Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, and Socratic guided modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review.
Search, read, and query research papers via the `alpha` CLI (alphaXiv-backed). Use when the user asks about academic papers, wants to find research on a topic, needs to read a specific paper, ask questions about a paper, inspect a paper's code repository, or manage paper annotations.
OpenClaw personalized paper recommendation skill. When the user invokes /aminer-rec5 or /skill aminer-rec5 in Feishu, immediately run the local pipeline under {baseDir}/scripts/, accept aminer_user_id, scholar hints, seed paper titles, papers_file, or free-form topic text, build a unified ResearchProfile, retrieve papers, enrich with AMiner, dispatch Feishu cards, and return NO_REPLY.
Public skill for installing, running, debugging, improving, and handing off a Paper Reader style product built with Next.js and FastAPI. Use when the user wants to work on a paper discovery and recommendation app with ranking cards, detail pages, and reproducibility evidence.