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get_course_context

Retrieve a Moodle course's compact overview—metadata, sections with module counts, recent lessons, and teacher/student enrolment counts—to decide where to place a new lesson.

Instructions

Returns a compact radiograph of a Moodle course: metadata, sections with module counts, recent MCP-published lessons, and enrolment counts (teachers vs students). Call this before publishing a lesson so the agent knows where it fits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idYes
include_recent_lessonsNo
Behavior3/5

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 discloses the content of the returned 'radiograph' and implies a read-only operation, but it does not mention potential side effects, limitations, or failure modes. It gives useful output detail but not exhaustive behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense sentence enumerating return components, followed by a clear usage directive. Every word adds value, and the structure is well front-loaded with the primary purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-param tool with no output schema, the description covers the main return categories (metadata, sections, lessons, enrolments) and the invocation context. It lacks parameter explanations, but the core purpose and contents are sufficiently described for an agent to call it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 2 parameters but the description provides 0% coverage. It does not explain course_id or include_recent_lessons; the phrase 'recent MCP-published lessons' hints at the latter but no explicit mapping is made. The agent must infer parameter meanings from the output description, which is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses a specific verb 'Returns' and a unique resource label 'compact radiograph of a Moodle course', enumerating concrete components (metadata, sections with module counts, recent MCP-published lessons, enrolment counts). This clearly distinguishes it from sibling tools like publish_class_lesson or get_course_logs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs when to use it: 'Call this before publishing a lesson so the agent knows where it fits.' This provides clear context, though it does not mention exclusions or alternative tools for similar context needs.

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

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