moodle-mcp

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 describes the tool as a read-only operation ('returns') and specifies the scope of data returned, which is helpful. However, it doesn't mention potential limitations like permissions needed, error conditions, or rate limits, leaving some behavioral aspects unclear for a tool with no annotation coverage.

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 front-loaded with the core purpose in the first sentence and follows with a clear usage guideline. Every sentence adds value without redundancy, making it efficiently structured and appropriately sized for the tool's complexity.

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 (2 parameters, no output schema, no annotations), the description provides good context on purpose and usage. It explains what the tool returns and when to use it, which is sufficient for a read-only tool. However, without an output schema or annotations, it could benefit from more details on return format or error handling, slightly limiting completeness.

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?

With 0% schema description coverage, the description must compensate for undocumented parameters. It explains the purpose of the tool's output but doesn't directly describe the parameters. However, the context ('compact radiograph of a Moodle course') and the parameter names ('course_id', 'incluir_ultimas_clases') are intuitive, and the description implies the tool fetches course-specific data, adding some semantic value. Since there are only 2 parameters, this partial compensation earns a 4.

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 ('returns a compact radiograph') and resources ('Moodle course'), detailing exactly what information is provided (metadata, sections with module counts, recent MCP-published lessons, enrolment counts). It distinguishes this tool from siblings by explaining its preparatory role for publishing a Ficha, making it highly specific and differentiated.

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 ('Call this before publishing a Ficha so the agent knows where it fits'), providing clear context and purpose. It distinguishes it from sibling tools by positioning it as a preparatory step for publishing operations, offering specific guidance on its role in the workflow.

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