LearnMCP 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 of behavioral disclosure. It states the tool retrieves summaries but doesn't cover key aspects like whether it's read-only (implied by 'Get'), potential rate limits, authentication needs, error handling, or the format of returned summaries. For a tool with no annotation coverage, this is insufficient, as it leaves critical behavioral traits unspecified.

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 a single, efficient sentence: 'Get learning content summary for a project or specific source.' It is front-loaded with the core purpose, uses clear language, and avoids unnecessary words. Every part of the sentence contributes directly to understanding the tool's function, making it highly concise and well-structured.

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 (3 parameters, no output schema, no annotations), the description is incomplete. It lacks details on return values, error conditions, and behavioral traits like performance or limitations. Without annotations or an output schema, the description should compensate by explaining what the summary contains or how it's structured, but it doesn't, leaving gaps in understanding for effective use.

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%, meaning all parameters are documented in the schema. The description adds minimal value beyond the schema by implying that 'source_id' is optional and affects aggregation, but it doesn't provide additional context like examples or edge cases. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

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: 'Get learning content summary for a project or specific source.' It specifies the verb ('Get'), resource ('learning content summary'), and scope ('project or specific source'), which is clear and actionable. However, it doesn't explicitly differentiate from sibling tools like 'list_learning_sources' or 'get_processing_status', which might offer related functionality, so it doesn't reach the highest score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools such as 'list_learning_sources' for listing sources or 'get_processing_status' for checking processing state, nor does it specify prerequisites like needing a project ID or when to use source_id for a specific source versus aggregated summary. This lack of contextual direction leaves usage ambiguous.

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