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Found 44 Skills
Write ML papers for NeurIPS/ICML/ICLR: design→submit.
Guide agents through structured research including planning, multi-query execution, source analysis, and synthesis. Use for comprehensive topic research, deep investigation, or creating research reports. Keywords: research, investigate, deep dive, comprehensive, analysis, synthesis, report.
Deep Research Skill - Multi-source investigation across X (Twitter), the Web, and academic papers using team agents. Utilize this skill when users request deep research, comprehensive investigation, multi-perspective analysis, or hypothesis development on any topic. It is triggered by phrases such as "deep research", "investigate thoroughly", "research across sources", "ディープリサーチ", or requests for fact-based analysis with original hypotheses. It conducts a 6-phase research process: needs analysis, X preliminary research, parallel web deep-dive (3 agents), information integration, hypothesis construction, and final report delivery.
Search and download academic papers from arXiv. Find papers by keywords, authors, or arXiv ID.
Use when answering complex questions about a codebase that require exploring multiple areas or understanding how components connect - coordinates parallel sub-agents to locate, analyze, and synthesize findings
Run a literature review using paper search and primary-source synthesis. Use when the user asks for a lit review, paper survey, state of the art, or academic landscape summary on a research topic.
Researches topics and trends for blog content with parallel multi-agent execution. USE WHEN orchestrator invokes research phase OR user says 'research topic', 'find trends', 'gather information for blog'.
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
Use when planning, running, comparing, or recording computational experiments, benchmarks, ablations, autonomous research loops, overnight runs, training runs, or exploratory variants.
Autonomous research agent that reads RESEARCH.md, infers what's needed, dynamically adjusts TODOs, and delegates to the right skill. Supports opt-in BFS mode for autonomous design space search. Respects a configurable supervision policy (presets: manual / checkpointed / autonomous / wild) governing notifications, approval gates, resource limits, and idea-change handling. Proactively surfaces gaps and asks before acting. Trigger phrases: "start research", "continue project", "what's next?", "explore design space", "autoresearch".
Schedule "research + content production" tasks in A/B/C levels. First define the audience, goal, carrier and perspective, then follow the Research→Synthesis→Content pipeline to output publishable content and evidence chains. It is suitable for writing tasks that require credible conclusions, stable structure and reusable material precipitation.
Iterative multi-round deep research with structured analysis frameworks. Use for: deep research on a topic, compare X vs Y, landscape analysis, evaluate options for a decision, deep dive into a technology, comprehensive research with cross-referencing. Triggers: deep research, compare, landscape, evaluate, deep dive, comprehensive research, which is better, should we use.