experiment-pipeline
Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments
npx skills add BioTender-max/awesome-bio-agent-skills --skill experiment-pipeline --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 Pipeline A structured 4-stage framework for executing research experiments from initial implementation through ablation study, with attempt budgets and gate conditions that prevent wasted effort. This follows the Experiment Tree Search design from the EvoScientist paper, where the engineer agent iteratively generates executable code, runs experiments, and records structured execution results at each stage. ## When to Use This Skill - User has a planned experiment and needs to organize the execution workflow - User wants to systematically validate a novel method against baselines - User asks about experiment stages, attempt budgets, or when to move on - User needs to reproduce baseline results before testing their method - User mentions "experiment pipeline", "baseline first", "ablation study", "stage budget", "experiment execution" ## The Pipeline Mindset **Experiments fail for two reasons: wrong order and no stopping criteria.** Most researchers jump straight to testing their novel method without verifying their baseline setup, then wonder why results don't make sense. Others spend weeks tuning hyperparameters without a budget, hoping the next run will work. The 4-sta
- When to Use This Skill
- The Pipeline Mindset
- Before Starting: Load Prior Knowledge
- 4-Stage Pipeline Overview
- The Stage Loop
- Stage 1: Initial Implementation
- Stage 2: Hyperparameter Tuning
- Stage 3: Proposed Method
- Stage 4: Ablation Study
- Integrating experiment-craft for Diagnosis
- Code Trajectory Logging
- Counterintuitive Pipeline Rules
- Handoff to Paper Writing
- Skill Integration
What does the experiment-pipeline skill do?
Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill experiment-pipeline --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.