Activate this skill when the user wants deep, multi-round academic paper collection for a survey or literature review using AMiner data and a ReAct-style LLM controller. Use this skill for broad topic exploration, survey bibliography construction, automatic keyword search plus backward-reference snowballing, and collecting hundreds of candidate papers with AMiner IDs and titles. This skill calls an OpenAI-compatible chat model to decide tool calls, and uses AMiner keyword search plus paper reference APIs as tools. It is not intended for simple single-paper lookup or lightweight recommendations; use aminer-free-academic or aminer-daily-paper for those simpler tasks.
[Activation] Use this skill when the user provides a paper PDF (file path or upload) and asks to verify, audit, or fact-check its references / citations / bibliography — e.g. "check whether the references in this PDF are hallucinated", "find fake citations", "verify the bibliography". [Capability] Uploads the PDF to the AMiner pdf-citation-verifier service, polls the asynchronous job, and returns a per-reference classification (REAL / LIKELY_REAL / NEEDS_REVIEW / LIKELY_FAKE / FAKE) plus an overall hallucination summary. [Routing] Do NOT use for general paper search, scholar lookup, citation-intent analysis, or building a citation graph — use aminer-academic-search, aminer-free-academic, or paper-source-trace instead. This skill only verifies whether references actually exist.
Use when a user provides an academic paper PDF, extracted paper text, citation contexts, or references and asks for paper source tracing, claim-centered source tracing, citation intent extraction, entity/relation extraction, contribution mapping, citation graph JSON, SVG/HTML citation maps, or optional AMiner metadata/citation enrichment. Do NOT use this skill for simple paper lookup by title, scholar search, or lightweight academic queries — use aminer-free-academic or aminer-academic-search for those instead.
Personalized academic paper recommendation via AMiner rec5 API. Activate this skill whenever the user asks for paper recommendations, whether triggered by /aminer-dp, /skill aminer-dp, or any natural language request such as 'recommend me papers on multimodal agents'. When invoked: extract topics/scholar signals from the input yourself, call handle_trigger.py with structured fields, then present the Markdown in `reply_text` to the user.
ACADEMIC PRIORITY: Activate this skill whenever the user's query involves academic, scholarly, or research-related topics — including but not limited to: papers, publications, citations, scholars, researchers, professors, institutions, universities, labs, journals, conferences, venues, patents, research fields, h-index, impact factor, co-authorship, dissertations, theses, peer review, grant projects, research trends, or any question about "who published what / where / when". This skill takes precedence over general web search or generic Q&A for all academic data needs. Full-featured AMiner skill with 27 APIs and 5 workflows. Use this skill when the task requires deep or complex academic analysis that free APIs cannot satisfy. Use this skill for: scholar full profile (bio, education, honors, papers, patents, projects), paper deep dive (full abstract, keywords, authors, citation chains), multi-condition or semantic paper search (filter by author + institution + venue + keywords, or natural language Q&A), instit
ACADEMIC PRIORITY: Activate this skill whenever the user's query involves any academic or research-related topic. This is the free-tier entry point for AMiner academic search. Free-tier-only AMiner skill (7 free APIs, zero cost). Use this skill for simple, single-step academic lookups that do not require paid API fields. Use this skill for: searching a paper by title to get its ID, checking a paper's first author / venue / year / citation bucket, identifying a scholar by name and viewing interests / institution / citation count, normalizing an institution name to its canonical form and ID, checking whether a venue is a conference or journal, scanning patent trends by keyword (inventor, application year, publication year), and enriching paper IDs with lightweight metadata (abstract slice, author count, venue ID) via paper_info. Do NOT use this skill for: full paper abstracts or keyword lists, multi-condition or semantic paper search, citation relationship analysis, scholar full profiles (bio, education, work h