osdi-experiments
Use when designing or auditing the evaluation of an OSDI submission — choosing mature baselines and realistic workloads, structuring the section around research questions, measuring scalability and tail behavior, quantifying the design's costs, and fitting the evidence into the 12-page reviewed body.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill osdi-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.
# OSDI Experiments Design the evaluation as the paper's proof obligation. The page constraints referenced here are OSDI '26 rules (12 reviewed pages, no appendices at submission — verified 2026-07-08); the evidence standards are the durable expectations of systems PCs. ## Research questions first Write the evaluation's research questions before running anything, and derive the experiment set from them. Every OSDI evaluation ultimately answers versions of: 1. **Does the idea work end to end?** — the headline comparison on a realistic workload against the strongest baseline. 2. **Where does the benefit come from?** — component breakdown attributing the win to the named design idea rather than to incidental engineering. 3. **What does it cost?** — the overheads the design admits (memory, write amplification, CPU, complexity), measured, not estimated. 4. **When does it break?** — scalability limits, adversarial workloads, failure and recovery behavior. An evaluation organized as RQ1–RQ4 with one experiment cluster each reads as an argument; a tour of every benchmark you happened to run reads as padding, which the OSDI '26 CFP explicitly invites reviewers to down-rank. ## Baselines that
- Research questions first
- Baselines that fight back
- Workload realism
- Measurement discipline
- Fitting evidence into 12 pages
- Reporting grid
- Review-time exposure
- Output format
What does the osdi-experiments skill do?
Use when designing or auditing the evaluation of an OSDI submission — choosing mature baselines and realistic workloads, structuring the section around research questions, measuring scalability and tail behavior, quantifying the design's costs, and fitting the evidence into the 12-page reviewed body.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill osdi-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.