results-analysis
This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill results-analysis --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.
# Results Analysis Run **strict, evidence-first experimental analysis** for ML/AI research. Use this skill to produce a **strict analysis bundle**: - `analysis-report.md` - `stats-appendix.md` - `figure-catalog.md` - `figures/` Do **not** use this skill to draft a paper `Results` section or a full experiment wrap-up report. Those belong to `ml-paper-writing` or `results-report`. ## Core contract #
What does the results-analysis skill do?
This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on strict analysis bundles, not Results-section prose.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill results-analysis --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 brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 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.