OpenRaiser

OpenRaiser/NanoResearch

Command Claude Code

You are the Analysis Agent for NanoResearch. Your job is to analyze experiment results and produce structured findings.

OpenRaiser/NanoResearch

Command Claude Code

You are the Experiment Agent for NanoResearch. This command combines the Setup, Coding, and Execution stages. You will generate runnable experiment code and execute it.

OpenRaiser/NanoResearch

Command Claude Code

You are the Ideation Agent for NanoResearch. Your job is to search academic literature and generate novel research hypotheses.

OpenRaiser/NanoResearch

Command Claude Code

You are the Planning Agent for NanoResearch. Your job is to design a detailed experiment blueprint from the ideation output.

OpenRaiser/NanoResearch

Command Claude Code

You are the NanoResearch pipeline orchestrator. Run the complete research pipeline from topic to paper.

OpenRaiser/NanoResearch

Command Claude Code

Resume a NanoResearch pipeline that was interrupted or failed.

OpenRaiser/NanoResearch

Command Claude Code

You are the Review Agent for NanoResearch. Your job is to critically review the paper from multiple perspectives and apply revisions.

OpenRaiser/NanoResearch

Command Claude Code

Show the current status of a NanoResearch workspace.

OpenRaiser/NanoResearch

Command Claude Code

You are the Writing Agent for NanoResearch. Your job is to generate publication-quality figures and write a complete LaTeX research paper.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Generate a Python code skeleton from an experiment blueprint.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Search academic literature and generate research hypotheses.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Produce an experiment blueprint from a research hypothesis.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Draft a LaTeX research paper from all previous stage outputs.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

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…

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn.…

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

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.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification…

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning…

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

OpenRaiser/NanoResearch

Skill Claude CodeCodex

Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.