Research
Research, evidence gathering, literature, reports, investigation, and synthesis
Browse research skills
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This skill should be used when the user asks to "brainstorm research ideas", "use 5W1H framework", "identify research gaps", "conduct gap analysis", "start research project", "conduct literature review", "define research question", "select research method", "plan research", or mentions research project initiation phase. Provides comprehensive guidance for research startup workflow from idea generation to planning.
Research Engineer for initial investigation, data gathering, and feasibility studies. Use this skill when exploring new technologies, analyzing existing systems, or gathering requirements data.
Research topics and document findings in Notion with organized structure and sources
Research topics and document findings in Notion with organized structure and sources
Comprehensive multi-source research with academic depth. Searches web, social platforms, news, academic databases, and GitHub. Discovers papers, datasets, and open source implementations. Use when conducting research, literature reviews, or investigating any topic.
Lightweight parallel research orchestration without full council debate. Spawns oracle agents with different queries, collects findings, synthesizes report.
Use when the user asks to research, investigate, compare approaches, or explore a topic in depth. Supports configurable depth and multi-source synthesis.
Multi-source research orchestration. Chains deepwiki, submodules, WebSearch, and codebase search. Defines when to escalate and how to synthesize findings.
Research and compare the Stateless Agent Methodology (SAM) against other methodologies using only verifiable reference material. Produce overlap/divergence analysis that is useful for comparing strategy, methodologies, and potential implementations, and for identifying weaknesses in the current SAM methodology while changes are still cheap. Creates structured comparison documents following the SAM comparison template, including terminology normalization + attribution notes.
Extract structured knowledge from source material. Comprehensive extraction is the default — every insight that serves the domain gets extracted. For domain-relevant sources, skip rate must be below 10%. Zero extraction from a domain-relevant source is a BUG. Triggers on "/reduce", "/reduce [file]", "extract insights", "mine this", "process this".
Get research-backed architecture advice for your knowledge system. Describe your use case, constraints, and goals — get specific recommendations grounded in TFT research with rationale for each decision. Triggers on "/recommend", "what would you recommend", "architecture advice", "knowledge system for".
Rapid topic mastery for video/content prep. Takes a topic → generates 5 research questions → parallel PubMed + web search → outputs McKinsey-style brief in 5 minutes. Use BEFORE recording videos or writing content.
Systematically resolve questions - determine if answerable, gather evidence
Evaluate ENCODE experiment quality using standard metrics and audit flags. Use when the user asks about data quality, wants to filter for high-quality experiments, needs to interpret quality metrics (FRiP, NSC, RSC, NRF, IDR, TSS enrichment, fragment size), wants to understand ENCODE audit warnings, needs to compare quality across experiments, or is deciding whether data is usable for their analysis. Also use when the user mentions QC, quality control, or data filtering.
直接访问PubMed REST API。高级布尔/MeSH查询、E-utilities API、批量处理、引文管理。对于Python工作流,建议使用biopython (Bio.Entrez)。此技能适用于直接HTTP/REST操作或自定义API实现。
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
Assess the scientific integrity and trustworthiness of publications before relying on their findings. Use this skill whenever evaluating a paper for a workflow, citing a study, building an analysis on published methods, or when a user asks about the reliability of a study. Checks for formal retractions, corrections, expressions of concern, and — critically — informal contradictions where subsequent studies failed to reproduce key findings. Integrates with PubMed, bioRxiv, and Consensus to pro...
Practitioner methodology for longitudinal case study research, evidence-based documentation, and publication-ready academic writing in AI-assisted development.
Practitioner methodology for longitudinal case study research, evidence-based documentation, and publication-ready academic writing in AI-assisted development.
Simulate peer review of academic papers with structured feedback. Produces bilingual review report with scoring and actionable suggestions. Triggers on "review", "peer review", "simulate reviewer", "审稿", "模拟评审".
Verify logical consistency across paper sections. Traces argument chains and identifies gaps, unsupported claims, terminology inconsistencies, and number contradictions. 论文逻辑验证,识别论证链断裂、无支撑声明、术语不一致、数字矛盾。
Analyze experiment results and generate discussion paragraphs for academic papers. Two-phase workflow: identify measurable findings (Phase 1), confirm with user, then generate grounded discussion paragraphs (Phase 2). Accepts tables, statistics, or result descriptions. 实验分析与讨论段落生成。
Review completed work and learn.