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/processes

Background jobs, long-running processes, and task management

From plugin
cloddsbot
3.1k121 skills

Claude Code

$ npx -y skills add alsk1992/CloddsBot --skill processes --agent claude-code

SKILL.md

processes.SKILL.md
name: processes
description: "Background jobs, long-running processes, and task management"
emoji: "⚙️"

Processes - Complete API Reference

Spawn and manage background processes, long-running jobs, and scheduled tasks.

---

Chat Commands

Spawn Jobs

/job spawn "npm run backtest"               Start background job
/job spawn "python train.py" --name ml      Named job
/job spawn "node bot.js" --restart          Auto-restart on exit

Manage Jobs

/jobs                                       List all jobs
/job status <id>                            Check job status
/job output <id>                            View job output
/job output <id> --follow                   Stream output
/job stop <id>                              Stop job
/job restart <id>                           Restart job

Logs

/job logs <id>                              View logs
/job logs <id> --tail 100                   Last 100 lines
/job logs <id> --since 1h                   Last hour

---

TypeScript API Reference

Create Process Manager

import { createProcessManager } from 'clodds/processes';

const processes = createProcessManager({
  // Working directory
  cwd: process.cwd(),

  // Environment
  env: process.env,

  // Limits
  maxProcesses: 10,
  maxMemoryMB: 1024,

  // Logging
  logDir: './logs/jobs',
  maxLogSizeMB: 100,

  // Storage
  storage: 'sqlite',
  dbPath: './jobs.db',
});

Spawn Process

// Simple spawn
const job = await processes.spawn({
  command: 'npm',
  args: ['run', 'backtest'],
  name: 'backtest-btc',
});

console.log(`Job ID: ${job.id}`);
console.log(`PID: ${job.pid}`);

// With options
const job = await processes.spawn({
  command: 'python',
  args: ['train.py', '--epochs', '100'],
  name: 'ml-training',

  // Environment
  env: {
    ...process.env,
    CUDA_VISIBLE_DEVICES: '0',
  },

  // Working directory
  cwd: '/path/to/ml-project',

  // Auto-restart
  restart: true,
  maxRestarts: 3,
  restartDelayMs: 5000,

  // Resource limits
  maxMemoryMB: 4096,
  timeoutMs: 3600000,  // 1 hour
});

List Jobs

const jobs = await processes.list();

for (const job of jobs) {
  console.log(`${job.id}: ${job.name}`);
  console.log(`  Status: ${job.status}`);  // 'running' | 'stopped' | 'failed' | 'completed'
  console.log(`  PID: ${job.pid}`);
  console.log(`  Started: ${job.startedAt}`);
  console.log(`  Memory: ${job.memoryMB}MB`);
  console.log(`  CPU: ${job.cpuPercent}%`);
}

Get Status

const status = await processes.getStatus(jobId);

console.log(`Status: ${status.status}`);
console.log(`Exit code: ${status.exitCode}`);
console.log(`Runtime: ${status.runtimeMs}ms`);
console.log(`Restarts: ${status.restarts}`);
console.log(`Memory: ${status.memoryMB}MB`);
console.log(`CPU: ${status.cpuPercent}%`);

Get Output

// Get all output
const output = await processes.getOutput(jobId);
console.log(output.stdout);
console.log(output.stderr);

// Get last N lines
const output = await processes.getOutput(jobId, { tail: 100 });

// Stream output
const stream = processes.streamOutput(jobId);
stream.on('stdout', (data) => console.log(data));
stream.on('stderr', (data) => console.error(data));
stream.on('exit', (code) => console.log(`Exit: ${code}`));

Stop Job

// Graceful stop (SIGTERM)
await processes.stop(jobId);

// Force kill (SIGKILL)
await processes.stop(jobId, { force: true });

// Stop all
await processes.stopAll();

Restart Job

await processes.restart(jobId);

Event Handlers

processes.on('started', (job) => {
  console.log(`Job started: ${job.name}`);
});

processes.on('stopped', (job) => {
  console.log(`Job stopped: ${job.name} (code: ${job.exitCode})`);
});

processes.on('failed', (job, error) => {
  console.error(`Job failed: ${job.name}`, error);
});

processes.on('output', (job, type, data) => {
  console.log(`[${job.name}] ${type}: ${data}`);
});

---

Job Status

| Status | Description | |--------|-------------| | `running` | Currently executing | | `stopped` | Stopped by user | | `completed` | Finished successfully | | `failed` | Exited with error | | `restarting` | Auto-restarting |

---

Use Cases

Run Backtest

const job = await processes.spawn({
  command: 'npm',
  args: ['run', 'backtest', '--', '--strategy', 'momentum'],
  name: 'backtest-momentum',
});

// Wait for completion
const result = await processes.wait(job.id);
console.log(`Backtest complete: ${result.exitCode === 0 ? 'success' : 'failed'}`);

Train ML Model

const job = await processes.spawn({
  command: 'python',
  args: ['train.py'],
  name: 'ml-training',
  cwd: './ml',
  maxMemoryMB: 8192,
  timeoutMs: 86400000,  // 24 hours
});

// Monitor progress
processes.streamOutput(job.id).on('stdout', (line) => {
  if (line.includes('Epoch')) {
    console.log(line);
  }
});

---

Best Practices

1. **Name your jobs** — Easier to identify 2. **Set timeouts** — Prevent runaway processes 3. **Monitor memory** — Prevent OOM kills 4. **Use restart sparingly** — Debug failures first 5. **Check logs** — Always review output

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Questions about processes.

Which coding agents can use processes?
processes installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.