調査、論文、教育、資格学習（4,124 件）
概要と使いどころ
Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.
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Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).
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Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.
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Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.
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Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
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Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.
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Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
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Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.
日本語の概要は準備中です。原文の説明を表示しています。
ARS-Codex research, writing, manuscript review, study screening, and experiments. Use for deep research, literature or systematic reviews, meta-analysis, research questions, drafts, revisions, roadmaps, abstracts, citations, integrity checks, peer review, research-to-paper. Screen records: sr-screener. Citation triggers: check citations, look over the refs, 檢查引用, 檢查參考文獻, 인용 확인, 인용 형식 검사. Korean: 논문 심사, 논문 수정, 초록 작성, 체계적 문헌고찰, 연구부터 논문까지. Español: revisión de literatura, revisar artículo, enmendar mi artículo, escribir resumen, investigación a artículo. Also use for ARS aliases: /ars-plan, /ars-outline, /ars-abstract, /ars-lit-review, /ars-citation-check, /ars-disclosure, /ars-format-convert, /ars-3w, /ars-revision-coach, /ars-revision, /ars-reviewer, /ars-mark-read, /ars-unmark-read, /ars-cache-invalidate, /ars-rebuttal-audit, /ars-full. Prompts, references, templates, and contracts live under ars/.
日本語の概要は準備中です。原文の説明を表示しています。
Research topics across the web and compile structured insights for content creation.
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Research competitors and produce a weekly digest of their positioning, launches, and messaging.
日本語の概要は準備中です。原文の説明を表示しています。
Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python API or the trl CLI.
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Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
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Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
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Use when users /learn, save, remember, or distill lessons.
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Brand mention and authority scanner for AI visibility. Analyzes brand presence across platforms that AI models rely on for entity recognition and citation decisions. Produces a Brand Authority Score (0-100) with platform-specific recommendations.
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Procedure for answering a question with a thorough, cross-checked, cited web-research report using the Keenable search + fetch tools.
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Extract decisions, lessons, patterns, and surprises from completed phase artifacts
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codebase intel | map graphify docs learnings mempalace
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Fetch content from Reddit via its JSON API using a browser session (DuckDuckGo-hop unlock). Use when accessing Reddit URLs, researching topics on Reddit, or when Reddit returns 403/blocked errors.
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Use this skill whenever a user specifically requests legal research or Westlaw Deep Research, asks for CoCounsel Legal or cocounsel legal support, or asks a question that requires explaining, analyzing, or synthesizing U.S. law.
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Cold-start interview — connects to your launch tracker, reads past reviews, learns your risk calibration. Use on fresh install, when onboarding product counsel, or when the plugin config has placeholders. Run with --redo to re-interview, or --check-integrations to re-probe connectors only.
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Run the cold-start interview — learns your privacy practice and writes CLAUDE.md from your policy, DPA template, and a reference PIA. Use on first run, when CLAUDE.md is missing or has placeholders, or when the user says "set up the privacy plugin", "onboard me", "configure privacy", or wants to re-run the interview or re-check integrations.
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Research roadmap for a legal issue — statutes to check, case law areas to investigate, regulatory frameworks, Westlaw search terms. Leads and frameworks, NOT authoritative citations; students verify and develop everything. Use when a student asks where to start researching, wants a research roadmap for an issue, or needs gaps identified in existing research.
日本語の概要は準備中です。原文の説明を表示しています。