Thinkific MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Returns'), which is helpful, but lacks critical details: it doesn't specify authentication requirements, rate limits, error handling (e.g., what happens if the slug doesn't exist), or the structure of the returned Course object. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 extremely concise—a single sentence that efficiently conveys the core functionality. It's front-loaded with the key action and resource, with no wasted words. This brevity is appropriate for a simple lookup tool, though it comes at the cost of completeness in other dimensions.

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?

For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what a 'Course' object contains, how errors are handled, or any dependencies (e.g., authentication). Given the complexity implied by GraphQL and the lack of structured metadata, more context is needed to fully understand the tool's operation and results.

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?

The schema description coverage is 100%, with the 'slug' parameter fully documented in the schema. The description adds minimal value beyond this, only reinforcing that the tool operates 'by slug'. It doesn't provide examples of valid slug formats, constraints, or how slugs relate to other identifiers. Given the high schema coverage, a baseline score of 3 is appropriate.

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 action ('Returns') and resource ('a Course by slug'), making the purpose understandable. It distinguishes this as a GraphQL variant, which helps differentiate it from non-GraphQL siblings like 'get_course'. However, it doesn't explicitly contrast with 'gql_course' (which likely returns a course by ID), leaving some ambiguity about when to use this specific slug-based query.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'by slug' and 'GraphQL', but doesn't explain when to prefer this over 'get_course' (which might use REST) or 'gql_course' (which might use a different identifier). There's no mention of prerequisites, error conditions, or typical use cases.

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