بنقرة واحدة
check-experiments
Standardized tmux experiment monitoring with progress parsing, CSV log reading, and status reporting
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Standardized tmux experiment monitoring with progress parsing, CSV log reading, and status reporting
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
计算机论文草稿终审与分层重写工作流。先逻辑后语言:检查全文章节结构 → 章节内部逻辑 → 跨章节一致性 → 写作风格 → 摘要逐句功能 → 图表 → 投稿前 sanity check。问题按 P0/P1/P2 分级。适用于 NeurIPS/ICML/ICLR/KDD/CCS/USENIX/SIGMOD/VLDB/IEEE Transactions 等顶会顶刊。Use when 用户请求论文终审、逻辑诊断、分层重写、投稿前检查,或在草稿已成形阶段进行系统性修改。
Paper editing with built-in style constraints for academic writing quality, including anti-AI detection, LaTeX validation, and figure standards
Address reviewer/editor comments by number with localized, traceable edits. Use when the user provides numbered reviewer concerns, editor proof queries, or revision lists and asks to "address comment N", "fix W1-W4", "respond to editor queries", etc. Complements review-response (rebuttal drafting) and paper-edit (style enforcement).
Use when ingesting arXiv papers into a project-local Zotero library, building a fresh Zotero collection tree for a research project, the Zotero free-tier 300 MB cloud quota is full ("File would exceed quota" / 413 Request Entity Too Large on attachment upload), the user wants PDFs to live alongside project files rather than in Zotero cloud, or the user asks to "把论文加进 Zotero / 建立 Zotero 分类 / set up related_work folder with Zotero".
Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.
从论文中提取图片,优先从arXiv源码包获取真正的论文图
| name | check-experiments |
| description | Standardized tmux experiment monitoring with progress parsing, CSV log reading, and status reporting |
| tags | ["Experiment","Monitoring","tmux","ML"] |
Standardized workflow for checking all running ML experiments via tmux sessions.
tmux ls
Report each session: name, creation time, attached/detached status.
For each session, capture the last 30-50 lines:
tmux capture-pane -t <session-name> -p | tail -50
Look for common progress indicators in the output:
Epoch X/Y or epoch: XStep X/Y or X/Y iterationsXX.X%loss: X.XXXX, val_loss: X.XXXXaccuracy, f1, aucIf experiments write to CSV logs, read the latest entries:
# Find recent CSV logs
find . -name "*.csv" -newer <start-time> -type f
# Read last few rows
tail -5 <log-file.csv>
Scan output for common failure patterns:
CUDA out of memoryRuntimeErrorTracebackErrorKilled or OOMOutput a structured report:
## Experiment Status Report
| Session | Status | Progress | Metric | ETA |
|---------|--------|----------|--------|-----|
| sweep-lr | Running | 45/100 epochs | loss: 0.234 | ~2h |
| ablation-1 | Running | 78% | acc: 0.891 | ~30min |
| baseline | Completed | 100/100 | loss: 0.198 | - |
| sweep-wd | Error | 23/100 | CUDA OOM | - |
If experiments.md exists in the project, update it with:
/check-experiments commandexperiment-monitor.js hook shows brief summary at session startstop-summary.js hook shows running session count at session end