Verify scientific claims, check calculations, validate experimental designs, and fact-check citations. Use when: (1) checking a claim against evidence, (2) validating statistical analyses, (3) verifying experimental reproducibility claims, (4) fact-checking references, (5) adversarial review of research. NOT for: generating new content (use scienceclaw-generation), simple QA (use scienceclaw-qa).
# Reproducibility Checklist โ Open Science Best Practices
Medical device standards compliance verification skill for ISO 13485, ISO 14971, IEC 62304, IEC 60601, and related standards
Measurement System Analysis (MSA) skill for Gage R&R studies with variance component analysis and measurement adequacy assessment
Performs statistical analysis for A/B testing experiments
Test equipment integration for signal analysis (oscilloscope and logic analyzer)
Power consumption measurement and analysis expertise for embedded systems. Integrates with power analyzer tools to measure, profile, and optimize power consumption in battery-powered and energy-efficient designs.
Develop survey instruments, implement sampling strategies, optimize response rates, and manage multi-mode data collection
Develop, validate, and adapt measurement instruments including factor analysis, reliability testing, and cross-cultural validation
Nanoparticle Tracking Analysis skill for single-particle size and concentration measurements
Laboratory Information Management System skill for nanomaterial sample tracking and data management
LabVIEW instrument control skill for DAQ systems, hardware integration, and real-time data acquisition
Measurement System Analysis skill for Gage R&R studies with variance component analysis.
Specialized skill for air pollution control equipment selection and design including scrubbers, baghouses, ESPs, oxidizers, and BACT/LAER determination.
Automated test equipment control and data acquisition skill for hardware validation, with VISA/SCPI instrument communication, test sequence scripting, and measurement uncertainty analysis.
Assist in constructing type soundness proofs using progress and preservation theorems
Supply chain master data quality monitoring and improvement skill
Sensor and robot calibration using specialized robotics calibration tools
Weights & Biases integration skill for experiment tracking, hyperparameter sweeps, and artifact versioning.
MLflow integration skill for experiment tracking, model registry, and artifact management. Enables LLMs to log experiments, compare runs, manage model lifecycle, and retrieve artifacts through the MLflow API.
Guide for experiment tracking tool setup (MLflow, Weights & Biases, etc.), reproducibility assurance, model registry, and experiment comparison methodology. Use this skill for ML experiment management involving 'experiment tracking', 'MLflow', 'W&B', 'Weights and Biases', 'reproducibility', 'model registry', 'experiment comparison', 'hyperparameter logging', etc. Enhances the training-manager's experiment management capabilities. Note: model architecture design and feature engineering are outside this skill's scope.
Methodology for analyzing changes according to Semantic Versioning (SemVer) rules and determining the appropriate version number. Use this skill for 'SemVer analysis', 'version number determination', 'Breaking Change assessment', 'version bump decisions', and other version management tasks. Note: automatic git tag creation and CI/CD release execution are outside the scope of this skill.
์ฝ๋๋ฒ ์ด์ค์ ์์กด์ฑ ๊ทธ๋ํ๋ฅผ ๋ถ์ํ๊ณ ๊ฒฐํฉ๋/์์ง๋๋ฅผ ์ ๋์ ์ผ๋ก ์ธก์ ํ๋ ๋๊ตฌ์ ๋ฐฉ๋ฒ๋ก . '์์กด์ฑ ๋ถ์', '๊ฒฐํฉ๋ ์ธก์ ', '์ํ ์์กด์ฑ', '๋ชจ๋ ๊ฒฐํฉ๋', '์์ง๋ ๋ถ์', '์์กด์ฑ ๊ทธ๋ํ', '์ปคํ๋ง ๋ถ์' ๋ฑ ์ฝ๋ ์์กด์ฑ ๊ด๋ จ ๋ถ์์ ์ด ์คํฌ์ ์ฌ์ฉํ๋ค. legacy-analyzer์ refactoring-strategist์ ์์กด์ฑ ๋ถ์ ์ญ๋์ ๊ฐํํ๋ค. ๋จ, ์ ์ฒด ํ์ดํ๋ผ์ธ ์ค์ผ์คํธ๋ ์ด์ ์ ์ด ์คํฌ์ ๋ฒ์๊ฐ ์๋๋ค.
MLflow, Weights & Biases ๋ฑ ์คํ ์ถ์ ๋๊ตฌ ์ค์ , ์ฌํ์ฑ ๋ณด์ฅ, ๋ชจ๋ธ ๋ ์ง์คํธ๋ฆฌ, ์คํ ๋น๊ต ๋ฐฉ๋ฒ๋ก ๊ฐ์ด๋. '์คํ ์ถ์ ', 'MLflow', 'W&B', 'Weights and Biases', '์ฌํ์ฑ', '๋ชจ๋ธ ๋ ์ง์คํธ๋ฆฌ', '์คํ ๋น๊ต', 'ํ์ดํผํ๋ผ๋ฏธํฐ ๋ก๊น ' ๋ฑ ML ์คํ ๊ด๋ฆฌ ์ ์ด ์คํฌ์ ์ฌ์ฉํ๋ค. training-manager์ ์คํ ๊ด๋ฆฌ ์ญ๋์ ๊ฐํํ๋ค. ๋จ, ๋ชจ๋ธ ์ํคํ ์ฒ ์ค๊ณ๋ ํผ์ฒ ์์ง๋์ด๋ง์ ์ด ์คํฌ์ ๋ฒ์๊ฐ ์๋๋ค.
