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Convex Cron Jobs

Community
waynesutton
convex-cron-jobs

Scheduled function patterns for background tasks including interval scheduling, cron expressions, job monitoring, retry strategies, and best practices for long-running tasks

Overview

Publisherwaynesutton
Repositoryconvexskills
Skill nameconvex-cron-jobs
Stars
404
Forks
32
Bundled files
3
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by waynesutton on GitHub. Read the source before you install it.

Installation

Install the Convex Cron Jobs AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/waynesutton/convexskills.git /tmp/convexskills
mkdir -p .claude/skills
cp -r /tmp/convexskills/skills/convex-cron-jobs .claude/skills/convex-cron-jobs
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Convex Cron Jobs in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Convex Cron Jobs on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Convex Cron Jobs is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Convex Cron Jobs

Schedule recurring functions for background tasks, cleanup jobs, data syncing, and automated workflows in Convex applications.

Documentation Sources

Before implementing, do not assume; fetch the latest documentation:

Instructions

Cron Jobs Overview

Convex cron jobs allow you to schedule functions to run at regular intervals or specific times. Key features:

  • Run functions on a fixed schedule
  • Support for interval-based and cron expression scheduling
  • Automatic retries on failure
  • Monitoring via the Convex dashboard

Basic Cron Setup

typescript
// convex/crons.ts
import { cronJobs } from "convex/server";
import { internal } from "./_generated/api";

const crons = cronJobs();

// Run every hour
crons.interval(
  "cleanup expired sessions",
  { hours: 1 },
  internal.tasks.cleanupExpiredSessions,
  {}
);

// Run every day at midnight UTC
crons.cron(
  "daily report",
  "0 0 * * *",
  internal.reports.generateDailyReport,
  {}
);

export default crons;

Interval-Based Scheduling

Use crons.interval for simple recurring tasks:

typescript
// convex/crons.ts
import { cronJobs } from "convex/server";
import { internal } from "./_generated/api";

const crons = cronJobs();

// Every 5 minutes
crons.interval(
  "sync external data",
  { minutes: 5 },
  internal.sync.fetchExternalData,
  {}
);

// Every 2 hours
crons.interval(
  "cleanup temp files",
  { hours: 2 },
  internal.files.cleanupTempFiles,
  {}
);

// Every 30 seconds (minimum interval)
crons.interval(
  "health check",
  { seconds: 30 },
  internal.monitoring.healthCheck,
  {}
);

export default crons;

Cron Expression Scheduling

Use crons.cron for precise scheduling with cron expressions:

typescript
// convex/crons.ts
import { cronJobs } from "convex/server";
import { internal } from "./_generated/api";

const crons = cronJobs();

// Every day at 9 AM UTC
crons.cron(
  "morning notifications",
  "0 9 * * *",
  internal.notifications.sendMorningDigest,
  {}
);

// Every Monday at 8 AM UTC
crons.cron(
  "weekly summary",
  "0 8 * * 1",
  internal.reports.generateWeeklySummary,
  {}
);

// First day of every month at midnight
crons.cron(
  "monthly billing",
  "0 0 1 * *",
  internal.billing.processMonthlyBilling,
  {}
);

// Every 15 minutes
crons.cron(
  "frequent sync",
  "*/15 * * * *",
  internal.sync.syncData,
  {}
);

export default crons;

Cron Expression Reference

┌───────────── minute (0-59)
│ ┌───────────── hour (0-23)
│ │ ┌───────────── day of month (1-31)
│ │ │ ┌───────────── month (1-12)
│ │ │ │ ┌───────────── day of week (0-6, Sunday=0)
│ │ │ │ │
* * * * *

Common patterns:

  • * * * * * - Every minute
  • 0 * * * * - Every hour
  • 0 0 * * * - Every day at midnight
  • 0 0 * * 0 - Every Sunday at midnight
  • 0 0 1 * * - First day of every month
  • */5 * * * * - Every 5 minutes
  • 0 9-17 * * 1-5 - Every hour from 9 AM to 5 PM, Monday through Friday

Internal Functions for Crons

Cron jobs should call internal functions for security:

typescript
// convex/tasks.ts
import { internalMutation, internalQuery } from "./_generated/server";
import { v } from "convex/values";

// Cleanup expired sessions
export const cleanupExpiredSessions = internalMutation({
  args: {},
  returns: v.number(),
  handler: async (ctx) => {
    const oneHourAgo = Date.now() - 60 * 60 * 1000;
    
    const expiredSessions = await ctx.db
      .query("sessions")
      .withIndex("by_lastActive")
      .filter((q) => q.lt(q.field("lastActive"), oneHourAgo))
      .collect();

    for (const session of expiredSessions) {
      await ctx.db.delete(session._id);
    }

    return expiredSessions.length;
  },
});

// Process pending tasks
export const processPendingTasks = internalMutation({
  args: {},
  returns: v.null(),
  handler: async (ctx) => {
    const pendingTasks = await ctx.db
      .query("tasks")
      .withIndex("by_status", (q) => q.eq("status", "pending"))
      .take(100);

    for (const task of pendingTasks) {
      await ctx.db.patch(task._id, {
        status: "processing",
        startedAt: Date.now(),
      });
      
      // Schedule the actual processing
      await ctx.scheduler.runAfter(0, internal.tasks.processTask, {
        taskId: task._id,
      });
    }

    return null;
  },
});

Cron Jobs with Arguments

Pass static arguments to cron jobs:

typescript
// convex/crons.ts
import { cronJobs } from "convex/server";
import { internal } from "./_generated/api";

const crons = cronJobs();

// Different cleanup intervals for different types
crons.interval(
  "cleanup temp files",
  { hours: 1 },
  internal.cleanup.cleanupByType,
  { fileType: "temp", maxAge: 3600000 }
);

crons.interval(
  "cleanup cache files",
  { hours: 24 },
  internal.cleanup.cleanupByType,
  { fileType: "cache", maxAge: 86400000 }
);

export default crons;
typescript
// convex/cleanup.ts
import { internalMutation } from "./_generated/server";
import { v } from "convex/values";

export const cleanupByType = internalMutation({
  args: {
    fileType: v.string(),
    maxAge: v.number(),
  },
  returns: v.number(),
  handler: async (ctx, args) => {
    const cutoff = Date.now() - args.maxAge;
    
    const oldFiles = await ctx.db
      .query("files")
      .withIndex("by_type_and_created", (q) => 
        q.eq("type", args.fileType).lt("createdAt", cutoff)
      )
      .collect();

    for (const file of oldFiles) {
      await ctx.storage.delete(file.storageId);
      await ctx.db.delete(file._id);
    }

    return oldFiles.length;
  },
});

Monitoring and Logging

Add logging to track cron job execution:

typescript
// convex/tasks.ts
import { internalMutation } from "./_generated/server";
import { v } from "convex/values";

export const cleanupWithLogging = internalMutation({
  args: {},
  returns: v.null(),
  handler: async (ctx) => {
    const startTime = Date.now();
    let processedCount = 0;
    let errorCount = 0;

    try {
      const expiredItems = await ctx.db
        .query("items")
        .withIndex("by_expiresAt")
        .filter((q) => q.lt(q.field("expiresAt"), Date.now()))
        .collect();

      for (const item of expiredItems) {
        try {
          await ctx.db.delete(item._id);
          processedCount++;
        } catch (error) {
          errorCount++;
          console.error(`Failed to delete item ${item._id}:`, error);
        }
      }

      // Log job completion
      await ctx.db.insert("cronLogs", {
        jobName: "cleanup",
        startTime,
        endTime: Date.now(),
        duration: Date.now() - startTime,
        processedCount,
        errorCount,
        status: errorCount === 0 ? "success" : "partial",
      });
    } catch (error) {
      // Log job failure
      await ctx.db.insert("cronLogs", {
        jobName: "cleanup",
        startTime,
        endTime: Date.now(),
        duration: Date.now() - startTime,
        processedCount,
        errorCount,
        status: "failed",
        error: String(error),
      });
      throw error;
    }

    return null;
  },
});

Batching for Large Datasets

Handle large datasets in batches to avoid timeouts:

typescript
// convex/tasks.ts
import { internalMutation } from "./_generated/server";
import { internal } from "./_generated/api";
import { v } from "convex/values";

const BATCH_SIZE = 100;

export const processBatch = internalMutation({
  args: {
    cursor: v.optional(v.string()),
  },
  returns: v.null(),
  handler: async (ctx, args) => {
    const result = await ctx.db
      .query("items")
      .withIndex("by_status", (q) => q.eq("status", "pending"))
      .paginate({ numItems: BATCH_SIZE, cursor: args.cursor ?? null });

    for (const item of result.page) {
      await ctx.db.patch(item._id, {
        status: "processed",
        processedAt: Date.now(),
      });
    }

    // Schedule next batch if there are more items
    if (!result.isDone) {
      await ctx.scheduler.runAfter(0, internal.tasks.processBatch, {
        cursor: result.continueCursor,
      });
    }

    return null;
  },
});

External API Calls in Crons

Use actions for external API calls:

typescript
// convex/sync.ts
"use node";

import { internalAction } from "./_generated/server";
import { internal } from "./_generated/api";
import { v } from "convex/values";

export const syncExternalData = internalAction({
  args: {},
  returns: v.null(),
  handler: async (ctx) => {
    // Fetch from external API
    const response = await fetch("https://api.example.com/data", {
      headers: {
        Authorization: `Bearer ${process.env.API_KEY}`,
      },
    });

    if (!response.ok) {
      throw new Error(`API request failed: ${response.status}`);
    }

    const data = await response.json();

    // Store the data using a mutation
    await ctx.runMutation(internal.sync.storeExternalData, {
      data,
      syncedAt: Date.now(),
    });

    return null;
  },
});

export const storeExternalData = internalMutation({
  args: {
    data: v.any(),
    syncedAt: v.number(),
  },
  returns: v.null(),
  handler: async (ctx, args) => {
    await ctx.db.insert("externalData", {
      data: args.data,
      syncedAt: args.syncedAt,
    });
    return null;
  },
});
typescript
// convex/crons.ts
import { cronJobs } from "convex/server";
import { internal } from "./_generated/api";

const crons = cronJobs();

crons.interval(
  "sync external data",
  { minutes: 15 },
  internal.sync.syncExternalData,
  {}
);

export default crons;

Examples

Schema for Cron Job Logging

typescript
// convex/schema.ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  cronLogs: defineTable({
    jobName: v.string(),
    startTime: v.number(),
    endTime: v.number(),
    duration: v.number(),
    processedCount: v.number(),
    errorCount: v.number(),
    status: v.union(
      v.literal("success"),
      v.literal("partial"),
      v.literal("failed")
    ),
    error: v.optional(v.string()),
  })
    .index("by_job", ["jobName"])
    .index("by_status", ["status"])
    .index("by_startTime", ["startTime"]),

  sessions: defineTable({
    userId: v.id("users"),
    token: v.string(),
    lastActive: v.number(),
    expiresAt: v.number(),
  })
    .index("by_user", ["userId"])
    .index("by_lastActive", ["lastActive"])
    .index("by_expiresAt", ["expiresAt"]),

  tasks: defineTable({
    type: v.string(),
    status: v.union(
      v.literal("pending"),
      v.literal("processing"),
      v.literal("completed"),
      v.literal("failed")
    ),
    data: v.any(),
    createdAt: v.number(),
    startedAt: v.optional(v.number()),
    completedAt: v.optional(v.number()),
  })
    .index("by_status", ["status"])
    .index("by_type_and_status", ["type", "status"]),
});

Complete Cron Configuration Example

typescript
// convex/crons.ts
import { cronJobs } from "convex/server";
import { internal } from "./_generated/api";

const crons = cronJobs();

// Cleanup jobs
crons.interval(
  "cleanup expired sessions",
  { hours: 1 },
  internal.cleanup.expiredSessions,
  {}
);

crons.interval(
  "cleanup old logs",
  { hours: 24 },
  internal.cleanup.oldLogs,
  { maxAgeDays: 30 }
);

// Sync jobs
crons.interval(
  "sync user data",
  { minutes: 15 },
  internal.sync.userData,
  {}
);

// Report jobs
crons.cron(
  "daily analytics",
  "0 1 * * *",
  internal.reports.dailyAnalytics,
  {}
);

crons.cron(
  "weekly summary",
  "0 9 * * 1",
  internal.reports.weeklySummary,
  {}
);

// Health checks
crons.interval(
  "service health check",
  { minutes: 5 },
  internal.monitoring.healthCheck,
  {}
);

export default crons;

Best Practices

  • Never run npx convex deploy unless explicitly instructed
  • Never run any git commands unless explicitly instructed
  • Only use crons.interval or crons.cron methods, not deprecated helpers
  • Always call internal functions from cron jobs for security
  • Import internal from _generated/api even for functions in the same file
  • Add logging and monitoring for production cron jobs
  • Use batching for operations that process large datasets
  • Handle errors gracefully to prevent job failures
  • Use meaningful job names for dashboard visibility
  • Consider timezone when using cron expressions (Convex uses UTC)

Common Pitfalls

  1. Using public functions - Cron jobs should call internal functions only
  2. Long-running mutations - Break large operations into batches
  3. Missing error handling - Unhandled errors will fail the entire job
  4. Forgetting timezone - All cron expressions use UTC
  5. Using deprecated helpers - Avoid crons.hourly, crons.daily, etc.
  6. Not logging execution - Makes debugging production issues difficult

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Convex Cron Jobs AI skill do?

Scheduled function patterns for background tasks including interval scheduling, cron expressions, job monitoring, retry strategies, and best practices for long-running tasks

Why use Convex Cron Jobs on TypingMind?

Because you install it once and use it with any model. Convex Cron Jobs is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Convex Cron Jobs in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/waynesutton/convexskills/tree/main/skills/convex-cron-jobs. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Convex Cron Jobs?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Convex Cron Jobs?

As many as you like. As long as a model supports skills, you can use Convex Cron Jobs with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Convex Cron Jobs AI skill free?

Yes. It is published on GitHub by waynesutton under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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