algorithms-complexity-guide
Analyze algorithm complexity and computational efficiency for research
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill algorithms-complexity-guide --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.
# Algorithms and Complexity Guide A skill for analyzing algorithm complexity and computational efficiency in research contexts. Covers asymptotic notation, common complexity classes, NP-completeness, amortized analysis, and strategies for presenting algorithmic contributions in papers. ## Asymptotic Notation ### Big-O, Omega, and Theta ``` O(f(n)) -- Upper bound (worst case, "at most") T(n) is O(f
What does the algorithms-complexity-guide skill do?
Analyze algorithm complexity and computational efficiency for research
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill algorithms-complexity-guide --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.