Thinkific MCP Server

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

No annotations are provided, so the description carries the full burden. It mentions the tool retrieves metrics for monitoring and optimization, but lacks details on behavioral traits such as required permissions, rate limits, data freshness, or potential side effects (e.g., the 'reset' parameter's impact). This is a significant gap for a tool with potential performance implications.

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 with two sentences: the first states the purpose, and the second provides usage context. It's front-loaded with key information and avoids unnecessary details, though it could be slightly more structured (e.g., separating purpose from guidelines).

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 moderate complexity (performance metrics with a reset option), no annotations, and no output schema, the description is incomplete. It covers the basic purpose but lacks details on behavioral traits, output format, or error handling, which are crucial for effective use by an AI agent in a monitoring context.

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 the single parameter ('reset') with its type and default. The description adds no additional parameter semantics beyond what the schema provides, such as explaining the implications of resetting metrics or typical usage patterns. Baseline 3 is appropriate when the schema handles documentation.

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 with specific verbs ('Get performance metrics and statistics') and resources ('API calls, cache hit rates, and tool execution times'). It distinguishes itself from sibling tools by focusing on monitoring and optimization rather than CRUD operations on business entities like users or courses, though it doesn't explicitly name alternatives.

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 implies usage context ('Use this to monitor and optimize MCP server performance'), providing a general purpose. However, it doesn't specify when to use this tool versus alternatives (e.g., other monitoring tools or logs) or any prerequisites, leaving some ambiguity for the agent.

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