convex-schema-validator

convex-schema-validator is a skill for Claude Code, Codex from waynesutton/convexskills. It costs 29 tokens per session (2,554 once invoked), scanned A, original, Apache-2.0.

Guidance for defining and checking the structure of data in Convex, including fields, types, indexes, optional values, allowed alternatives, and changes to existing data.

In plain words
What is it for?
Use it when creating or updating Convex database schemas, adding indexes, validating records, or preparing migrations.
Why use it?
It helps prevent stored data from having the wrong shape and makes database changes easier to plan safely.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the convexskills plugin — 14 skills shipped together

Good fit Use it when creating or updating Convex database schemas, adding indexes, validating records, or preparing migrations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/waynesutton/convexskills/convex-schema-validator
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add waynesutton/convexskills --skill convex-schema-validator
Clone the repo
git clone --depth 1 https://github.com/waynesutton/convexskills

Made for: Claude Code, Codex.

Or install convexskills, the plugin that ships this one along with the rest of its 14 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for convex-schema-validator

README.md
[![agentmods](https://agentmods.dev/badge/skills/waynesutton/convexskills/convex-schema-validator/github.svg)](https://agentmods.dev/skills/waynesutton/convexskills/convex-schema-validator)
Your own site
<a href="https://agentmods.dev/skills/waynesutton/convexskills/convex-schema-validator"><img src="https://agentmods.dev/badge/skills/waynesutton/convexskills/convex-schema-validator/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for convex-schema-validator

Your own site · 80×15
<a href="https://agentmods.dev/skills/waynesutton/convexskills/convex-schema-validator"><img src="https://agentmods.dev/badge/skills/waynesutton/convexskills/convex-schema-validator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,554 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 18 Mar 2026
  • Snyk pass 17 Feb 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00029 $0.02554
Opus 5 $0.00015 $0.01277
Sonnet 5 $0.00006 $0.00511
Haiku 4.5 $0.00003 $0.00255

Measured 9d ago against content hash 97c8539f19f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

convex-schema-validator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

skills/convex-schema-validator/SKILL.md · 401 lines

How it starts

The opening of the file, as written. The whole thing — 401 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Convex Schema Validator

Define and validate database schemas in Convex with proper typing, index configuration, optional fields, unions, and strategies for schema migrations.

Documentation Sources

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

Instructions

Basic Schema Definition

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

export default defineSchema({
  users: defineTable({
    name: v.string(),
    email: v.string(),
    avatarUrl: v.optional(v.string()),
    createdAt: v.number(),
  }),
  
  tasks: defineTable({
    title: v.string(),
    description: v.optional(v.string()),
    completed: v.boolean(),
    userId: v.id("users"),
    priority: v.union(
      v.literal("low"),
      v.literal("medium"),
      v.literal("high")
    ),
  }),
});

Validator Types

Validator TypeScript Type Example
v.string() string "hello"
v.number() number 42, 3.14
v.boolean() boolean true, false
v.null() null null
v.int64() bigint 9007199254740993n
v.bytes() ArrayBuffer Binary data
v.id("table") Id<"table"> Document reference
v.array(v) T[] [1, 2, 3]
v.object({}) { ... } { name: "..." }
v.optional(v) T | undefined Optional field
v.union(...) T1 | T2 Multiple types
v.literal(x) "x" Exact value
v.any() any Any value
v.record(k, v) Record<K, V> Dynamic keys

Index Configuration

export default defineSchema({
  messages: defineTable({
    channelId: v.id("channels"),
    authorId: v.id("users"),
    content: v.string(),
    sentAt: v.number(),
  })
    // Single field index
    .index("by_channel", ["channelId"])
    // Compound index
    .index("by_channel_and_author", ["channelId", "authorId"])
    // Index for sorting
    .index("by_channel_and_time", ["channelId", "sentAt"]),
    
  // Full-text search index
  articles: defineTable({
    title: v.string(),
    body: v.string(),
    category: v.string(),
  })
    .searchIndex("search_content", {
      searchField: "body",
      filterFields: ["category"],
    }),
});

Read the full file on GitHub · 401 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 401 lines · 29 tokens per session scan A 97c8539f19f9

Subscribe to this mod's changes

convex-schema-validator is a skill published in the GitHub repository waynesutton/convexskills (404 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 2,554 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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