sigcomm-reproducibility
Use when strengthening the reproducibility evidence of an ACM SIGCOMM paper — topology and testbed ledgers, traffic workload and trace provenance, configuration and version pinning, tail-percentile run counts and variance, legal data-release decisions, and consistency between the paper's claims and the artifact that backs them.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-reproducibility --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.
# SIGCOMM Reproducibility Use this before submission and again before the artifact deadline. SIGCOMM's culture treats a result as a claim a stranger should be able to rebuild; reproducibility here is largely about whether the **network conditions** behind a number are recorded well enough to recreate. Reopen the current Call for Artifacts to confirm the process for this edition. ## Evidence map - Map each reported number to a rebuildable location: a script, a logged run, a config, and the figure it feeds. - For every measurement, record the **topology** (physical or emulated), the **traffic** (workload generator or trace, with provenance), the **configuration** (every parameter), and the **environment** (kernel, NIC, switch firmware, data-plane toolchain). - For any stochastic result, report the **run count**, the seed or workload driver, and the variance behind each percentile — a lone 99th-percentile number with no replication is not reproducible. - Decide early what can legally ship: production traces and topologies often cannot, so plan a substitute with matching statistical character rather than discovering the block at the deadline. - Keep the paper and the artifact consisten
- Evidence map
- The four ledgers
- Degrees of reproducibility
- Vignette: a wide-area measurement result
- Legal and ethical release
- Output format
What does the sigcomm-reproducibility skill do?
Use when strengthening the reproducibility evidence of an ACM SIGCOMM paper — topology and testbed ledgers, traffic workload and trace provenance, configuration and version pinning, tail-percentile run counts and variance, legal data-release decisions, and consistency between the paper's claims and the artifact that backs them.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill sigcomm-reproducibility --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.