Cron Evaluator

该 Skill 通过 Python 脚本扫描系统 cron 任务，从时间、资源、健壮性和 pertinence 四个维度打分，检测午夜时间碰撞、重负载命令、缺少日志/flock/timeout 等问题，输出健康状态、改进建议以及 systemd timer 迁移建议，并附带 KAN 模型训练脚本与训练数据。

kofna3369

热度 29.22

最近更新 2026-05-18 12:31:01

分类：自动化依赖：代码执行 / 读写文件应用场景：自动化脚本 / DevOps / 日程安排 / 报告撰写

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add cron-evaluator

Metadata

name: cron-evaluator
description: Cron Evaluator — Analyzes and scores cron jobs on a system for health, resource usage, collision risk, and resilience. Provides actionable suggestions for improvement. Use when: (1) auditing cron jobs, (2) detecting timing collisions, (3) optimizing cron performance, (4) planning systemd migration.
triggers: ["cron evaluation","cron audit","cron health","collision detection","cron optimization","systemd migration"]
author: Axioma Cluster
date: 2026-05-17
version: 1.0.0
tags: ["cron","evaluation","system-administration","performance","systemd","scheduling"]
status: active

Cron Evaluator

Evaluates cron job health across 4 pillars: Temporal, Resource, Resilience, and Pertinence.

4 Pillars

Pillar	Checks	Score Range
Temporal	Midnight collision, frequency, jitter	0-1
Resource	Heavy commands (torch, docker, ollama)	0-1
Resilience	Logging, flock, timeout, error handling	0-1
Pertinence	Cron vs systemd timer recommendation	0-1

Usage

# Scan all cron jobs
python3 cron_evaluator_v3.py --scan

# Run health check
python3 cron_evaluator_v3.py --health

# Get improvement suggestions
python3 cron_evaluator_v3.py --suggest

Health Thresholds

Score	Status
>80%	🟢 HEALTHY
60-80%	🟡 NEEDS_WORK
<60%	🔴 CRITICAL

Key Checks

Temporal Collision Detection

# Two crons at 00:00 → suggest jitter
if cron1['time'] == '0 0 * * *' and cron2['time'] == '0 0 * * *':
    suggest("Add jitter: sleep $((RANDOM % 60))")

Resource Signatures

HEAVY_COMMANDS = ['torch', 'tensorflow', 'ollama', 'docker']
if any(h in command for h in HEAVY_COMMANDS):
    score -= 0.3  # Heavy resource consumer

Resilience Verification

CHECKS = {
    'logging': '>> /var/log/...' in command or '2>' in command,
    'flock': 'flock' in command,
    'timeout': 'timeout' in command,
    'error_handling': '||' in command
}

Jitter Implementation

# BEFORE (collision risk)
0 2 * * * /path/to/script.sh

# AFTER (staggered with jitter)
0 2 * * * sleep $((RANDOM % 60)) && /path/to/script.sh

Wrapper for Observability

# Wrapper that logs time/exit/memory
0 2 * * * /usr/bin/python3 /opt/evaluator/wrapper.py --task "TaskName" --cmd "/path/to/script.sh"

Files

cron-evaluator/
├── SKILL.md                   # This file
├── scripts/
│   ├── cron_evaluator.py      # v1 (basic)
│   ├── cron_evaluator_v2.py   # v2 (enhanced)
│   ├── cron_evaluator_v3.py   # v3 (with KAN)
│   └── train_cron_kan.py     # KAN training script
├── data/
│   └── cron_training.json     # Training dataset
└── models/
    └── cron_kan.pt           # Trained KAN model

KAN Model

The Cron KAN (16→32→16→8→4→3) predicts cron job quality from 16 features extracted from schedule and command patterns.