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Conduct pure research for YouTube video topics by analyzing competitors, identifying content gaps, and documenting strategic insights. Use when you need to research a video topic before planning. Produces conci...
Curated repository of experiment hypotheses, assumptions, and historical learnings.
Use when planning features and need current API docs, library patterns, or external knowledge; when testing hypotheses about technology choices or claims; when verifying assumptions before design decisions - ga...
Research standards/patterns via MCP Ref. Generates Standards Research for Story Technical Notes subsection. Reusable worker.
Research best practices via MCP Ref/Context7/WebSearch and create documentation (guide/manual/ADR/research). Single research, multiple output types.
This skill should be used when the user asks to "research a topic", "deep research", "investigate thoroughly", "multi-source research", "comprehensive analysis", or needs to conduct research across web, documen...
Execute autonomous multi-step research using Google Gemini Deep Research Agent. Use for: market analysis, competitive landscaping, literature reviews, technical research, due diligence. Takes 2-10 minutes but p...
Use when researching documentation, papers, or articles for insights. Triggers on "research external", "find sources", "literature review", "what do the docs say".
Scrape documentation websites into organized reference files. Use when converting docs sites to searchable references or building Claude skills.
Detects AI-generated writing patterns and suggests authentic alternatives. Auto-applies when reviewing content, editing documents, generating text, or when user mentions writing quality, AI detection, authentic...
Scrape documentation websites into organized reference files. Use when converting docs sites to searchable references or building Claude skills.
Aggregate multi-reviewer feedback into consolidated, actionable recommendations. Use when relevant to the task.
Detects AI-generated writing patterns and suggests authentic alternatives. Auto-applies when reviewing content, editing documents, generating text, or when user mentions writing quality, AI detection, authentic...
Comprehensive toolkit for detecting and eliminating "AI slop" - generic, low-quality AI-generated patterns in natural language, code, and design. Use when reviewing or improving content quality, preventing gene...
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Expert web research with advanced search techniques. Use for deep research, information gathering, or fact verification.
This skill should be used when users explicitly request academic papers, recent research, most cited research, or scholarly articles about longevity, aging, lifespan extension, or related topics. Triggers on ph...
This skill should be used when users request comprehensive, in-depth research on a topic that requires detailed analysis similar to an academic journal or whitepaper. The skill conducts multi-phase research usi...
This skill should be used when users want to validate or critique an argument by extracting premises, surfacing hidden assumptions, checking logical validity, optionally formalizing in Lean, and researching pre...
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
LLM output evaluation and quality assessment. Use when implementing LLM-as-judge patterns, quality gates for AI outputs, or automated evaluation pipelines.
Query decomposition for multi-concept retrieval. Use when handling complex queries spanning multiple topics, implementing multi-hop retrieval, or improving coverage for compound questions.
Advanced RAG with Self-RAG, Corrective-RAG, and knowledge graphs. Use when building agentic RAG pipelines, adaptive retrieval, or query rewriting.
HyDE (Hypothetical Document Embeddings) for improved semantic retrieval. Use when queries don't match document vocabulary, retrieval quality is poor, or implementing advanced RAG patterns.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.