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student-experiment-design

Design experiments with variables, baselines, ablations, resources, and success criteria.

Skill by LiXin97

IndexedApache-2.0★ 51
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Design experiments with variables, baselines, ablations, resources, and success criteria.

Use cases: design

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/student-experiment-design

What's inside

Skill name
student-experiment-design
Description
Design experiments with variables, baselines, ablations, resources, and success criteria.
License
Apache-2.0
Instructions
77 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Student Experiment Design

## Student-specific extensions

- Add the exact artifact path where the plan will be published.
- Add `Reviewer-facing risks` after `## Risks`.
- The plan is incomplete if it cannot tell a reviewer what outcome would falsify the idea.

## Purpose

Translate a research hypothesis into a concrete, executable experiment plan.

## Workflow

1. **State hypothesis**: What specific claim are you testing?
2. **Define variables**: Independent (what you change), dependent (what you measure), controlled (what stays fixed)
3. **Choose baselines**: What are you comparing against?
4. **Design protocol**: Steps to execute, datasets, evaluation metrics
5. **Resource estimation**: Compute, time, data requirements
6. **Publish**: Write to your canonical shared artifact directory: `{artifact_dir}/{your-name}/experiment_plan_{id}.md`

## Output Format

```markdown
# Experiment Plan: {title}

## Hypothesis
{Specific, testable claim}

## Variables
- **Independent**: What we vary (e.g., attention mechanism type)
- **Dependent**: What we measure (e.g., perplexity, latency)
- **Controlled**: What stays fixed (e.g., model size, dataset, training steps)

## Baselines
1. {Baseline method} — why it's relevant
2. ...

## Datasets
| Dataset | Size | Purpose | Source |
|---|---|---|---|

## Metrics
| Metric | Purpose | Expected Direction |
|---|---|---|

## Protocol
1. Step-by-step execution plan
2. ...

## Ablations
What variations to test:
1. ...

## Resource Estimate
- GPU hours: ...
- Storage: ...
- Expected runtime: ...

## Success Criteria
What results would support/refute the hypothesis.

## Risks
What could go wrong and mitigation strategies.

## Reviewer-facing risks
The objections a reviewer is most likely to raise and how the plan addresses them.
```

## Rules

- Every experiment must have at least one baseline comparison
- Always include ablation studies to isolate the contribution
- Fix random seeds and log all hyperparameters
- Plan for at least 3 runs with different seeds for statistical significance

From LiXin97/agora-lab, Apache-2.0.

Signals

Stars
51
Forks
8
Open issues
1
Last commit (this folder)
Apr 11, 2026 (7 months ago)
Last release
Apr 18, 2026 (6 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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student-experiment-design skill. Agent Mart. https://agentmart.dev/skills/lixin97-student-experiment-design (last updated 2026-10-24)