sigir-experiments
Use when designing or auditing the empirical program of a SIGIR paper — choosing test collections that match the claim, metric-cutoff discipline, paired significance testing with multiple-comparison correction, baseline tuning symmetry, ablations that isolate mechanisms, efficiency reporting, and LLM-era evaluation pitfalls.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-experiments --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.
# SIGIR Experiments SIGIR inherits its experimental culture from the Cranfield/TREC tradition: shared test collections, pooled relevance judgments, and statistical comparison of systems. Reviewers audit the *protocol* before they admire the numbers. This skill designs an evidence program that survives that audit — and flags the LLM-era failure modes that current program committees have learned to
What does the sigir-experiments skill do?
Use when designing or auditing the empirical program of a SIGIR paper — choosing test collections that match the claim, metric-cutoff discipline, paired significance testing with multiple-comparison correction, baseline tuning symmetry, ablations that isolate mechanisms, efficiency reporting, and LLM-era evaluation pitfalls.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigir-experiments --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/Awesome-Journal-Skills, a repository with 909 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.