hivelearn_create_enrollment
Enroll a user in a course. Both user_id and course_id must belong to the authenticated community. Duplicate enrollments are rejected.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | ||
| course_id | Yes |
Enroll a user in a course. Both user_id and course_id must belong to the authenticated community. Duplicate enrollments are rejected.
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | ||
| course_id | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses two key behaviors: both IDs must belong to the authenticated community and duplicate enrollments are rejected. However, it does not mention return values, error handling, permissions, or side effects, leaving some behavioral ambiguity.
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 two sentences, front-loaded with the action, and every sentence adds meaningful information. No filler or redundant phrasing.
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?
The tool is simple (two required UUID parameters) and the description covers the core purpose and two important constraints. It lacks mention of return value or error behavior, but those could be inferred from the action. Given the simplicity, it is mostly complete.
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 coverage is 0%, so the description must compensate. It adds the community constraint for both user_id and course_id, which is helpful, but it does not individually explain the semantics of each parameter beyond their names. The tool name and first sentence already imply the roles, but the description could go further.
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 states a clear action ('Enroll a user in a course') with a specific verb and resource, and it adds constraints (community membership, duplicate rejection) that distinguish it from sibling tools. This clearly separates it from create_course, create_certificate, and other create operations.
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 clear context for when to use the tool: to enroll a user in a course. It implies a prerequisite (community membership) and a constraint (duplicates rejected) but does not explicitly name alternative tools or state when not to use it. The context is sufficient for a straightforward creation tool with no direct sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool targets a distinct resource/action combination, and similar-looking tools are carefully differentiated in descriptions (e.g., get_course_structure vs list_course_modules, update_lesson vs update_lesson_content). There is no meaningful overlap or ambiguity between tools.
All tools use a consistent 'hivelearn_<verb>_<noun>' pattern with common verbs (get, list, create, update). The only minor deviation is 'add' vs 'create' (add_track_course vs create_track), but this is semantically appropriate and does not disrupt the overall pattern.
With 57 tools, the server is significantly over the recommended range and exceeds the 25+ threshold for 'too many'. While the broad domain (courses, community, analytics) justifies a large surface, this many tools makes selection overwhelming for agents and suggests a need for consolidation or sub-servers.
The tool surface covers create, read, and update for most core entities (courses, lessons, quizzes, tracks, posts, events, resources), plus publishing/verification and analytics. However, there are notable gaps: no delete operations for courses, lessons, modules, quizzes, posts, events, resources, or enrollments, and no way to remove a course from a track. These lifecycle holes are significant but not fatal for common workflows.