LMS Content Tagging Agent
Automatically tags, categorizes, and organizes uploaded course content in the LMS with consistent metadata so instructors and students can find materials faster.
As instructors upload lecture slides, videos, readings, and assignments into the learning management system, they typically apply tags and folder organization inconsistently or skip metadata entirely, which makes the institution's growing content library difficult for other instructors to search, reuse, or audit for accessibility compliance
IT teams responsible for LMS governance can't manually review and re-tag thousands of uploaded files across every course shell, so content sprawl only gets worse each term
This agent automatically analyzes newly uploaded LMS content, whether documents, video, or slide decks, and applies consistent, structured metadata tags covering subject area, content type, learning objective alignment, and accessibility attributes like caption availability
It flags content missing required accessibility elements for remediation before it reaches students
The agent monitors the LMS content repository via API for newly uploaded files, then runs each item through content analysis appropriate to its type: text extraction and topic classification for documents, transcript generation and accessibility checking for video, and slide text extraction for presentations. It matches extracted content against the institution's standardized tagging taxonomy, covering subject area, content type, course learning objectives, and accessibility status, and applies the resulting tags directly to the LMS item's metadata fields. Content identified as missing required accessibility elements, such as a video with no captions, is flagged and routed to the instructor and the accessibility services team with a specific remediation request before the content is marked available to students.
Detect New Content
- Monitor the LMS repository for newly uploaded files
- Identify content type and course context
- Queue items for automated analysis
Analyze and Extract
- Run text extraction, transcription, or slide parsing as appropriate
- Classify subject area and content type
- Check for accessibility elements like captions and alt text
Apply Structured Tags
- Map analysis results to the standardized tagging taxonomy
- Apply tags to the LMS metadata fields directly
- Link content to relevant course learning objectives
Flag Accessibility Gaps
- Identify content missing required accessibility elements
- Route remediation requests to instructors and accessibility services
- Hold flagged content from full release until remediated per policy