Mikensey MCP Server

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

The annotations already indicate this is a read-only, non-destructive, idempotent operation with a closed world. The description adds context about the tool's purpose ('deep-dive into a specific conversation') and the need to find episode IDs first, which provides useful behavioral insight beyond the annotations. It doesn't contradict annotations, but could mention more about rate limits or error handling.

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 the core purpose, followed by usage guidelines and parameter details. Every sentence serves a clear purpose without redundancy, making it efficient and easy to parse for an AI agent.

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 annotations cover safety and idempotency, and the schema fully describes parameters, the description provides good context about usage and purpose. However, without an output schema, it could benefit from more detail on return values (e.g., format of 'metadata' mentioned). It's mostly complete but has a minor gap in output clarification.

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 fully documents all parameters. The description adds minimal value by listing parameters with brief examples (e.g., episode slug format) and default values, but doesn't provide significant additional semantics beyond what's in the schema. This meets the baseline 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 specific action ('Read the full or partial transcript') and resource ('of a specific podcast episode'), distinguishing it from siblings like mikensey_list_episodes (which lists episodes) or mikensey_search (which searches content). It explicitly mentions what the tool does beyond just the title.

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 ('Use this to deep-dive into a specific conversation') and when not to use it ('Use mikensey_list_episodes or mikensey_search first to find the episode id'), naming specific alternatives. This helps the agent understand the proper workflow and tool selection.

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