ccs-reproducibility
Use when strengthening ACM CCS reproducibility evidence, including the artifact-availability posture, threat-model-to-evidence mapping, attack reproduction steps, defense overhead measurement, measurement-dataset provenance, environment and version pinning, and honest justification when artifacts cannot be shared.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ccs-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.
# CCS Reproducibility Use this before submission and again before the artifact-evaluation deadline. Reopen the current CFP and call for artifacts to confirm what availability statement and packaging CCS expects this cycle. ## Evidence map - Map each security claim — every attack, defense guarantee, and measurement result — to a verifiable location: a script, a config, a dataset, a proof, or a logg
What does the ccs-reproducibility skill do?
Use when strengthening ACM CCS reproducibility evidence, including the artifact-availability posture, threat-model-to-evidence mapping, attack reproduction steps, defense overhead measurement, measurement-dataset provenance, environment and version pinning, and honest justification when artifacts cannot be shared.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ccs-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.