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Convex Functions

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waynesutton
convex-functions

Writing queries, mutations, actions, and HTTP actions with proper argument validation, error handling, internal functions, and runtime considerations

Overview

Publisherwaynesutton
Repositoryconvexskills
Skill nameconvex-functions
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 Functions 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-functions .claude/skills/convex-functions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Convex Functions 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 Functions 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 Functions 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 Functions

Master Convex functions including queries, mutations, actions, and HTTP endpoints with proper validation, error handling, and runtime considerations.

Code Quality

All examples in this skill comply with @convex-dev/eslint-plugin rules:

  • Object syntax with handler property
  • Argument validators on all functions
  • Explicit table names in database operations

See the Code Quality section in convex-best-practices for linting setup.

Documentation Sources

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

Instructions

Function Types Overview

TypeDatabase AccessExternal APIsCachingUse Case
QueryRead-onlyNoYes, reactiveFetching data
MutationRead/WriteNoNoModifying data
ActionVia runQuery/runMutationYesNoExternal integrations
HTTP ActionVia runQuery/runMutationYesNoWebhooks, APIs

Queries

Queries are reactive, cached, and read-only:

typescript
import { query } from "./_generated/server";
import { v } from "convex/values";

export const getUser = query({
  args: { userId: v.id("users") },
  returns: v.union(
    v.object({
      _id: v.id("users"),
      _creationTime: v.number(),
      name: v.string(),
      email: v.string(),
    }),
    v.null(),
  ),
  handler: async (ctx, args) => {
    return await ctx.db.get("users", args.userId);
  },
});

// Query with index
export const listUserTasks = query({
  args: { userId: v.id("users") },
  returns: v.array(
    v.object({
      _id: v.id("tasks"),
      _creationTime: v.number(),
      title: v.string(),
      completed: v.boolean(),
    }),
  ),
  handler: async (ctx, args) => {
    return await ctx.db
      .query("tasks")
      .withIndex("by_user", (q) => q.eq("userId", args.userId))
      .order("desc")
      .collect();
  },
});

Mutations

Mutations modify the database and are transactional:

typescript
import { mutation } from "./_generated/server";
import { v } from "convex/values";
import { ConvexError } from "convex/values";

export const createTask = mutation({
  args: {
    title: v.string(),
    userId: v.id("users"),
  },
  returns: v.id("tasks"),
  handler: async (ctx, args) => {
    // Validate user exists
    const user = await ctx.db.get("users", args.userId);
    if (!user) {
      throw new ConvexError("User not found");
    }

    return await ctx.db.insert("tasks", {
      title: args.title,
      userId: args.userId,
      completed: false,
      createdAt: Date.now(),
    });
  },
});

export const deleteTask = mutation({
  args: { taskId: v.id("tasks") },
  returns: v.null(),
  handler: async (ctx, args) => {
    await ctx.db.delete("tasks", args.taskId);
    return null;
  },
});

Actions

Actions can call external APIs but have no direct database access:

typescript
"use node";

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

export const sendEmail = action({
  args: {
    to: v.string(),
    subject: v.string(),
    body: v.string(),
  },
  returns: v.object({ success: v.boolean() }),
  handler: async (ctx, args) => {
    // Call external API
    const response = await fetch("https://api.email.com/send", {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify(args),
    });

    return { success: response.ok };
  },
});

// Action calling queries and mutations
export const processOrder = action({
  args: { orderId: v.id("orders") },
  returns: v.null(),
  handler: async (ctx, args) => {
    // Read data via query
    const order = await ctx.runQuery(api.orders.get, { orderId: args.orderId });

    if (!order) {
      throw new Error("Order not found");
    }

    // Call external payment API
    const paymentResult = await processPayment(order);

    // Update database via mutation
    await ctx.runMutation(internal.orders.updateStatus, {
      orderId: args.orderId,
      status: paymentResult.success ? "paid" : "failed",
    });

    return null;
  },
});

HTTP Actions

HTTP actions handle webhooks and external requests:

typescript
// convex/http.ts
import { httpRouter } from "convex/server";
import { httpAction } from "./_generated/server";
import { api, internal } from "./_generated/api";

const http = httpRouter();

// Webhook endpoint
http.route({
  path: "/webhooks/stripe",
  method: "POST",
  handler: httpAction(async (ctx, request) => {
    const signature = request.headers.get("stripe-signature");
    const body = await request.text();

    // Verify webhook signature
    if (!verifyStripeSignature(body, signature)) {
      return new Response("Invalid signature", { status: 401 });
    }

    const event = JSON.parse(body);

    // Process webhook
    await ctx.runMutation(internal.payments.handleWebhook, {
      eventType: event.type,
      data: event.data,
    });

    return new Response("OK", { status: 200 });
  }),
});

// API endpoint
http.route({
  path: "/api/users/:userId",
  method: "GET",
  handler: httpAction(async (ctx, request) => {
    const url = new URL(request.url);
    const userId = url.pathname.split("/").pop();

    const user = await ctx.runQuery(api.users.get, {
      userId: userId as Id<"users">,
    });

    if (!user) {
      return new Response("Not found", { status: 404 });
    }

    return Response.json(user);
  }),
});

export default http;

Internal Functions

Use internal functions for sensitive operations:

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

// Only callable from other Convex functions
export const _updateUserCredits = internalMutation({
  args: {
    userId: v.id("users"),
    amount: v.number(),
  },
  returns: v.null(),
  handler: async (ctx, args) => {
    const user = await ctx.db.get("users", args.userId);
    if (!user) return null;

    await ctx.db.patch("users", args.userId, {
      credits: (user.credits || 0) + args.amount,
    });
    return null;
  },
});

// Call internal function from action
export const purchaseCredits = action({
  args: { userId: v.id("users"), amount: v.number() },
  returns: v.null(),
  handler: async (ctx, args) => {
    // Process payment externally
    await processPayment(args.amount);

    // Update credits via internal mutation
    await ctx.runMutation(internal.users._updateUserCredits, {
      userId: args.userId,
      amount: args.amount,
    });

    return null;
  },
});

Scheduling Functions

Schedule functions to run later:

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

export const scheduleReminder = mutation({
  args: {
    userId: v.id("users"),
    message: v.string(),
    delayMs: v.number(),
  },
  returns: v.id("_scheduled_functions"),
  handler: async (ctx, args) => {
    return await ctx.scheduler.runAfter(
      args.delayMs,
      internal.notifications.sendReminder,
      { userId: args.userId, message: args.message },
    );
  },
});

export const sendReminder = internalMutation({
  args: {
    userId: v.id("users"),
    message: v.string(),
  },
  returns: v.null(),
  handler: async (ctx, args) => {
    await ctx.db.insert("notifications", {
      userId: args.userId,
      message: args.message,
      sentAt: Date.now(),
    });
    return null;
  },
});

Examples

Complete Function File

typescript
// convex/messages.ts
import { query, mutation, internalMutation } from "./_generated/server";
import { v } from "convex/values";
import { ConvexError } from "convex/values";
import { internal } from "./_generated/api";

const messageValidator = v.object({
  _id: v.id("messages"),
  _creationTime: v.number(),
  channelId: v.id("channels"),
  authorId: v.id("users"),
  content: v.string(),
  editedAt: v.optional(v.number()),
});

// Public query
export const list = query({
  args: {
    channelId: v.id("channels"),
    limit: v.optional(v.number()),
  },
  returns: v.array(messageValidator),
  handler: async (ctx, args) => {
    const limit = args.limit ?? 50;
    return await ctx.db
      .query("messages")
      .withIndex("by_channel", (q) => q.eq("channelId", args.channelId))
      .order("desc")
      .take(limit);
  },
});

// Public mutation
export const send = mutation({
  args: {
    channelId: v.id("channels"),
    authorId: v.id("users"),
    content: v.string(),
  },
  returns: v.id("messages"),
  handler: async (ctx, args) => {
    if (args.content.trim().length === 0) {
      throw new ConvexError("Message cannot be empty");
    }

    const messageId = await ctx.db.insert("messages", {
      channelId: args.channelId,
      authorId: args.authorId,
      content: args.content.trim(),
    });

    // Schedule notification
    await ctx.scheduler.runAfter(0, internal.messages.notifySubscribers, {
      channelId: args.channelId,
      messageId,
    });

    return messageId;
  },
});

// Internal mutation
export const notifySubscribers = internalMutation({
  args: {
    channelId: v.id("channels"),
    messageId: v.id("messages"),
  },
  returns: v.null(),
  handler: async (ctx, args) => {
    // Get channel subscribers and notify them
    const subscribers = await ctx.db
      .query("subscriptions")
      .withIndex("by_channel", (q) => q.eq("channelId", args.channelId))
      .collect();

    for (const sub of subscribers) {
      await ctx.db.insert("notifications", {
        userId: sub.userId,
        messageId: args.messageId,
        read: false,
      });
    }
    return null;
  },
});

Best Practices

  • Never run npx convex deploy unless explicitly instructed
  • Never run any git commands unless explicitly instructed
  • Always define args and returns validators
  • Use queries for read operations (they are cached and reactive)
  • Use mutations for write operations (they are transactional)
  • Use actions only when calling external APIs
  • Use internal functions for sensitive operations
  • Add "use node"; at the top of action files using Node.js APIs
  • Handle errors with ConvexError for user-facing messages

Common Pitfalls

  1. Using actions for database operations - Use queries/mutations instead
  2. Calling external APIs from queries/mutations - Use actions
  3. Forgetting to add "use node" - Required for Node.js APIs in actions
  4. Missing return validators - Always specify returns
  5. Not using internal functions for sensitive logic - Protect with internalMutation

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 Functions AI skill do?

Writing queries, mutations, actions, and HTTP actions with proper argument validation, error handling, internal functions, and runtime considerations

Why use Convex Functions on TypingMind?

Because you install it once and use it with any model. Convex Functions 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 Functions in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/waynesutton/convexskills/tree/main/skills/convex-functions. 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 Functions?

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 Functions?

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

Is the Convex Functions 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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