awesome-cursor-rules-mdc is a generator that creates Cursor MDC rule files from structured library information, using semantic search and language models to gather and organize guidance. Developers use it to produce reusable rules for libraries in Cursor, and the catalogue includes 200 of those rules.
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.
git clone --depth 1 https://github.com/sanjeed5/awesome-cursor-rules-mdcWrote 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/rules/sanjeed5/awesome-cursor-rules-mdc/firebase)<a href="https://agentmods.dev/rules/sanjeed5/awesome-cursor-rules-mdc/firebase"><img src="https://agentmods.dev/badge/rules/sanjeed5/awesome-cursor-rules-mdc/firebase.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 | $0.00292 | $0.00292 |
| Opus 5 | $0.00146 | $0.00146 |
| Sonnet 5 | $0.00058 | $0.00058 |
| Haiku 4.5 | $0.00029 | $0.00029 |
Grade A, and why
firebase 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 3d 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.
What it actually says
firebase Best Practices
Firebase is a powerful Backend-as-a-Service (BaaS) that accelerates development. To leverage it effectively, you must adhere to strict best practices for security, performance, and maintainability. This guide outlines the definitive approach for our team.
1. Security Best Practices
Security is paramount. Assume all client-side code is compromised and enforce access control exclusively through Firebase Security Rules and App Check.
1.1 Enable Firebase App Check
Always enable App Check for all supported Firebase services. This verifies that requests originate from your authentic app and an untampered device, preventing unauthorized clients from accessing your backend.
✅ GOOD: Enable App Check Configure App Check in the Firebase Console for Firestore, Realtime Database, Storage, and Functions. On the client, initialize it early.
// client/src/firebase.ts
import { initializeApp } from 'firebase/app';
import { initializeAppCheck, ReCaptchaV3Provider } from 'firebase/app-check';
// For mobile, use platform-specific providers (e.g., ReactNativeFirebaseAppCheckProvider)
const firebaseConfig = {
apiKey: "YOUR_API_KEY",
authDomain: "YOUR_AUTH_DOMAIN",
projectId: "YOUR_PROJECT_
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.
- 3d ago First seen · 29 lines · 292 tokens per session scan A 6bf82a15ca9e
firebase is a cursor rule published in the GitHub repository sanjeed5/awesome-cursor-rules-mdc (3,571 stars, last pushed 3mo ago), licensed CC0-1.0. It adds 292 tokens to every session, about $0.0015 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 2026-09-03.
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