experiment-craft
Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experi
npx skills add BioTender-max/awesome-bio-agent-skills --skill experiment-craft --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Experiment Craft A systematic approach to running, debugging, and iterating on research experiments. The critical skill is not running more experiments — it's understanding WHY experiments fail. ## When to Use This Skill - User's experiment is not working or producing unexpected results - User needs help diagnosing why a method fails on certain data - User wants to organize their experiment process with structured logging - User asks about debugging research code or iterating on approaches - User mentions "experiment debugging", "why doesn't this work", "experiment log", "results are wrong" > This skill is typically loaded from within `experiment-pipeline` when a stage attempt fails. After debugging, return to the pipeline's stage-gate structure to continue. Can also be used standalone for any experiment debugging. ## The Debugging Mindset **Finding WHY experiments fail is the most critical research skill.** Not analyzing results leads to two failure modes: 1. **Slow progress**: Running random experiments without understanding failure causes 2. **Wasted time**: Abandoning good approaches because activation tricks were missed The goal is not to run more experiments. The goal is to
- When to Use This Skill
- The Debugging Mindset
- 5-Step Diagnostic Flow
- Step 1: Collect Failure Cases
- Step 2: Find a Working Version
- Step 3: Bridge the Gap
- Step 4: Hypothesize and Verify
- Step 5: Propose and Implement a Fix
- Counterintuitive Experiment Rules
- Experiment Logging
- Return to experiment-pipeline
- Handoff to Paper Writing
- Reference Navigation
What does the experiment-craft skill do?
Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experi
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill experiment-craft --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.