Extracting Windows Event Logs Artifacts
mukul975/Anthropic-Cybersecurity-Skills
Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.
Agent skill
Iclr Artifact Evaluation
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging ICLR code, data, checkpoints, demos, logs, and reproduction instructions for reviewers or post-acceptance release, including anonymized links and private…
MITAuto-check passed
Install Iclr Artifact Evaluation
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iclr-artifact-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills iclr-artifact-evaluation --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/ICLR-Skills/skills/iclr-artifact-evaluation .claude/skills/iclr-artifact-evaluation && 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 "iclr-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICLR-Skills/skills/iclr-artifact-evaluation into .claude/skills/iclr-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iclr-artifact-evaluation", 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/ICLR-Skills/skills/iclr-artifact-evaluationType 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 iclr-artifact-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills iclr-artifact-evaluation --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/ICLR-Skills/skills/iclr-artifact-evaluation .agents/skills/iclr-artifact-evaluation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "iclr-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICLR-Skills/skills/iclr-artifact-evaluation into .agents/skills/iclr-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iclr-artifact-evaluation", 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 iclr-artifact-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills iclr-artifact-evaluation --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/ICLR-Skills/skills/iclr-artifact-evaluation .cursor/skills/iclr-artifact-evaluation && 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 "iclr-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICLR-Skills/skills/iclr-artifact-evaluation into .cursor/skills/iclr-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iclr-artifact-evaluation", 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 ICLR-Skills/skills/iclr-artifact-evaluation--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 iclr-artifact-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills iclr-artifact-evaluation --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/ICLR-Skills/skills/iclr-artifact-evaluation .gemini/skills/iclr-artifact-evaluation && 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 "iclr-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICLR-Skills/skills/iclr-artifact-evaluation into .gemini/skills/iclr-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iclr-artifact-evaluation", 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 iclr-artifact-evaluationInstalls 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 iclr-artifact-evaluation -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/ICLR-Skills/skills/iclr-artifact-evaluation .github/skills/iclr-artifact-evaluation && 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 "iclr-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICLR-Skills/skills/iclr-artifact-evaluation into .github/skills/iclr-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iclr-artifact-evaluation", 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 iclr-artifact-evaluation -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 iclr-artifact-evaluation --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/ICLR-Skills/skills/iclr-artifact-evaluation .opencode/skills/iclr-artifact-evaluation && 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 "iclr-artifact-evaluation" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICLR-Skills/skills/iclr-artifact-evaluation into .opencode/skills/iclr-artifact-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "iclr-artifact-evaluation", 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
iclr-artifact-evaluation- GitHub stars
- 1.2k
- Token cost
- ~953 tokens
- SKILL.md length
- 423 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when packaging ICLR code, data, checkpoints, demos, logs, and reproduction instructions for reviewers or post-acceptance release, including anonymized links and private…
- Packaging ICLR code
- SKILL.md covers Artifact package, ICLR-specific handling, What reviewers actually open and Worked vignette, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Reproduction instructions for reviewers
What it does
Iclr Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging ICLR code, data, checkpoints, demos, logs, and reproduction instructions for reviewers or post-acceptance release, including anonymized links and private OpenReview discussion-period sharing. Use when a reviewer asks for a missing repro path, when a public comment questions whether claims can be verified, or when converting an anonymous supplement into a durable post-acceptance release for the permanent ICLR record.
Its SKILL.md is about 950 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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
- Packaging ICLR code
- Reproduction instructions for reviewers
- Post-acceptance release
- Including anonymized links and private OpenReview discussion-period sharing
Example prompts
- “/iclr-artifact-evaluation”
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
Iclr Artifact Evaluation loads about 953 tokens when it runs. Until then it costs about 116 tokens; SKILL.md has 423 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). 423 words, ~953 tokens.
Download SKILL.mdSave it as
.claude/skills/iclr-artifact-evaluation/SKILL.md (or your agent's skills folder).- name
- iclr-artifact-evaluation
- description
- Use when packaging ICLR code, data, checkpoints, demos, logs, and reproduction instructions for reviewers or post-acceptance release, including anonymized links and private OpenReview discussion-period sharing. Use when a reviewer asks for a missing repro path, when a public comment questions whether claims can be verified, or when converting an anonymous supplement into a durable post-acceptance release for the permanent ICLR record.
ICLR Artifact Evaluation
Use this to prepare artifacts that make an ICLR paper reproducible and reviewable. ICLR may not run a separate artifact-badge process for every paper, so the practical bar is whether reviewers and ACs can verify the claims without identity leakage or excessive setup.
Artifact package
- Provide a minimal reproduction path for every central table or figure: command, config, seed, expected runtime, hardware, and expected output file.
- Include data provenance, preprocessing scripts, licenses, and any access restrictions.
- Separate heavy checkpoints or datasets from the core anonymized supplement when file-size limits require it; document private reviewer links clearly.
- Remove usernames, organization names, cloud buckets, Git history, API keys, and metadata that can deanonymize authors.
- Add a smoke-test script that runs in minutes and confirms environment integrity.
- Mark any unreleasable component and give a defensible reason, not a vague "proprietary" note.
ICLR-specific handling
- Submit supplementary material by the paper deadline when the current Author Guide requires it.
- During discussion, use private links or revised supplements only within current OpenReview rules.
- If a demo is useful, make it anonymous and robust to reviewer traffic, and avoid analytics that identify visitors.
- After acceptance, replace anonymous links with durable public archives or project pages.
What reviewers actually open
ICLR reviewers sample the supplement under time pressure during an open discussion everyone can read later. Optimize for the first ten minutes.
| Reviewer signal | Strong artifact | Weak artifact |
|---|---|---|
| "Rerun the headline table?" | run_main.sh with seed, config, log | "See repo", no entry point |
| "Is this anonymous?" | Stripped remotes, no analytics | Demo that logs reviewer IPs |
| "Checkpoint matches paper?" | Hash-pinned weights + eval command | Unlabeled .pt files |
| "What is not covered?" | "Cannot release X, license Y" | Silent gaps read as hiding |
Show full SKILL.md (140 more words)Show less
Worked vignette
A submission proposes a self-supervised contrastive objective for graph encoders and ships a 9 GB
checkpoint but no eval command. A public review asks how to reproduce Table 2 without retraining.
The fix: add eval_table2.sh that loads the checkpoint, runs the frozen-encoder probe, prints the
exact numbers, pin the checkpoint hash, and note in the thread that it runs in minutes on one GPU.
The clean path stays public forever and reassures every later reader of the accepted paper.
Reviewer-pushback patterns
- "Anonymous link is dead." Host static files in the OpenReview supplement ZIP, not an external service that can expire mid-discussion.
- "Smoke test passes but the real run does not." Ship a longer reference log so reviewers can diff intermediate values, not only final scores.
- "Proprietary, cannot share." Replace the vague label with a synthetic-data substitute.
Output format
[Artifact status] complete / partial / risky / unavailable
[Reviewer path] <fastest route to reproduce main claim>
[Anonymity risks] <metadata, links, logs, demos>
[Release plan] anonymous review / post-acceptance public / cannot release
[Missing evidence] <commands, seeds, data, checkpoints, licenses>© 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 ICLR-Skills/skills/iclr-artifact-evaluation of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Iclr Artifact Evaluation 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 |
|---|---|---|---|---|---|---|
| Iclr Artifact Evaluation this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~953 | Automated safety check: Pass | MIT | |
| Extracting Windows Event Logs Artifactsmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| Artifacts Buildernexu-io/open-design | 100k | — | ~347 | Automated safety check: Pass | Apache-2.0 | |
| Ccs Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~969 | Automated safety check: Pass | MIT | |
| Mobisys Artifact Evaluationbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1k | Automated safety check: Pass | MIT |
Similar skills
- Official
Arize Evaluator
github/awesome-copilot
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and…
Artifacts Builder
nexu-io/open-design
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui).
Ccs Artifact Evaluation
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging ACM CCS artifacts for the artifact-evaluation committee and the ACM badges — Artifacts Available, Artifacts Evaluated Functional, Artifacts Evaluated Reusable…
Mobisys Artifact Evaluation
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging a MobiSys artifact for the Artifact Evaluation Committee — choosing among the three independent ACM badges (Available, Evaluated–Functional, Results…
Fast Artifact Evaluation
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when packaging a USENIX FAST artifact for the USENIX Artifact Evaluation scheme (Artifacts Available, Artifacts Functional, Results Reproduced), covering what a storage AEC…
More from brycewang-stanford/Awesome-Journal-Skills
All 2,387 skills in this repoAaag Data Analysis
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…
Aaag Literature Positioning
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…
Aaag Rebuttal
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…
Aaag Research Design
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…
Aaag Review Process
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…
Aaag Submission
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…
Questions about Iclr Artifact Evaluation
What does Iclr Artifact Evaluation do?
A skill your agent uses when packaging ICLR code, data, checkpoints, demos, logs, and reproduction instructions for reviewers or post-acceptance release, including anonymized links and private…. Iclr Artifact Evaluation is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when packaging ICLR code, data, checkpoints, demos, logs, and reproduction instructions for reviewers or post-acceptance release, including anonymized links and private OpenReview discussion-period sharing.
When should I use Iclr Artifact Evaluation?
Iclr Artifact Evaluation fits situations like: packaging ICLR code; reproduction instructions for reviewers; post-acceptance release; including anonymized links and private OpenReview discussion-period sharing.
How do I install Iclr Artifact Evaluation in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iclr-artifact-evaluation -a claude-code`. Or copy the skill folder (ICLR-Skills/skills/iclr-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/iclr-artifact-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Iclr Artifact Evaluation in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iclr-artifact-evaluation -a codex`. Or copy the skill folder (ICLR-Skills/skills/iclr-artifact-evaluation in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/iclr-artifact-evaluation in your project. Codex loads it when a task matches its description.
Can I use Iclr Artifact Evaluation 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 iclr-artifact-evaluation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iclr-artifact-evaluation, .gemini/skills/iclr-artifact-evaluation, .github/skills/iclr-artifact-evaluation and .opencode/skills/iclr-artifact-evaluation in your project.
What does Iclr Artifact Evaluation need to run?
SKILL.md names no scripts, command-line tools or credentials: Iclr Artifact Evaluation is instructions for the agent only.
Does Iclr Artifact Evaluation 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 Iclr Artifact Evaluation 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 Iclr Artifact Evaluation use?
Iclr Artifact Evaluation 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 Iclr Artifact Evaluation use?
About 953 tokens (SKILL.md is roughly 3.8k 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 Iclr Artifact Evaluation?
Skills that share tags, products or a category with Iclr Artifact Evaluation: Extracting Windows Event Logs Artifacts (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Arize Evaluator (github/awesome-copilot, 40k stars), Artifacts Builder (nexu-io/open-design, 100k stars) and Ccs Artifact Evaluation (brycewang-stanford/Awesome-Journal-Skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Iclr Artifact Evaluation?
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.