Nanoresearch experiment

Skill OpenRaiser/NanoResearch/skills/nanoresearch-experiment

🦞+🔬 NanoResearch: The Autonomous AI Research Assistant

Install

npx -y skills add OpenRaiser/NanoResearch --skill nanoresearch-experiment

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What its author says it does

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Generate a Python code skeleton from an experiment blueprint

SKILL.md

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Experiment Skill

Purpose

Take the experiment blueprint and produce a runnable Python code skeleton that implements the proposed method, baselines, training loops, evaluation harness, and ablation configurations.

Tools Required

None. This skill operates entirely through LLM code generation based on the experiment blueprint.

Input

experiment_blueprint: Path to papers/experiment_blueprint.json produced by the planning skill

Process

Parse the experiment blueprint for datasets, baselines, metrics, and ablation groups
Generate the project directory structure (data loaders, models, training, evaluation, configs)
Produce data loading and preprocessing code for each specified dataset
Implement model architecture stubs for the proposed method and each baseline
Generate training loop with logging, checkpointing, and early stopping
Implement the evaluation harness computing all specified metrics
Create configuration files for each ablation group
Add a main entry point that accepts a config and runs the full train-evaluate pipeline

Output

Produces experiments/ directory containing:

data/: Data loading and preprocessing modules
models/: Model architecture implementations (proposed method and baselines)
training/: Training loop and optimization utilities
evaluation/: Metric computation and result aggregation
configs/: YAML configuration files for each experiment and ablation variant
run.py: Main entry point for launching experiments
requirements.txt: Python dependencies