Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
A skill your agent uses when making an NDSS paper's results reconstructible — snapshotting live-network observations, pinning testbeds and toolchains, scrubbing traces that carry identities, and…
Install Ndss Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-reproducibility --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/NDSS-Skills/skills/ndss-reproducibility .claude/skills/ndss-reproducibility && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ndss-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-reproducibility into .claude/skills/ndss-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-reproducibility", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-reproducibilityType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-reproducibility --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/NDSS-Skills/skills/ndss-reproducibility .agents/skills/ndss-reproducibility && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ndss-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-reproducibility into .agents/skills/ndss-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-reproducibility", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-reproducibility --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/NDSS-Skills/skills/ndss-reproducibility .cursor/skills/ndss-reproducibility && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ndss-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-reproducibility into .cursor/skills/ndss-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-reproducibility", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path NDSS-Skills/skills/ndss-reproducibility--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-reproducibility --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/NDSS-Skills/skills/ndss-reproducibility .gemini/skills/ndss-reproducibility && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ndss-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-reproducibility into .gemini/skills/ndss-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-reproducibility", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-reproducibilityInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/NDSS-Skills/skills/ndss-reproducibility .github/skills/ndss-reproducibility && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ndss-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-reproducibility into .github/skills/ndss-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-reproducibility", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-reproducibility --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/NDSS-Skills/skills/ndss-reproducibility .opencode/skills/ndss-reproducibility && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ndss-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-reproducibility into .opencode/skills/ndss-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-reproducibility", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ndss-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 534 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when making an NDSS paper's results reconstructible — snapshotting live-network observations, pinning testbeds and toolchains, scrubbing traces that carry identities, and…
- Works in 2 steps: Reconstruction — anyone can re-derive… → Re-execution — anyone can re-run your…
- Making an NDSS papers results reconstructible — snapshotting live-network observations
- SKILL.md covers Freezing the measured world, Traces are radioactive, The claims ledger and Honest availability statements, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Ndss Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when making an NDSS paper's results reconstructible — snapshotting live-network observations, pinning testbeds and toolchains, scrubbing traces that carry identities, and writing honest availability statements when ethics or vendor embargoes limit release.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Reproducible research. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Making an NDSS papers results reconstructible — snapshotting live-network observations
- Pinning testbeds and toolchains
- Scrubbing traces that carry identities
- Writing honest availability statements when ethics
Example prompts
- “/ndss-reproducibility”
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Reconstruction — anyone can re-derive your numbers from what you recorded.
- Re-execution — anyone can re-run your pipeline against the world and get their
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Ndss Reproducibility loads about 1.3k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 534 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 534 words, ~1,280 tokens.
Download SKILL.mdSave it as
.claude/skills/ndss-reproducibility/SKILL.md (or your agent's skills folder).- name
- ndss-reproducibility
- description
- Use when making an NDSS paper's results reconstructible — snapshotting live-network observations, pinning testbeds and toolchains, scrubbing traces that carry identities, and writing honest availability statements when ethics or vendor embargoes limit release.
NDSS Reproducibility
Network-security results decay: targets patch, providers change behavior, botnets die, and the population you measured in August is not the population of next March. Reproducibility at NDSS therefore means two different promises, and conflating them is the classic mistake:
- Reconstruction — anyone can re-derive your numbers from what you recorded.
- Re-execution — anyone can re-run your pipeline against the world and get their numbers, understanding why they differ from yours.
Promise (1) unconditionally. Promise (2) only where the world cooperates.
Freezing the measured world
| Volatile thing | What to freeze at experiment time |
|---|---|
| Scanned population | Input list + source + retrieval date; per-target response snapshots |
| Target software | Exact versions, build hashes, config files; patch level on the test date |
| Network path | Vantage descriptions, traceroute-level context where relevant, ASN of probes |
| Testbed | Topology file, firmware images (or their hashes), kernel/NIC settings |
| Toolchain | Container image or lockfile for every analysis script; seeds for anything sampled |
| Third-party feeds | Copies (or hashes + dates) of blocklists, zone files, certificate logs used |
The snapshot habit converts "trust us, it was exploitable in July 2026" into an auditable record — which is also what the rebuttal will need when a reviewer asks whether the fix released in September invalidates the paper.
Traces are radioactive
Packet captures, flow logs, DNS transcripts, and crawl outputs embed user identities, internal hostnames, and your institution's fingerprints — an anonymity leak against double-blind review and a privacy harm on release. Rules that hold up:
- Scrub at capture time, not release time; a raw pcap on a laptop is a liability, not an asset.
- Prefix-preserving IP anonymization where analysis needs structure; deletion where it does not. Document which was applied — reviewers of measurement work will check.
- Replace real victim traffic with regenerated synthetic equivalents whenever the result tolerates it, and say so.
- Grep every release candidate for institutional domains, usernames, and cloud-account identifiers before it leaves the repo.
Show full SKILL.md (222 more words)Show less
The claims ledger
Maintain, from the first experiment, a machine-checkable mapping between paper claims and regeneration paths:
# claims.yml — one entry per number/figure the paper depends on
fig4_takeover_success:
claim: "takeover succeeds against configs A-C"
inputs: [snapshots/2026-07-scan/, configs/targets.yml]
command: "make fig4" # runs inside container ndss-artifact:v3
runtime: "35 min, no network" # replays recorded traces
status: verified 2026-07-05
prevalence_table2:
claim: "condition present in N/M sampled domains"
inputs: [snapshots/2026-06-population.csv.gz]
command: "make table2"
status: verified 2026-07-02If a claim has no entry, either add the pipeline or soften the claim. The ledger later
becomes the artifact-evaluation appendix almost verbatim (see ndss-artifact-evaluation).
Honest availability statements
Some NDSS work legitimately cannot release everything: unpatched-exploit details under embargo, traces that cannot be de-identified, vendor NDAs. The venue's culture accepts limits that are named and mitigated, not gestured at:
- State precisely what is withheld, why, and until when (e.g., "exploit module released after the coordinated-disclosure window closes").
- Ship the largest safe substitute: redacted configs, synthetic traces with matched statistics, the analysis code even when the data stays private.
- Never write "code available upon request" as the entire plan — at this venue it reads as "not available".
Because NDSS proceedings are open access (Internet Society model, no paywall), your artifact link and the paper will be read together by the whole community; the availability statement is a public commitment, not review-stage decoration.
Cheap habits that pay at rebuttal time
- Date-stamp every scan directory; the timeline question always comes.
- Re-run the full pipeline from clean checkout monthly during the project — drift found early is drift fixed cheaply.
- Keep one
LIMITS.mdrecording every known non-determinism (timing-sensitive exploits, load-dependent measurements) and how the paper's statistics absorb it.
Output format
[Reconstruction status] claims with regeneration paths: N/M; missing listed
[World snapshot] frozen / partial / absent per volatile category
[Trace hygiene] scrub method, leak grep result, synthetic substitutions
[Availability statement] withheld items + reason + mitigation + release date
[Drift check] last clean-checkout rerun date and result© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in NDSS-Skills/skills/ndss-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ndss Reproducibility next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Ndss Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT | |
| CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw | 617 | 1 repos | ~1.8k | Automated safety check: Pass | None | |
| Compute Environment Setupaipoch/open-science | 5.5k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Figure Styleaipoch/open-science | 5.5k | — | ~5.1k | Automated safety check: Pass | Apache-2.0 | |
| Add Bactopia Toolbactopia/bactopia | 522 | — | ~4.1k | Automated safety check: Pass | MIT |
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CHARLS Paper Reproduction Guide
xjtulyc/MedgeClaw
Guides an agent through reproducing papers built on the CHARLS health and retirement survey, from variable mapping to cognition, depression and isolation scores.
Compute Environment Setup
aipoch/open-science
Prepares setup instructions and a named activation file for a user-managed software environment on an Open-Science SSH or Slurm compute host.
Figure Style
aipoch/open-science
Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots.
Add Bactopia Tool
bactopia/bactopia
Scaffold a complete Bactopia Tool across all three tiers -- module, subworkflow, and workflow entry point under workflows/bactopia-tools/.
Modeling Code and Result Contracts
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Generates result-evidence contracts, tables and runnable q1 to q3 modeling code scaffolds for a math modeling paper from a model route, a data plan and cleaned data.
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Related
Categories
Questions about Ndss Reproducibility
What does Ndss Reproducibility do?
A skill your agent uses when making an NDSS paper's results reconstructible — snapshotting live-network observations, pinning testbeds and toolchains, scrubbing traces that carry identities, and…. Ndss Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when making an NDSS paper's results reconstructible — snapshotting live-network observations, pinning testbeds and toolchains, scrubbing traces that carry identities, and writing honest availability statements when ethics or vendor embargoes limit release.
When should I use Ndss Reproducibility?
Ndss Reproducibility fits situations like: making an NDSS papers results reconstructible — snapshotting live-network observations; pinning testbeds and toolchains; scrubbing traces that carry identities; writing honest availability statements when ethics.
How do I install Ndss Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a claude-code`. Or copy the skill folder (NDSS-Skills/skills/ndss-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ndss-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Ndss Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a codex`. Or copy the skill folder (NDSS-Skills/skills/ndss-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ndss-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Ndss Reproducibility in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-reproducibility -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ndss-reproducibility, .gemini/skills/ndss-reproducibility, .github/skills/ndss-reproducibility and .opencode/skills/ndss-reproducibility in your project.
What does Ndss Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Ndss Reproducibility is instructions for the agent only.
Does Ndss Reproducibility access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Ndss Reproducibility safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Ndss Reproducibility use?
Ndss Reproducibility is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Ndss Reproducibility use?
About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Ndss Reproducibility?
Skills that share tags, products or a category with Ndss Reproducibility: Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Compute Environment Setup (aipoch/open-science, 5.5k stars) and Figure Style (aipoch/open-science, 5.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ndss Reproducibility?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.