🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
BytesAgain β€Ί Skills β€Ί NeuriCo
πŸ¦€ ClawHub

NeuriCo

by @laoliu5280

Autonomous research framework that orchestrates AI agents (Claude Code, Codex, Gemini) to design, execute, analyze, and document scientific experiments. Take...

Versionv0.2.1
Downloads580
#crypto-defi#research#legal
TERMINAL
clawhub install neurico

πŸ“– About This Skill

name: neurico version: 0.2.0 description: > Autonomous research framework that orchestrates AI agents (Claude Code, Codex, Gemini) to design, execute, analyze, and document scientific experiments. Takes a structured research idea (YAML with title, domain, hypothesis) and produces code, results, plots, LaTeX papers, and GitHub repositories. tags: - autonomous-research - ai-scientist - experiment-automation - research-agent - paper-writing - literature-review - hypothesis-testing - scientific-computing - multi-agent - machine-learning - docker - latex

NeuriCo

Autonomous AI research framework. Idea in, paper out.

Quick Reference

| | | |---|---| | What it does | Takes a research idea (YAML) and autonomously runs the full research lifecycle: literature review, experiment design, code execution, analysis, paper writing, GitHub push | | Input | YAML file with 3 required fields: title, domain, hypothesis | | Output | Code (src/), results & plots (results/), LaTeX paper (paper_draft/), GitHub repo | | Providers | Claude Code, Codex, Gemini (OAuth login, not API keys) | | Install | git clone https://github.com/ChicagoHAI/neurico && cd neurico && ./neurico setup | | Source | github.com/ChicagoHAI/neurico β€” Chicago Human+AI Lab (ChicagoHAI), University of Chicago | | License | Apache 2.0 |

Requirements

Minimal (one of)

| Option | What you need | |--------|--------------| | Docker (recommended) | git + docker | | Native | git + python>=3.10 + uv |

Resource

Access to at least one AI coding CLI (OAuth login required):

  • Claude Code (recommended)
  • Codex
  • Gemini CLI

    • Recommended

    | What | Why | |------|-----| | GitHub token (classic, repo scope) | Auto-creates repos and pushes results. Create here |

    Optional API Keys

    | Key | Purpose | |-----|---------| | OPENAI_API_KEY | LLM-based repo naming, IdeaHub fetching, paper-finder | | S2_API_KEY | Semantic Scholar literature search via paper-finder | | OPENROUTER_KEY | Multi-model access during experiments | | COHERE_API_KEY | Improves paper-finder ranking (~7% boost) | | HF_TOKEN | Hugging Face private models/datasets | | WANDB_API_KEY | Weights & Biases experiment tracking |

    Setup Tiers

  • Basic: CLI login + GITHUB_TOKEN -- full NeuriCo functionality
  • Enhanced: + OPENAI_API_KEY -- LLM repo naming + IdeaHub support
  • Full: + S2_API_KEY (+ optional COHERE_API_KEY) -- paper-finder literature search

    • Installation

    Docker (recommended)

    The Docker image is a pre-configured environment with Python, Node.js, AI coding CLIs (Claude Code, Codex, Gemini), and a full LaTeX installation for paper compilation -- so you don't have to install any of these yourself. All experiments run inside this container; nothing is installed on your host system beyond the cloned repo. The image is built from the open-source Dockerfile and hosted on GitHub Container Registry.

    git clone https://github.com/ChicagoHAI/neurico && cd neurico
./neurico setup     # pulls Docker image, configures API keys, walks through CLI login

    Or step by step:

    git clone https://github.com/ChicagoHAI/neurico && cd neurico
docker pull ghcr.io/chicagohai/neurico:latest
docker tag ghcr.io/chicagohai/neurico:latest chicagohai/neurico:latest
./neurico config    # configure API keys
claude              # login to AI CLI (one-time, on host)

    Native

    git clone https://github.com/ChicagoHAI/neurico && cd neurico
curl -LsSf https://astral.sh/uv/install.sh | sh
uv sync
cp .env.example .env   # edit: add your API keys
claude                  # login to AI CLI

    Invocation

    Fastest: Fetch from IdeaHub and run

    ./neurico fetch  --submit --run --provider claude

    Browse ideas at IdeaHub, copy the URL, and run the command above. NeuriCo fetches the idea, creates a GitHub repo, runs experiments, writes a paper, and pushes everything.

    From a YAML file

    ./neurico submit path/to/idea.yaml
./neurico run  --provider claude

    Run options

    | Option | Description | |--------|-------------| | --provider claude\|gemini\|codex | AI provider (default: claude) | | --no-github | Run locally without GitHub integration | | --write-paper | Generate LaTeX paper after experiments (default: on) | | --paper-style neurips\|icml\|acl\|ams | Paper format (default: neurips) | | --private | Create private GitHub repository |

    Input Format

    Only 3 fields required:

    idea:
  title: "Do LLMs understand causality?"
  domain: artificial_intelligence
  hypothesis: "LLMs can distinguish causal from correlational relationships"

    Optional fields: background (papers, datasets, code references), methodology (approach, steps, baselines, metrics), constraints (compute, time, memory, budget), expected_outputs, evaluation_criteria.

    Full schema: ideas/schema.yaml

    Output Format

    workspace//
  src/            # Python experiment code
  results/        # Metrics, plots, models
  paper_draft/    # LaTeX paper (with --write-paper)
  logs/           # Execution logs
  artifacts/      # Models, checkpoints
  .neurico/       # Original idea spec

    Results are automatically pushed to the GitHub repo created during submission.

    Supported Domains

    | Domain | Examples | |--------|----------| | Artificial Intelligence | LLM evaluation, prompt engineering, AI agents | | Machine Learning | Training, evaluation, hyperparameter tuning | | Data Science | EDA, statistical analysis, visualization | | NLP | Language model experiments, text analysis | | Computer Vision | Image processing, object detection | | Reinforcement Learning | Agent training, policy evaluation | | Systems | Performance benchmarking, optimization | | Theory | Algorithmic analysis, proof verification | | Scientific Computing | Simulations, numerical methods |

    Configuration

    ./neurico config      # Interactive API key configuration
./neurico setup       # Full setup wizard
./neurico shell       # Interactive shell inside container
./neurico help        # Show all commands

    Environment variables go in .env (copy from .env.example). See README for details.

    Security

  • No secrets are uploaded. API keys and tokens stay local in your .env file and are never committed, pushed, or sent anywhere beyond the APIs they authenticate with. Sensitive environment variables are explicitly filtered out from all subprocess calls and sanitized from logs.
  • Experiments run inside Docker. The container is isolated from your host system. The only host directories mounted are your config, templates, and workspace output folder.
  • Open source. The entire codebase, including the Dockerfile and install script, is publicly auditable on GitHub.
  • Built by ChicagoHAI β€” the Human+AI Lab at the University of Chicago.

    • βš™οΈ Configuration

    ./neurico config      # Interactive API key configuration
./neurico setup       # Full setup wizard
./neurico shell       # Interactive shell inside container
./neurico help        # Show all commands

    Environment variables go in .env (copy from .env.example). See README for details.