Research skills

Browse reusable Agent Skills, each with a clear purpose and practical guidance.

stuart-russell

Applies the reasoning of Stuart Russell, AI safety expert, UC Berkeley professor, and co-author of 'Artificial Intelligence: A Modern Approach'. Reach for this skill whenever evaluating AI safety, value alignment, the control problem, existential risk, AI regulation, or autonomous weapons. Use this when the user is discussing objective uncertainty, reinforcement learning risks, AI governance, or the societal impacts of AGI. Trigger this skill to apply his frameworks on provably beneficial AI, assistance games, and red-line regulation, ensuring AI systems remain deferential, uncertain of their objectives, and strictly aligned with human preferences.

230 repo starsObserved in 2 repos
Research
GitHub

yann-lecun

This skill channels the reasoning of Yann LeCun, Chief AI Scientist at Meta and Turing Award winner. Use this skill whenever you are evaluating AI architectures, discussing the limitations of Large Language Models (LLMs), debating AI safety and regulation (anti-doomerism), or designing autonomous machine intelligence. It is highly relevant for topics involving self-supervised learning, open-source AI strategy, world models, physical grounding versus text-based learning, and objective-driven AI systems. Trigger this skill to apply his frameworks on abstract representation learning (JEPA) and energy-based models, even if the user doesn't explicitly name him.

230 repo starsObserved in 2 repos
Research
GitHub

yoshua-bengio

Applies the reasoning, AI safety frameworks, and deep learning principles of Yoshua Bengio (Turing Award winner, Mila). Reach for this skill whenever you are discussing AI safety, existential risk, deep learning architecture, representation learning, or AI governance. Trigger this skill when the user asks about mitigating AI risks, designing safe-by-design systems, evaluating frontier models, international AI coordination, or the fundamental mechanisms of intelligence (like compositionality and distributed representations). Use it to shift the focus from agentic reward-maximization to non-agentic 'Scientist AI', apply the precautionary principle to catastrophic risks, and emphasize mathematically rigorous guardrails.

230 repo starsObserved in 2 repos
Research
GitHub

docs-lookup

通过 Context7 MCP 获取库和框架的实时最新文档，而非依赖训练数据，防止 API 幻觉。适用于查询任何库或框架的用法、配置、示例代码。触发词：怎么用、怎么配置、API参考、文档、示例代码、用法、接口、库文档、框架文档、documentation、docs、how to use、API reference、setup、configure、React怎么用、Next.js配置、Prisma查询、Vue用法、Express路由、Tailwind类名、Supabase认证、TypeScript类型、Zod验证、shadcn组件、Drizzle ORM、tRPC、Fastify、NestJS、Astro、SvelteKit、Nuxt、Vite、Vitest、Playwright。

230 repo starsObserved in 1 repos
Research
GitHub

interview-knowledge-track

三阶段面试知识点追踪：英文命令 split-knowledge（知识点拆分与 KB-INDEX）、research-topic（按主题检索落盘 opensource + interview-drill）、synthesize-topic（结合 KB 原文与第二步产出，写入经历绑定的架构与面试 Markdown）。别名 kp-split、topic-research、topic-synthesize。中文触发：知识点拆分、按主题检索、业务梳理、薄弱点追踪、KB-INDEX。默认工作目录 interview-knowledge-track/；不自动改写用户工作区文件，除非用户明确要求。自包含，不绑定特定简历路径或仓库结构。

230 repo starsObserved in 1 repos
Research
GitHub

llm-wiki-interview

面试向 LLM Wiki 全流程：Raw 层在 raw/ 沉淀 _research.md、basic/、blog/（见 references/raw-layer.md）；Wiki 层只读 raw/、编译维护 wiki/（实体/概念、index、log，见 references/wiki-layer.md）。触发：建资料包、收录博客、从 raw 导入 wiki、查询、lint、面试备考知识库。关键词：LLM Wiki、raw、wiki、ingest、面试、Obsidian、知识库、用户供稿。

230 repo starsObserved in 1 repos
Research
GitHub

mongodb-query

Query MongoDB notes store for memory analysis and statistics.

230 repo starsObserved in 1 repos
Research
GitHub

research-scope

Investigate the intended scope of a codebase topic through discussion with a human, propose a research-note outline, and only create a .memory-bank/research file after explicit human confirmation.

228 repo starsObserved in 1 repos
Research
GitHub

apify-ecommerce

Scrape e-commerce data for pricing, reviews, bestsellers, and seller discovery across 30+ platforms including Amazon, Walmart, eBay, Shopify, WooCommerce, and more. Use when user asks about product prices, competitor analysis, store scraping, tech stack detection, food delivery, real estate, or marketplace intelligence.

227 repo starsObserved in 2 repos
Research
GitHub

apify-ads-intelligence

Research, spy on, and analyze ads across Meta (Facebook & Instagram), Google (Ads Transparency Center + paid search results), TikTok (Ads Library + Creative Center), LinkedIn Ad Library, and X (Twitter — promoted tweets, best-effort) using Apify Actors. Use when user asks about competitor ads, ad library research, winning creatives, ad copy analysis, landing page audits from ads, cross-platform ad audits, brand transparency checks, or any task involving paid ad creatives, advertiser data, or ad targeting from public ad libraries.

227 repo starsObserved in 1 repos
Research
GitHub