From 352d95519c4f3a42d733ace51e63082174da0682 Mon Sep 17 00:00:00 2001 From: willamhou Date: Mon, 16 Mar 2026 15:03:39 +0800 Subject: [PATCH] Add use case: HF Papers Research Discovery MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Discover and triage trending ML papers from Hugging Face Papers, then deep-read via arxiv-reader — a two-skill research pipeline. --- README.md | 1 + usecases/hf-papers-research-discovery.md | 52 ++++++++++++++++++++++++ 2 files changed, 53 insertions(+) create mode 100644 usecases/hf-papers-research-discovery.md diff --git a/README.md b/README.md index 0e1fe4d..ae446cb 100644 --- a/README.md +++ b/README.md @@ -89,6 +89,7 @@ Solving the bottleneck of OpenClaw adaptation: Not ~~skills~~, but finding **way | [Semantic Memory Search](usecases/semantic-memory-search.md) | Add vector-powered semantic search to your OpenClaw markdown memory files with hybrid retrieval and auto-sync. | | [arXiv Paper Reader](usecases/arxiv-paper-reader.md) | Read and analyze arXiv papers conversationally — fetch by ID, browse sections, compare abstracts, and get AI summaries. | | [LaTeX Paper Writing](usecases/latex-paper-writing.md) | Write and compile LaTeX papers conversationally with instant PDF preview — no local TeX installation needed. | +| [HF Papers Research Discovery](usecases/hf-papers-research-discovery.md) | Discover trending ML papers on Hugging Face, triage by upvotes, and deep-read via arXiv — all conversationally. | ## Finance & Trading diff --git a/usecases/hf-papers-research-discovery.md b/usecases/hf-papers-research-discovery.md new file mode 100644 index 0000000..2fb9518 --- /dev/null +++ b/usecases/hf-papers-research-discovery.md @@ -0,0 +1,52 @@ +# HF Papers Research Discovery + +Keeping up with ML research means refreshing Hugging Face Papers daily, scanning dozens of titles, clicking into each one for the abstract, and manually cross-referencing GitHub repos. You want a conversational way to discover, triage, and deep-read trending papers without leaving your workspace. + +This workflow combines two skills to create a full research discovery pipeline: + +- Browse today's trending papers on Hugging Face — sorted by upvotes or date +- Search papers by keyword to find relevant work on any topic +- Get full paper metadata: abstract, authors, GitHub repos, community upvotes, AI-generated summaries +- Read community discussion and comments on any paper +- Deep-read the full LaTeX source of any paper via its arXiv ID (using arxiv-reader) + +## Skills you Need + +- [hf-papers](https://github.com/openclaw/skills/tree/main/skills/willamhou/hf-papers) skill (4 tools: `hf_daily_papers`, `hf_search_papers`, `hf_paper_detail`, `hf_paper_comments`) +- [arxiv-reader](https://github.com/openclaw/skills/tree/main/skills/willamhou/arxiv-source) skill (3 tools: `arxiv_fetch`, `arxiv_sections`, `arxiv_abstract`) — for full paper text + +No Docker or authentication required — both skills use public APIs with local caching. + +## How to Set it Up + +1. Install both skills: +```bash +clawhub install hf-papers +clawhub install arxiv-source +``` + +2. Prompt OpenClaw with your research workflow: +```text +I want to stay on top of ML research. Here's my daily workflow: + +1. Every morning, show me the top 10 trending papers on Hugging Face (sorted by upvotes) + - For each paper, show: title, upvotes, GitHub repo (if any), and 1-line AI summary + +2. When I say "search [topic]": + - Search HF Papers and show the most relevant results + - Highlight papers with linked GitHub repos or high upvote counts + +3. When I pick a paper (by ID): + - Show the full abstract, authors, and linked resources + - Show community comments if any + - Ask if I want a deep read + +4. For deep reads: + - Fetch the full paper via arxiv-reader + - Summarize key contributions, methodology, and results + - Note any linked code repos I should check out + +Keep a running list of papers I've reviewed today with one-line takeaways. +``` + +3. Try it: "What's trending on Hugging Face Papers today?"