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Agent Skill · 前端设计

agentic-process-monitor(Agent 过程监视器)

agentic-process-monitor 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

agentic-process-monitor 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 4,928。

总安装 774周安装 31GitHub Stars 37下载 250核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agentic-process-monitor(Agent 过程监视器)
来源仓库:https://github.com/terrylica/cc-skills
仓库路径:skills/agentic-process-monitor
安装命令:
npx skills add https://github.com/terrylica/cc-skills --skill agentic-process-monitor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/terrylica/cc-skills --skill agentic-process-monitor

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。提供后台进程监控模式,可检测成功、失败、超时或挂起任务。

安装命令:npx skills add https://github.com/terrylica/cc-skills --skill agentic-process-monitor。注意权限范围、维护状态,避免触发联网、命令执行或文件读写。

来源仓库内路径:skills/agentic-process-monitor

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/terrylica/cc-skills --skill agentic-process-mo…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agentic-process-monitor 怎么安装?

在终端执行 npx skills add https://github.com/terrylica/cc-skills --skill agentic-process-monitor。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agentic-process-monitor 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agentic-process-monitor 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/terrylica/cc-skills --skill agentic-process-monitor 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

agentic-process-monitor 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

agentic-process-monitor 用的人多吗?

公开数据是累计安装 774 次,近一周安装 31 次,下载 250 次,GitHub 37 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agentic-process-monitor 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
agentic-process-monitor

Agent 过程监视器 · 本页

77437执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Agentic Process Monitor

Patterns for monitoring background processes from Claude Code — detecting success, failure, timeout, and hung processes, then returning results to the main context to drive the next action.

Companion skills: devops-tools:pueue-job-orchestration (remote/queued work) | devops-tools:distributed-job-safety (concurrency)


Self-Evolving Skill: This skill improves through use. If instructions are wrong, parameters drifted, or a workaround was needed — fix this file immediately, don't defer. Only update for real, reproducible issues.

Architecture: Sentinel + Heartbeat + Agent

Main Context                          Monitor Agent (subagent)
─────────────                         ──────────────────────
1. Start work (Bash run_in_background)
   └─ work wrapper writes sentinel files
2. Launch Agent (poll every 15s) ────► poll loop:
3. Continue other work                  .status exists? → return result
                                        .heartbeat stale? → kill, return error
                                        elapsed > max? → kill, return timeout
4. Agent returns ◄──────────────────── detected outcome
5. Act on result (next step / retry / abort)

Why this architecture: The main context stays lean (no polling tokens burned). The subagent handles all the waiting. If the subagent itself fails, the main context can recover by checking sentinel files directly.


Sentinel Protocol

The work process writes 4 files to a known directory (e.g., /tmp/<project>-monitor/):

FileWhen WrittenPurpose
<step>.pidOn startPID for timeout kill
<step>.heartbeatEvery N seconds during workmtime freshness = alive proof
<step>.statusOn exit (SUCCESS / FAILED)Completion sentinel
<step>.resultOn successStructured output (JSON)

Work Wrapper Template

#!/usr/bin/env bash
set -uo pipefail
STEP="${1:?step name required}"
MONITOR_DIR="${2:-/tmp/monitor}"
mkdir -p "$MONITOR_DIR"

echo $$ > "${MONITOR_DIR}/${STEP}.pid"

# Heartbeat: touch file every 10s in background
(while true; do touch "${MONITOR_DIR}/${STEP}.heartbeat"; sleep 10; done) &
HB_PID=$!
trap "kill $HB_PID 2>/dev/null" EXIT

# === YOUR WORK HERE ===
if your_command --args 2>"${MONITOR_DIR}/${STEP}.log"; then
    echo "SUCCESS" > "${MONITOR_DIR}/${STEP}.status"
    echo '{"key": "value"}' > "${MONITOR_DIR}/${STEP}.result"
else
    echo "FAILED" > "${MONITOR_DIR}/${STEP}.status"
fi

Monitor Decision Tree

The polling agent checks every POLL_INTERVAL seconds (default: 15s):

every POLL_INTERVAL:
  .status exists?
    → read status + result, return to main context
  .heartbeat exists AND mtime stale (> STALE_THRESHOLD)?
    → process hung — kill PID, return "hung" error
  elapsed > MAX_TIMEOUT?
    → timeout — kill PID, return "timeout" error
  otherwise
    → sleep POLL_INTERVAL, continue

Recommended Defaults

ParameterDefaultRationale
POLL_INTERVAL15sBalances latency vs token cost
HEARTBEAT_INTERVAL10sMust be < STALE_THRESHOLD / 2
STALE_THRESHOLD60s6x heartbeat interval = generous slack
MAX_TIMEOUT1800s (30min)Catch infrastructure failures

Circuit Breaker

Prevent repeated failures from wasting compute. Three consecutive crashes or failures → stop and report. Reset counter on any success.

consecutive_failures = 0
MAX_CONSECUTIVE = 3

on failure:
  consecutive_failures += 1
  if consecutive_failures >= MAX_CONSECUTIVE:
    STOP — likely infrastructure, not the work itself

on success:
  consecutive_failures = 0

Agent Self-Healing

If the monitoring subagent fails (context overflow, timeout, crash), the main context recovers:

  1. Check .status file directly — work may have finished while agent was dead
  2. If .status exists → read result, continue normally
  3. If no .status but .heartbeat is fresh → spawn replacement monitor agent
  4. If no .status and .heartbeat is stale → process hung, kill PID, log error

This guarantees the main context never gets permanently stuck.


Anti-Patterns

Anti-PatternWhy It FailsUse Instead
`tail -f \grep -m1`Broken on macOS — pipe buffering prevents grep exit from killing tail, causing permanent hangPoll the log file for markers with grep in a loop
run_in_background aloneTask IDs can expire or become unretrievable; stuck-as-running bug; no intermediate progressSentinel files + agent polling
Poll from main contextEach poll injects output into the context window, burning ~50K tokens per checkDelegate polling to a subagent
Hardcoded sleep timeoutWastes time on fast completions, too short for slow onesPoll interval + max timeout
PID-only liveness checkCannot distinguish a hung process (PID alive, no progress) from a running oneHeartbeat file mtime — hung process stops touching the file
uv run masking stale venvuv run has its own resolution that bypasses broken venv state; console scripts (pytest, ruff) have stale shebangs after repo renameRun uv sync --python 3.13 --extra dev after any repo rename or move

Environment Preflight

Run before entering any autonomous loop. If any check fails, fix before proceeding.

# 1. Python package importable?
uv run --python 3.13 python -c "import your_package" \
  || uv sync --python 3.13 --extra dev

# 2. Console scripts have valid shebangs? (catches post-rename breakage)
uv run --python 3.13 pytest --co -q tests/ 2>/dev/null \
  || uv sync --python 3.13 --extra dev

# 3. External service reachable?
curl -sf "http://localhost:PORT/?query=SELECT+1" \
  || echo "FAIL: start service or SSH tunnel"

Common uv/venv Failures

SymptomRoot CauseFix
ModuleNotFoundError but uv run python -c "import..." worksStale venv — console script shebangs point to old repo pathuv sync --python 3.13 --extra dev
bad interpreter:...old-path/.venv/bin/python3Same — .venv/bin/pytest shebang hardcoded pre-rename directoryuv sync --python 3.13 --extra dev
pip show says not found, uv run says installeduv run resolution bypasses venv pip metadatauv sync reconciles both

Rule: After any repo rename, directory move, or Python version change → always uv sync --python 3.13 --extra dev before running anything.

Post-Execution Reflection

After this skill completes, check before closing:

  1. Did the command succeed? — If not, fix the instruction or error table that caused the failure.
  2. Did parameters or output change? — If the underlying tool's interface drifted, update Usage examples and Parameters table to match.
  3. Was a workaround needed? — If you had to improvise (different flags, extra steps), update this SKILL.md so the next invocation doesn't need the same workaround.

Only update if the issue is real and reproducible — not speculative.

平台分布

Codex

35.1%
按下载量换算88

Claude

28.84%
按下载量换算72

Cursor

17.46%
按下载量换算44

Gemini CLI

8.72%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/terrylica/cc-skills --skill agentic-process-monitor 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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