Borrowing it
Nothing to install: this file belongs to powroom/flins. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/powroom/flins/main/.agents/skills/Convex Schema Validator/SKILL.mdgit clone --depth 1 https://github.com/powroom/flinsWrote 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.
[](https://agentmods.dev/skills/powroom/flins/convex-schema-validator)<a href="https://agentmods.dev/skills/powroom/flins/convex-schema-validator"><img src="https://agentmods.dev/badge/skills/powroom/flins/convex-schema-validator.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.02547 |
| Opus 5 | $0.00015 | $0.01273 |
| Sonnet 5 | $0.00006 | $0.00509 |
| Haiku 4.5 | $0.00003 | $0.00255 |
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 8d 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.
This is a copy
100% identical to convex-schema-validator — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 400 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:
- Primary: https://docs.convex.dev/database/schemas
- Indexes: https://docs.convex.dev/database/indexes
- Data Types: https://docs.convex.dev/database/types
- For broader context: https://docs.convex.dev/llms.txt
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"],
}),
});
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.
- 8d ago First seen · 400 lines · 29 tokens per session scan A afe8950d358b
Convex Schema Validator is a skill published in the GitHub repository powroom/flins (39 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 2,547 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to convex-schema-validator, differing in 3 lines, and is treated as a copy.
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