Monitor CI
nrwl/nx
Monitor Nx Cloud CI pipeline and handle self-healing fixes. An agent skill from nrwl/nx.
A skill your agent uses when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing…
Install Ndss Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-experiments --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-experiments .claude/skills/ndss-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-experiments into .claude/skills/ndss-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-experiments", 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-experimentsType 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-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-experiments --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-experiments .agents/skills/ndss-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-experiments into .agents/skills/ndss-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-experiments", 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-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-experiments --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-experiments .cursor/skills/ndss-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-experiments into .cursor/skills/ndss-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-experiments", 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-experiments--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-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ndss-experiments --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-experiments .gemini/skills/ndss-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-experiments into .gemini/skills/ndss-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-experiments", 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-experimentsInstalls 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-experiments -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-experiments .github/skills/ndss-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-experiments into .github/skills/ndss-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-experiments", 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-experiments -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-experiments --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-experiments .opencode/skills/ndss-experiments && 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-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/NDSS-Skills/skills/ndss-experiments into .opencode/skills/ndss-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ndss-experiments", 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-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 590 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing…
- Works in 3 steps: Restate the defense as the constraint it… → Enumerate strategies that respect… → Implement the strongest of these, not…
- Auditing the evaluation of an NDSS paper — attack demonstrations
- SKILL.md covers Evidence by contribution type, Choosing the experimental…, The adaptive-adversary… and Measurement hygiene, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Ndss Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing between testbed, emulation, and live experiments and meeting NDSS's deployment-realism evidence bar.
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 DevOps & Cloud. 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
- Auditing the evaluation of an NDSS paper — attack demonstrations
- Defense evaluations under adaptive adversaries
- Internet measurements — choosing between testbed
- Live experiments and meeting NDSSs deployment-realism evidence bar
Example prompts
- “/ndss-experiments”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Restate the defense as the constraint it imposes on the adversary.
- Enumerate strategies that respect capabilities from the threat model but target the
- Implement the strongest of these, not the most convenient, and report where the defense
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.
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 Experiments loads about 1.3k tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 590 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). 590 words, ~1,336 tokens.
Download SKILL.mdSave it as
.claude/skills/ndss-experiments/SKILL.md (or your agent's skills folder).- name
- ndss-experiments
- description
- Use when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing between testbed, emulation, and live experiments and meeting NDSS's deployment-realism evidence bar.
NDSS Experiments
Evidence at NDSS answers one question: would this hold on the real network? Every design choice in the evaluation — target selection, vantage, scale, baseline — either supports that answer or advertises that you avoided it.
Evidence by contribution type
| You claim... | Reviewers require... | Weak substitute they will flag |
|---|---|---|
| A new attack | End-to-end demonstration on real implementations, named versions, measured preconditions and cost | PoC against a config you weakened |
| A prevalent condition | Defined population, sampling method, validated vulnerability test, false-positive analysis | Extrapolation from anecdotes |
| A defense | Security and utility: adaptive-adversary evaluation + overhead on realistic workloads | Blocking only the published attack |
| A detection system | Base-rate honest metrics on traffic resembling deployment, drift discussion | Accuracy on one stale benchmark |
| A protocol change | Interop and incremental-deployment story, behavior under partial adoption | "Assume everyone upgrades" |
Choosing the experimental substrate
Match the substrate to the claim, and say why in the paper:
- Live Internet — the only substrate for prevalence claims. Requires the ethics machinery (below) and a recorded snapshot: measurement results are time-indexed facts, so log the observation window, vantage points, and population source.
- Testbed / physical devices — for exploit reliability and defense overhead, where you need ground truth and repeatability. Pin firmware, kernel, and topology; a testbed nobody can reconstruct is an anecdote with racks.
- Emulation / simulation — legitimate for scale sweeps and what-if topologies after the mechanism is shown real elsewhere. A paper whose only evidence is simulated packets is, at this venue, a proposal.
Mixed designs are the norm: demonstrate on real systems, generalize on the testbed, sweep in emulation, and keep the chain of custody between the three explicit.
The adaptive-adversary requirement
For defenses, the reviewer's first move is to play attacker against your design. Do it first, in print:
- Restate the defense as the constraint it imposes on the adversary.
- Enumerate strategies that respect capabilities from the threat model but target the mechanism itself — evasion, mimicry, resource exhaustion, downgrade, oracle abuse.
- Implement the strongest of these, not the most convenient, and report where the defense bends. Cost asymmetry (defender cents vs. attacker weeks) is a legitimate result; silence about adaptation is not.
Show full SKILL.md (237 more words)Show less
Measurement hygiene
- One vantage point is a case study; state how many you used and what each can and cannot see (anycast, geo-blocking, and CDN behavior all bite here).
- Validate the classifier or vulnerability test against labeled ground truth and report both error directions — a scanner's false positives are the headline number's error bar.
- Repeat over time before claiming stability; the Internet's diurnal and patch-cycle rhythms confound single-shot scans.
Ethics as an experimental parameter
Live experiments are bounded by harm, and the CFP backs this with an Ethics Review Board. Design limits in from the start: rate caps and opt-out honoring for scans, no serving of real user traffic during interception experiments, synthetic victims wherever the demonstration allows, notification pipelines for anything you confirm exploitable, and IRB engagement where humans are observed — while remembering NDSS treats IRB sign-off as necessary context, not sufficient mitigation. Every one of these choices belongs in the paper's method text, not only in the ethics section.
Reporting discipline
For every headline number, the text or appendix must pin:
target set + versions + selection method
vantage(s) and observation window
trials, variance, and the aggregation rule
hardware/software of the measurement or attack host
configuration deltas from defaults (ideally: none, or justified)
the command or procedure that regenerates the number (→ artifact)Numbers that move between runs get intervals; comparisons against baselines get identical conditions or an explanation of why identity was impossible.
Failure modes this venue punishes
- Evaluating on the environment you developed on, and nowhere else.
- Baselines run with defaults while your system got tuning.
- Success rates without denominators; "up to X" as a summary statistic.
- Prevalence claims from a population chosen because it was scannable, described as if it were representative.
Output format
[Claim → evidence map] each headline claim + substrate + status
[Adaptive evaluation] strategies enumerated / strongest implemented / result
[Measurement validity] population, vantage, validation, error directions
[Ethics parameters] rate caps, synthetic victims, notification, IRB state
[Repro pinning] items from the reporting block still missing© 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-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ndss Experiments 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 Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Monitor CInrwl/nx | 29k | 6 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Terraform and OpenTofu Guideagentscope-ai/QwenPaw | 35k | 6 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Vercel Optimize Auditvercel-labs/agent-skills | 32k | 9 repos | ~4.3k | Automated safety check: Pass | None | |
| Openclaw Live Updateropenclaw/openclaw | 392k | — | ~3.7k | Automated safety check: Pass | MIT | |
| Analyze GitHub Action Logswithastro/astro | 63k | 1 repos | ~1.3k | Automated safety check: Pass | Custom licence |
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Maintain the canonical live OpenClaw main checkout, macOS LaunchAgent-managed Gateway, local macOS app, exact-head main CI, and recurring full release validation.
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Analyze recent GitHub Actions workflow runs to identify patterns, mistakes, and improvements.
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Questions about Ndss Experiments
What does Ndss Experiments do?
A skill your agent uses when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing…. Ndss Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of an NDSS paper — attack demonstrations, defense evaluations under adaptive adversaries, and Internet measurements — choosing between testbed, emulation, and live experiments and meeting NDSS's deployment-realism evidence bar.
When should I use Ndss Experiments?
Ndss Experiments fits situations like: auditing the evaluation of an NDSS paper — attack demonstrations; defense evaluations under adaptive adversaries; internet measurements — choosing between testbed; live experiments and meeting NDSSs deployment-realism evidence bar.
How do I install Ndss Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-experiments -a claude-code`. Or copy the skill folder (NDSS-Skills/skills/ndss-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ndss-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Ndss Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ndss-experiments -a codex`. Or copy the skill folder (NDSS-Skills/skills/ndss-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ndss-experiments in your project. Codex loads it when a task matches its description.
Can I use Ndss Experiments 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-experiments -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-experiments, .gemini/skills/ndss-experiments, .github/skills/ndss-experiments and .opencode/skills/ndss-experiments in your project.
What does Ndss Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Ndss Experiments is instructions for the agent only.
Does Ndss Experiments 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 Experiments 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 Experiments use?
Ndss Experiments 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 Experiments use?
About 1.3k tokens (SKILL.md is roughly 5.3k 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 Experiments?
Skills that share tags, products or a category with Ndss Experiments: Monitor CI (nrwl/nx, 29k stars), Terraform and OpenTofu Guide (agentscope-ai/QwenPaw, 35k stars), Vercel Optimize Audit (vercel-labs/agent-skills, 32k stars) and Openclaw Live Updater (openclaw/openclaw, 392k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ndss Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 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.