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Found 57 Skills
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Triggers whenever a user uploads a syllabus, course outline, or curriculum document and wants supplementary readings. Also triggers on: 'syllabus reading list', 'find papers for my course', 'create a reading list from this syllabus', 'recent research for my class', 'supplementary readings', 'find journal articles for these topics', 'what recent papers cover this material', 'any new research on these course topics', 'update my syllabus with recent papers'. Even casual mentions when a syllabus is attached should trigger this skill.
Run any question, plan, PR, or code through a Diverse Multi-Agent Debate (DMAD) council of 5 AI advisors with distinct reasoning methods. Advisors collaborate, peer-review each other anonymously, and a chairman synthesizes a verdict. Empirically outperforms adversarial debate (M3MADBench 2026, DMAD ICLR 2025). Use when: 'council this', 'run the council', 'council review', 'pressure-test this', 'stress-test this', 'war room this', or when facing a genuine decision with stakes and tradeoffs.
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
Academic writing, research methodology, and scholarly communication workflows. Use when writing papers, literature reviews, grant proposals, conducting research, managing citations, or preparing for peer review. Essential for researchers, graduate students, and academics across disciplines.
Specialized workflows for drafting, refining, and responding to academic literature reviews and peer review feedback. Use this skill for literature review outlines, research-gap synthesis, reviewer rebuttals, response letters, and academic writing tone repair.
Write point-by-point rebuttals to reviewer comments. Extract concerns from reviews, generate evidence-based responses, and format as a structured rebuttal document. Use after receiving peer review feedback.
Systematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
Create a novelty/prior-work matrix comparing the submission’s contributions against related work (overlaps vs deltas). **Trigger**: novelty matrix, prior-work matrix, overlap/delta, 相关工作对比, 新颖性矩阵. **Use when**: peer review 中评估 novelty/positioning，需要把贡献与相关工作逐项对齐并写出差异点证据。 **Skip if**: 缺少 claims（先跑 `claims-extractor`）或你不打算做新颖性定位分析。 **Network**: none (retrieval of additional related work is out-of-scope unless provided). **Guardrail**: 明确 overlap 与 delta；尽量给出可追溯证据来源（来自稿件/引用/作者陈述）。
MantaBase T3 Hardware Audit System (Chinese Version). Objectively classify hardware products based on design theories through Brand Blinding, three Auditor (Tool/Toy/Trash) special scoring and Peer Review. Triggers: product link, T3 audit, Tool/Toy/Trash classification, hardware evaluation, VC investment advice
Student weekly assignment planner for Canvas LMS. Shows all due dates, submission status, grades, and peer reviews across all courses. Use when a student says "what's due", "plan my week", "weekly check", or wants to organize their coursework.
Run a decision through 5 AI advisors with different thinking styles, anonymous peer review, and chairman synthesis. For genuine decisions with stakes and tradeoffs — not simple questions. Based on Karpathy's LLM Council.