RuView Advanced Sensing
ruvnet/RuView
Reference for RuView's research-grade WiFi sensing features: multistatic fusion, cross-viewpoint geometry, persistent field models, RF tomography, intention signals and mesh security.
A skill your agent uses when designing or auditing the evaluation of an IEEE S&P (Oakland) paper, including end-to-end attack demonstration, adaptive-adversary evaluation of defenses, measurement…
Install Ieeesp Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ieeesp-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ieeesp-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/IEEE-SP-Skills/skills/ieeesp-experiments .claude/skills/ieeesp-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 "ieeesp-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IEEE-SP-Skills/skills/ieeesp-experiments into .claude/skills/ieeesp-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ieeesp-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/IEEE-SP-Skills/skills/ieeesp-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 ieeesp-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ieeesp-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/IEEE-SP-Skills/skills/ieeesp-experiments .agents/skills/ieeesp-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 "ieeesp-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IEEE-SP-Skills/skills/ieeesp-experiments into .agents/skills/ieeesp-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ieeesp-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 ieeesp-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ieeesp-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/IEEE-SP-Skills/skills/ieeesp-experiments .cursor/skills/ieeesp-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 "ieeesp-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IEEE-SP-Skills/skills/ieeesp-experiments into .cursor/skills/ieeesp-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ieeesp-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 IEEE-SP-Skills/skills/ieeesp-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 ieeesp-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills ieeesp-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/IEEE-SP-Skills/skills/ieeesp-experiments .gemini/skills/ieeesp-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 "ieeesp-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IEEE-SP-Skills/skills/ieeesp-experiments into .gemini/skills/ieeesp-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ieeesp-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 ieeesp-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 ieeesp-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/IEEE-SP-Skills/skills/ieeesp-experiments .github/skills/ieeesp-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 "ieeesp-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IEEE-SP-Skills/skills/ieeesp-experiments into .github/skills/ieeesp-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ieeesp-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 ieeesp-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 ieeesp-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/IEEE-SP-Skills/skills/ieeesp-experiments .opencode/skills/ieeesp-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 "ieeesp-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/IEEE-SP-Skills/skills/ieeesp-experiments into .opencode/skills/ieeesp-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ieeesp-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
ieeesp-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 467 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 IEEE S&P (Oakland) paper, including end-to-end attack demonstration, adaptive-adversary evaluation of defenses, measurement…
- Auditing the evaluation of an IEEE S&P (Oakland) paper
- SKILL.md covers Match the evaluation to the…, The adaptive-adversary rule…, Measurement validity is an… and Statistics for attacks and…, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Including end-to-end attack demonstration
What it does
Ieeesp Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of an IEEE S&P (Oakland) paper, including end-to-end attack demonstration, adaptive-adversary evaluation of defenses, measurement sampling and validity, baselines and ablations, statistical reporting of attack success, and the ethics constraints that shape what experiments are permissible.
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. 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 IEEE S&P (Oakland) paper
- Including end-to-end attack demonstration
- Adaptive-adversary evaluation of defenses
- Measurement sampling and validity
Example prompts
- “/ieeesp-experiments”
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
Ieeesp Experiments loads about 1.3k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 467 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). 467 words, ~1,299 tokens.
Download SKILL.mdSave it as
.claude/skills/ieeesp-experiments/SKILL.md (or your agent's skills folder).- name
- ieeesp-experiments
- description
- Use when designing or auditing the evaluation of an IEEE S&P (Oakland) paper, including end-to-end attack demonstration, adaptive-adversary evaluation of defenses, measurement sampling and validity, baselines and ablations, statistical reporting of attack success, and the ethics constraints that shape what experiments are permissible.
IEEE S&P Experiments
Use this to build or audit the evidence an S&P paper stands on. The venue's reviewers are professional adversaries; an evaluation that would satisfy a systems or ML PC often leaves an Oakland reviewer's central question — "does this survive a real, adaptive attacker?" — unanswered.
Match the evaluation to the contribution type
| Contribution | Evaluation that closes the loop | Fatal gap |
|---|---|---|
| Attack | End-to-end demonstration against a realistic, current target | Toy target; unrealistic preconditions |
| Defense | Adaptive adversary who knows the design; cost/overhead | Only non-adaptive or prior attacks |
| Measurement | Representative sampling + validation + ethics | Convenience sample presented as population |
| System | Security property demonstrated and performance | Property asserted, not tested |
| SoK | Systematic re-analysis under one framework | Cherry-picked coverage |
The adaptive-adversary rule dominates defense papers
A defense evaluated only against existing or non-adaptive attacks is the most common S&P defense rejection. The standard:
- Define the adaptive adversary explicitly: knows the mechanism, the parameters, and the deployment.
- Show your defense against attacks designed to break it, not just yesterday's attacks it happens to stop.
- Report the cost of adaptation for the attacker and the overhead for the defender — both are part of the security claim.
- If a class of adaptive attack is out of scope, say so in the threat model and own the boundary; do not leave it for a reviewer to discover.
Measurement validity is an evidence question and an ethics question
For measurement papers, the sampling story and the ethics story are the same paragraph in reviewers' minds:
- State the population, the frame, and the sampling method; quantify coverage and bias.
- Validate a subsample by an independent method where possible.
- Active measurement (scanning, probing) must respect opt-out norms, rate
limits, and the ethics record (
ieeesp-review-process) — an experiment that harms the systems it measures is a reject regardless of results. - Human-subjects components need IRB determination before running, not a post-hoc note.
Show full SKILL.md (159 more words)Show less
Statistics for attacks and fuzzing
Security evidence is often probabilistic and gets held to a real bar:
Attack-success reporting:
n trials (state n) · success rate ± dispersion · target set described
→ "worked" without n is an anecdote, not a result
Fuzzing / bug-finding comparison (the field's known pitfalls):
- equal budgets (CPU-time, not wall-clock)
- ≥ 5–10 campaigns per configuration; report variance
- identical seed corpora across compared tools
- a ground-truth or triage method for "unique" bugs
→ a single-run bug count comparison is not evidence of superiority
Timing / side-channel:
noise floor stated · machine quiescence (isolated cores, freq pinning)
· distinguisher's statistical test namedBaselines and ablations Oakland reviewers ask for
- The strongest prior attack/defense, at its best configuration, not a weakened reimplementation.
- An ablation isolating the component you claim is responsible for the security gain.
- A cost baseline: what does the attacker/defender spend, and is it realistic at the claimed scale?
- Negative results where they bound the claim (attack fails against target class Y — state it; it strengthens the scoped claim).
Ethics as an experimental design constraint, not an afterthought
Some experiments are simply not runnable as first imagined:
- Testing an exploit against live third-party systems without authorization is out; build a representative testbed instead.
- Collecting user data beyond what the IRB and the ethics record cover is out.
- Disclosure timing constrains when certain measurements can be published
— design the timeline so the evidence and the fix do not collide
(
ieeesp-reproducibility).
Audit worksheet
For each experiment:
claim it supports | contribution type | adaptive adversary evaluated? |
strongest baseline used? | n trials + dispersion | ethics clearance |
realistic target? | rerunnable? (→ ieeesp-reproducibility)
Flag any row with: non-adaptive-only defense · anecdotal success rate ·
weakened baseline · unmet ethics preconditionOutput format
[Contribution type] attack / defense / measurement / system / SoK
[Loop closed?] <the demonstration/eval that proves the claim> ✓/✗
[Adaptive adversary] evaluated ✓/✗/n-a — scope stated?
[Baselines] strongest prior used ✓/✗ · ablation ✓/✗ · cost baseline ✓/✗
[Statistics] trials+dispersion ✓/✗ · fuzzing pitfalls avoided ✓/✗/n-a
[Ethics preconditions] IRB ✓/✗/n-a · authorization ✓/✗ · disclosure timing ok ✓/✗© 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 IEEE-SP-Skills/skills/ieeesp-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Ieeesp 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 |
|---|---|---|---|---|---|---|
| Ieeesp Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| RuView Advanced Sensingruvnet/RuView | 97k | — | ~1.2k | Automated safety check: Notes | MIT | |
| Intelligence Collection MethodologyRightNow-AI/openfang | 18k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Interceptor ResearchHacker-Valley-Media/Interceptor | 519 | — | ~3.8k | Automated safety check: Pass | Custom licence | |
| Nemo GuardrailsOrchestra-Research/AI-Research-SKILLs | 13k | 2 repos | ~1.9k | Automated safety check: Warn | MIT | |
| Bio Atac Seq FootprintingGPTomics/bioSkills | 1.2k | 2 repos | ~4.8k | Automated safety check: Pass | MIT |
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Interceptor Research
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Deep web-research methodology for the interceptor browser surface — investigate a topic the way researchers, intelligence analysts, investigative journalists, private investigators, and OSINT…
Nemo Guardrails
Orchestra-Research/AI-Research-SKILLs
NVIDIA's runtime safety framework for LLM applications. An agent skill from Orchestra-Research/AI-Research-SKILLs.
Bio Atac Seq Footprinting
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Detect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter.
Network And Distributed System Security Symposium
franklee16/academic-research-skills
A skill your agent uses when targeting Network and Distributed System Security Symposium (NDSS) or deciding whether a computer-science manuscript fits this venue.
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Categories
Questions about Ieeesp Experiments
What does Ieeesp Experiments do?
A skill your agent uses when designing or auditing the evaluation of an IEEE S&P (Oakland) paper, including end-to-end attack demonstration, adaptive-adversary evaluation of defenses, measurement…. Ieeesp Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of an IEEE S&P (Oakland) paper, including end-to-end attack demonstration, adaptive-adversary evaluation of defenses, measurement sampling and validity, baselines and ablations, statistical reporting of attack success, and the ethics constraints that shape what experiments are permissible.
When should I use Ieeesp Experiments?
Ieeesp Experiments fits situations like: auditing the evaluation of an IEEE S&P (Oakland) paper; including end-to-end attack demonstration; adaptive-adversary evaluation of defenses; measurement sampling and validity.
How do I install Ieeesp Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ieeesp-experiments -a claude-code`. Or copy the skill folder (IEEE-SP-Skills/skills/ieeesp-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/ieeesp-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Ieeesp Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill ieeesp-experiments -a codex`. Or copy the skill folder (IEEE-SP-Skills/skills/ieeesp-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/ieeesp-experiments in your project. Codex loads it when a task matches its description.
Can I use Ieeesp 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 ieeesp-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/ieeesp-experiments, .gemini/skills/ieeesp-experiments, .github/skills/ieeesp-experiments and .opencode/skills/ieeesp-experiments in your project.
What does Ieeesp Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Ieeesp Experiments is instructions for the agent only.
Does Ieeesp 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 Ieeesp 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 Ieeesp Experiments use?
Ieeesp 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 Ieeesp Experiments use?
About 1.3k tokens (SKILL.md is roughly 5.2k 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 Ieeesp Experiments?
Skills that share tags, products or a category with Ieeesp Experiments: RuView Advanced Sensing (ruvnet/RuView, 97k stars), Intelligence Collection Methodology (RightNow-AI/openfang, 18k stars), Interceptor Research (Hacker-Valley-Media/Interceptor, 519 stars) and Nemo Guardrails (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ieeesp Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 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.