Statistical Experiment Evaluation
Designs and records statistical experiments that test research claims against baselines and theory.
- Repository
- aiming-lab/AutoResearchClaw
- Stars
- 14,802
- Licence
- MIT
- Files
- 1 file
What it does
When installed, the agent follows a structured process for testing a research idea with experiments. It plans the conditions, data, proposed method, baselines, ablations, metrics and failure counts, then writes results in fixed file formats (metrics, run manifest, comparison summary, claim verdicts and a paper draft). It is meant to be used after the theory and method have been worked out, so each result ties back to a specific claim.
Great for
- Researchers writing an academic paper who need a disciplined experiment plan and evidence records
- Students learning how to set up baselines, ablations and fair comparisons
- Teams working inside the AutoResearchClaw pipeline at the experiment stages
Skip it if
- Quick data analysis or exploratory charts, because the skill imposes a heavy artifact structure that adds overhead
- Non-research projects where no formal claims or theory need testing, since the rules assume a formulated claim
- Anyone expecting it to verify results automatically: it only describes what to record and does not check statistical validity
Try asking
- “Design an experiment plan comparing my proposed estimator against two standard baselines under heavy-tailed noise”
- “Set up ablations for my method and produce a claim_verdicts.json linking each claim to theory and results”
- “Write the metric rows and comparison summary for my simulation study, counting failed runs”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
statistical-experimental-evaluation.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip statistical-experimental-evaluation.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip statistical-experimental-evaluation.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- State your claims and theoretical predictions before running experiments so the verdicts are meaningful.
- Keep the same data conditions across all compared methods, as the evidence rules require.
- Ask the agent to record failed runs and runtime changes explicitly rather than omitting them.
What's inside
- SKILL.md
Redistributed unmodified from aiming-lab/AutoResearchClaw under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.