ijoc-methods
Use when the method choice, baselines, and computational-experiment design need alignment for an INFORMS Journal on Computing (IJOC) manuscript — before the experiments are run at scale. Designs a fair, reproducible experimental protocol; it does not write the algorithm proofs (see ijoc-theory-development).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ijoc-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.
# Method & Experimental Design (ijoc-methods) ## When to trigger - The algorithm is settled but the **experimental protocol** (instances, baselines, tuning, hardware, metrics) is not designed - You are about to run experiments and want to avoid a protocol a referee will reject after the fact - A referee challenges the **fairness** of a comparison (asymmetric tuning, mismatched time limits, weak baseline) - You must choose **what to measure** so the computational claim is actually supported ## Designing an IJOC-grade computational experiment At IJOC the experiment *is* the evidence, so it is held to a high methodological standard. Design it before running it, around five pillars. Getting these right up front is cheaper than re-running after an R&R. 1. **Instances.** Use **public, standard benchmark sets** wherever they exist (e.g., MIPLIB-class libraries, TSPLIB-style, established generators) so results are comparable and not cherry-picked. If you must generate instances, document the generator, the parameter ranges, and the seeds, and deposit them. Report the size distribution; do not test only on the sizes where you win. 2. **Baselines.** Compare against the **strongest available*
- When to trigger
- Designing an IJOC-grade computational experiment
- Method choice should follow the structure, not fashion
- Common protocol traps by archetype
- Reproducibility is part of the method
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Output format
What does the ijoc-methods skill do?
Use when the method choice, baselines, and computational-experiment design need alignment for an INFORMS Journal on Computing (IJOC) manuscript — before the experiments are run at scale. Designs a fair, reproducible experimental protocol; it does not write the algorithm proofs (see ijoc-theory-development).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ijoc-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.