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Found 36 Skills
Multi-AI Parallel Deep Research. Triggered when users need comprehensive research, in-depth study, multi-party comparison, or comprehensive analysis covering multiple dimensions and sources for a certain topic. Suitable for complex topics (technical selection, competitor analysis, industry trends, controversial topics, etc.), not suitable for simple fact queries. Conduct parallel research through multiple AI services, cross-validate, and output a comprehensive report with citations.
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.
Search, filter, and format entries from BibTeX or BibLaTeX .bib files for research workflows. Use when a user wants to find papers, search a bibliography, filter a library, or look up references by topic, author, year, venue, DOI, arXiv ID, keywords, annotation, abstract, or entry type. Handles Zotero-exported libraries. Supports compact search expressions such as author:, year-gte, type:, and has:, combined filters, research-oriented output fields, raw BibTeX export, and LaTeX/Typst citation snippet generation.
Guide a CS or AI PhD student through a focused literature review sprint that produces a ranked paper map, notes, gaps, and next actions. Use this skill whenever the user needs to survey a topic, prepare related work, check whether an idea is novel, catch up on a field, read papers before a meeting, or turn a pile of papers into an organized research direction.
Sync verified experiment results from the code repo or a code worktree into the paper's daily experiments log and project memory. Use when results in code/docs/results, code/docs/reports, code/docs/runs, worktree docs, logs, or user-confirmed metrics should be promoted into paper-facing evidence.
Create a new Git branch or code worktree for experiments, features, baselines, rebuttal fixes, or method revisions. Use when starting an isolated code direction, creating a branch, creating a project-aware code worktree under a project control root, or setting up a worktree with UV sync, IDE config copying, linked assets, and worktree memory.
Diagnose surprising, negative, unstable, or ambiguous ML/AI experiment results and decide whether to debug implementation, rerun experiments, change metrics or baselines, revise the algorithm, narrow the paper claim, park, or kill a direction. Use this skill whenever results do not match expectations, a method fails, metrics conflict, seeds vary, baselines beat the method, plots look suspicious, or the user asks what to do next after experimental results.
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 comprehensive research using perplexity-researcher, claude-researcher, and gemini-researcher agents. Launches up to 10 parallel research agents for fast results. USE WHEN user says 'do research', 'research X', 'find information about', 'investigate', 'analyze trends', 'current events', or any research-related request.
Conduct topic and competitor research for any content type. Analyzes existing content landscape, identifies gaps, and produces actionable insights. This is a generalized research skill — platform-specific tools and output locations are provided by orchestrator skills.
Search and research enhancement skills. Use when performing web searches, looking up library documentation, or conducting research that requires multiple sources.
Run the Phase 0 research workflow to scaffold research artifacts before task planning.