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.
npx agentmods add rules/squirrelogic/cursor-rules/drizzle-queriesgit clone --depth 1 https://github.com/squirrelogic/cursor-rulesWhat 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 | $0.00000 | $0.01384 |
| Opus 5 | $0.00000 | $0.00692 |
| Sonnet 5 | $0.00000 | $0.00277 |
| Haiku 4.5 | $0.00000 | $0.00138 |
Grade A, and why
drizzle-queries 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Drizzle Query Patterns
Guidelines for writing consistent and secure Drizzle ORM queries with RLS.
Overview
This rule defines patterns for writing Drizzle ORM queries and mutations that respect Row Level Security (RLS) policies.
actions:
-
type: suggest message: | When writing Drizzle queries:
- Query Structure:
// ✅ DO: Use simple, direct queries with RLS export async function getItems() { const db = await createDrizzleSupabaseClient() const result = await db.rls(async (tx) => { return await tx.select().from(items) }) return result } // ❌ DON'T: Add unnecessary complexity or manual auth checks export async function getItems() { const supabase = await createClient() // ❌ Don't use Supabase client directly const { data: { user } } = await supabase.auth.getUser() if (!user) throw new Error('Not authenticated') // ... more unnecessary checks }- Mutations:
// ✅ DO: Return the mutated record when possible export async function createItem(data: NewItem) { const db = await createDrizzleSupabaseClient() const result = await db.rls(async (tx) => { const [item] = await tx.insert(items) .values(data) .returning() return item }) return result } // ❌ DON'T: Return void or boolean when you can return the record export async function createItem(data: NewItem) { const db = await createDrizzleSupabaseClient() await db.rls(async (tx) => { await tx.insert(items).values(data) }) return true // ❌ Less useful than returning the record }
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.
- 2d ago First seen · 197 lines · 0 tokens per session scan A 3b0f901708ef
drizzle-queries is a cursor rule published in the GitHub repository squirrelogic/cursor-rules (20 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,384 tokens. 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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