get_course_announcementsFetch announcements for a specific Ninova course to track instructor updates, deadlines, and course news from your ITÜ LMS account.
Return announcements for a specific Ninova course.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| course | Yes | ||
| compact | No | ||
| include_full_text | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.2.1Output schema / additionalPropertiesRemoved value: -trueOutput schema / propertiesAdded value: +{
+ "result": {
+ "additionalProperties": true,
+ "title": "Result",
+ "type": "object"
+ }
+}Output schema / requiredAdded value: +[
+ "result"
+]Output schema / titlePrevious value: -"get_course_announcementsDictOutput"New value: +"get_course_announcementsOutput"v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond that — no pagination behavior, no indication of what 'compact' or 'include_full_text' change about the result, and no note on how many announcements are returned by default.
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?
A single front-loaded sentence with zero filler is structurally clean, but at this length it is terse rather than concise — it omits information the agent needs, so brevity here costs more than it saves.
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?
An output schema exists, so return values need not be described. But with four parameters at 0% schema coverage and a dense sibling set of announcement-related tools, the definition is too thin to let an agent invoke it confidently.
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 0% across four parameters, so the description is the only chance to explain them. It alludes only to 'course' and says nothing about limit (default 50), compact, or include_full_text, which are the genuinely opaque flags; the compensation required for low coverage is absent.
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 names a specific verb+resource ('Return announcements') and scopes it to 'a specific Ninova course', which is concrete and readable. However, it never distinguishes this tool from the sibling get_dashboard_announcements or get_itu_announcements, so scope boundaries must be inferred from the name.
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?
There is no when-to-use guidance, no prerequisite or auth context, and no routing to alternatives such as get_dashboard_announcements for cross-course announcements. The agent is left to guess which announcement tool applies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.