Mikensey MCP Server

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, indicating it's a safe, read-only, idempotent operation with a closed world. The description adds valuable context beyond this: it explains what types of frameworks are available (Industry vs. Consulting with examples), clarifies the return format (name, description, when to use, examples), and mentions filtering capabilities. No contradiction with annotations exists.

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 bullet points for framework categories, a clear Args section, and a Returns statement. Every sentence adds value: it explains the two framework types with examples, documents parameters, specifies return format, and provides usage guidance. No wasted words.

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 (browsing frameworks with filtering), rich annotations (covering safety and behavior), and 100% schema coverage, the description is complete. It explains what the tool does, when to use it, what it returns, and how it differs from siblings. No output schema exists, but the description adequately describes return values.

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%, with both parameters having clear enum values and descriptions. The description adds some semantic context by explaining that 'audience' filters industry frameworks by target audience and 'type' filters by framework category, but this largely repeats what's in the schema. Baseline 3 is appropriate as the schema does most of the work.

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: to browse two specific categories of frameworks (Industry Frameworks and Consulting Frameworks) available in Mikensey. It distinguishes this from sibling tools by specifying it's for browsing frameworks, not applying them (mikensey_analyze) or getting other content like advice, benchmarks, or episodes.

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 states when to use this tool vs. alternatives: 'To actually APPLY a consulting framework to your specific situation, use mikensey_analyze.' This provides clear guidance on when to use this tool (for browsing frameworks) versus when to use a sibling tool (for applying frameworks).

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