基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/Best6668/AMIS --skill monitor-solver命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | monitor-solver |
| description | 监控求解进度,检查中间结果,估算剩余时间。当用户说'检查进度'、'is it done'、'monitor'、'求解完了吗'时使用。 |
| argument-hint | ["solver-name or log-file"] |
| allowed-tools | Bash(*), Read, Write, Edit, Grep, Glob |
Monitor: $ARGUMENTS
# Check for running solver processes
ps aux | grep -E "python|matlab" | grep -v grep
# Check if PID file exists
if [ -f solver_pid.txt ]; then
PID=$(cat solver_pid.txt)
ps -p $PID > /dev/null 2>&1 && echo "Solver running (PID: $PID)" || echo "Solver finished/crashed"
fi
Check the most recent log files:
# Find recent log files
ls -lt *.log solve_log.txt *.txt 2>/dev/null | head -10
# Show last 50 lines of the most recent log
tail -50 solve_log.txt 2>/dev/null
If no log files found, check for output files in results/ directory.
# Check for result files
ls -lt results/*.{json,csv,xlsx,txt} output/*.{json,csv,xlsx,txt} 2>/dev/null | head -20
If result files exist, read and parse them:
# For CSV results
python3 -c "import pandas as pd; df = pd.read_csv('results/latest.csv'); print(df.describe())"
# For JSON results
python3 -c "import json; data = json.load(open('results/latest.json')); print(json.dumps(data, indent=2, ensure_ascii=False)[:2000])"
Parse the log file for key solving metrics:
python3 -c "
import re
with open('solve_log.txt') as f:
lines = f.readlines()
# Extract iteration progress
iterations = [l for l in lines if 'iteration' in l.lower() or 'iter' in l.lower()]
if iterations:
print('Latest iteration:', iterations[-1].strip())
# Extract objective function values
objectives = [l for l in lines if 'objective' in l.lower() or 'obj' in l.lower()]
if objectives:
print('Latest objective:', objectives[-1].strip())
# Extract convergence info
convergence = [l for l in lines if 'residual' in l.lower() or 'converge' in l.lower()]
if convergence:
print('Convergence:', convergence[-1].strip())
# Extract timing info
timing = [l for l in lines if 'time' in l.lower() or 'elapsed' in l.lower()]
if timing:
print('Timing:', timing[-1].strip())
"
What to extract:
This gives the /auto-optimize-loop richer signal than just log output — convergence trends, objective evolution, and timing estimates.
Present results in a comparison table:
| 子问题 | 方法 | 关键指标 | 与预期对比 | 状态 |
|--------|------|---------|----------|------|
| 问题1 | 线性规划 | 最优值=X.XX | 符合预期 | done |
| 问题2 | 回归分析 | R²=0.95 | +0.05 vs baseline | done |
Generate a brief progress report:
=== 求解进度报告 ===
运行状态: [running/completed/error]
已完成子问题: X/Y
当前子问题: [name] (迭代 M/N)
目标函数趋势: [converging/oscillating/diverging]
已用时间: XX min
预估剩余: XX min
cat << 'EOF' > file) to write in chunks. Do NOT ask the user for permission — just do it silently.数据清洗、EDA、缺失值处理、异常值检测、相关性分析。触发词: 数据预处理、数据清洗、EDA、缺失值、异常值、data preprocessing、数据探索。
模型验证:交叉验证、留出法、残差分析、与已知解对比、假设检验。触发词: 模型验证、交叉验证、残差分析、model validation、留出法、误差分析、假设检验。
多子问题拆解与依赖分析。触发词: 子问题拆解、拆题、problem decomposition、依赖关系、求解顺序、时间分配、并行安排。