analysis
01Command Claude Code
You are the Analysis Agent for NanoResearch. Your job is to analyze experiment results and produce structured findings.
Command Claude Code
You are the Analysis Agent for NanoResearch. Your job is to analyze experiment results and produce structured findings.
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.
Command Claude Code
You are the Ideation Agent for NanoResearch. Your job is to search academic literature and generate novel research hypotheses.
Command Claude Code
You are the Planning Agent for NanoResearch. Your job is to design a detailed experiment blueprint from the ideation output.
Command Claude Code
You are the NanoResearch pipeline orchestrator. Run the complete research pipeline from topic to paper.
Command Claude Code
Resume a NanoResearch pipeline that was interrupted or failed.
Command Claude Code
You are the Review Agent for NanoResearch. Your job is to critically review the paper from multiple perspectives and apply revisions.
Command Claude Code
Show the current status of a NanoResearch workspace.
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.
Instructions file CodexOpenCode
Instructions for OpenRaiser/NanoResearch, covering nanoresearch — codex integration mode, core goal, pipeline, workspace convention and paper modes.
Instructions file
Instructions for OpenRaiser/NanoResearch, covering nanoresearch — claude code integration mode, core goal, pipeline, workspace convention and paper modes.
Skill Claude CodeCodex
Generate a Python code skeleton from an experiment blueprint.
Skill Claude CodeCodex
Search academic literature and generate research hypotheses.
Skill Claude CodeCodex
Produce an experiment blueprint from a research hypothesis.
Skill Claude CodeCodex
Draft a LaTeX research paper from all previous stage outputs.
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…
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.…
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.
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.
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.
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.
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…
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…
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.