claude-lab
claude-lab contains 8 collected skills from Butanium, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Write up research experiments and findings as an interactive, self-contained HTML report published as a claude.ai Artifact, with figures and data exploration. Use when creating a research report from experiment results.
How to write a comprehensive research report for your supervisor summarizing experiment findings, hypothesis tests, and data exploration. Use when you need to communicate results from multiple experiments with proper analysis, visualizations, and interactive data exploration.
How to send notifications to the human supervisor via ntfy.sh. Use when you need input, hit a blocker, or update them on your progress.
Cost and latency optimization for Anthropic API usage. Covers prompt caching, batch API, and when to combine them.
Standard experiment folder structure and templates. Reference for creating or validating experiment folders.
Read model outputs, samples, or log entries by eye and report specific observations about what's in them. Use when asked for a "qualitative" read/analysis, or when the goal is to understand WHAT is in the data rather than count patterns. Not for numerical summaries, metric computation, or classifier-driven sweeps.
How to evaluate research samples using structured JSON output from claude -p. Covers criteria writing, the core judging pattern, and practical examples.
Core research principles for hypothesis-driven investigation. Shared across orchestrator, scientists, and colleagues.