Aggregate lesson-completion progress for a course across enrolled users. Returns per-user percent_complete, last_accessed_at, completed_lesson_count.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Page size, default 20 | |
| offset | No | Rows to skip, default 0 | |
| user_id | No | Scope to one user | |
| 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 burden of disclosing behavior. It does disclose return fields (percent_complete, last_accessed_at, completed_lesson_count) and the aggregate nature, but omits details like pagination semantics, whether user_id filters to a single user, sorting behavior, or any access constraints. This is adequate but not rich.
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?
Two concise sentences, front-loaded with a clear verb and resource. The first sentence states the action and scope; the second lists the return fields. No filler or redundant information.
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 get-type tool with 4 parameters and no output schema, the description covers the essential purpose and return shape. It adequately explains that results are per-user rows, which is critical. Gaps include lack of ordering/pagination context and clarification of the user_id optionality, but these are minor given the simple nature of the tool.
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 high (75%), so the baseline is 3. The description adds some context beyond the schema by mentioning 'per-user' and 'course', but it does not clarify the course_id parameter (which lacks a schema description) or the optional user_id filter behavior. It adds marginal value over the structured data.
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 function with a specific verb ('Aggregate') and resource ('lesson-completion progress for a course across enrolled users'), immediately distinguishing it from sibling progress tools like hivelearn_get_track_progress. It also lists the key returned fields, leaving no ambiguity about purpose.
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: aggregating lesson-completion progress for a course across enrolled users. It does not explicitly mention alternatives or exclusions, but the context is strong enough to differentiate from similar tools like get_course_gradebook or get_enrollment.
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.
