ors-methods
Use when designing the proof technique, algorithm, or simulation protocol for an Operations Research (OR) manuscript — choosing the right machinery (duality, dynamic programming, probabilistic coupling, convergence analysis, simulation output analysis) to actually establish the claimed results. Establishes the results; it does not state the model (ors-theory-development) or run the experiments (ors-data-analysis).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ors-methods --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.
# Proof & Algorithm Methodology (ors-methods) ## When to trigger - The model and claims exist (`ors-theory-development`) and now must be *proved* or *guaranteed*. - You need to pick a proof strategy or design an algorithm with provable guarantees. - A reviewer says "the proof of Theorem X has a gap" or "the rate is not established." ## Match the machinery to the result *Operations Research* is mathematically rigorous: the contribution lives or dies on the soundness and strength of the analysis. Pick technique by methodology: | Result you need | Typical machinery | |-----------------|-------------------| | Optimality / strong duality | LP/conic duality, KKT, polyhedral / total unimodularity, submodularity | | Approximation guarantee | LP/SDP rounding, primal-dual, greedy + submodular bounds | | Complexity / hardness | reductions (NP-hardness), oracle lower bounds | | Convergence & rate | monotonicity/Lyapunov, fixed-point/contraction, first-order analysis | | Steady-state / stability | Foster-Lyapunov, regenerative arguments, fluid/diffusion limits | | Stochastic comparison / bounds | coupling, stochastic dominance, martingale/concentration inequalities | | MDP / dynamic decisions |
- When to trigger
- Match the machinery to the result
- Algorithm design with guarantees
- Simulation methodology (when the analysis is empirical-stochastic)
- Proof hygiene OR reviewers expect
- Methodology pushback patterns and the OR fix
- Worked machinery walk-through (illustrative)
- Execution bridge (StatsPAI / Stata MCP)
- Anti-patterns
- Output format
What does the ors-methods skill do?
Use when designing the proof technique, algorithm, or simulation protocol for an Operations Research (OR) manuscript — choosing the right machinery (duality, dynamic programming, probabilistic coupling, convergence analysis, simulation output analysis) to actually establish the claimed results. Establishes the results; it does not state the model (ors-theory-development) or run the experiments (ors-data-analysis).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ors-methods --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.