensey_get_advice or mikensey_get_benchmarks instead, which would be needed for a score of 5.

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