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Local Blackboard resource search and API-powered Q&A. Search your Blackboard course pages, announcements, PDFs, and docs locally, then ask grounded questions with source links. Overview Blackboard Search Extension turns the Blackboard materials you can already access into a local, searchable study assistant. After you sign in to Blackboard, refresh the local index and ask natural questions about course pages, announcements, linked documents, and PDFs. The extension searches the local index first, ranks the most relevant snippets, then uses your selected API provider to draft an answer grounded in those matched materials. Use it for questions like: - What deadlines are coming up? - What do I need for my X1 visa? - Where is the reading list for this module? - Which documents mention health insurance, packing, or arrival steps? - What did the announcement say about the capstone survey? Answers include expandable source cards so you can open the original Blackboard page or file and verify the response. If you want the answer only, leave the sources collapsed. If something looks off, expand the evidence and inspect the exact materials used. Supported API providers include OpenAI, DeepSeek, and OpenRouter. You choose the provider, model, and API key in Setup. Blackboard Search Extension is designed for students who want faster answers from scattered course materials while still keeping source links close. It is especially useful when Blackboard contains a mix of announcements, PDFs, handbook pages, forms, and deadline reminders. This extension is not affiliated with Blackboard, Anthology, Tsinghua University, or Schwarzman Scholars.
Aug 1, 2026
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.