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 skills add j4flmao/agent-skills --skill firebasegit clone --depth 1 https://github.com/j4flmao/agent-skillsWrote 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/j4flmao/agent-skills/firebase)<a href="https://agentmods.dev/skills/j4flmao/agent-skills/firebase"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/firebase/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.
<a href="https://agentmods.dev/skills/j4flmao/agent-skills/firebase"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/firebase.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00091 | $0.05228 |
| Opus 5 | $0.00046 | $0.02614 |
| Sonnet 5 | $0.00018 | $0.01046 |
| Haiku 4.5 | $0.00009 | $0.00523 |
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 6d 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 — 597 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Firebase
Purpose
Architect serverless backends on Firebase — Firestore document modeling, Authentication providers, Cloud Functions triggers, Storage security, Hosting configuration, and operational best practices.
Agent Protocol
Trigger
User request includes: Firebase, Firestore, Firebase Auth, Cloud Functions, Firebase Storage, Firebase Hosting, security rules, Firebase Admin, Firebase Extensions, Firebase App Check, Firebase Remote Config, Firebase emulator, Firebase cost.
Input Context
- All Firebase capabilities needed (DB, auth, storage, functions, hosting)
- Target platforms (web, iOS, Android, Node.js admin)
- Estimated user/request scale
- Auth providers (email, Google, Apple, custom)
Output Artifact
Firebase project architecture, security rules, data model, function triggers, hosting config.
Response Format
Produce artifact directly. No preamble, no postamble, no explanations. No filler, no hedging, no transitions. Strip articles a/an/the where unambiguous. Compress output — why use many token when few do trick.
Completion Criteria
- Firestore data model designed (collections, documents, indexes, subcollections)
- Security rules defined (read/write/validate per collection)
- Auth providers configured (web + mobile SDK setup)
- Cloud Functions triggers mapped (onCreate, onUpdate, onDelete, onRequest, scheduled)
- Storage security rules + Hosting config (rewrites, headers, redirects)
- Cost optimization plan (read/write counts, indexes, function timeout/memory)
Max Response Length
4096 tokens
Decision Tree
Firestore vs Realtime Database?
What data access pattern do you need?
├── Complex queries, filtering, sorting, transactions
│ └── Firestore — rich querying, multi-collection, auto-scaling
├── Low-latency real-time sync, simple key-value data
│ └── Realtime Database — lower latency, simpler pricing (bandwidth), WebSocket-native
└── I need both
└── Use Firestore for structured data, RTDB for presence/live cursors
What ships with it
6 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.
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.
- 6d ago First seen · 597 lines · 91 tokens per session scan A e6cdf0212e2d
firebase is a skill published in the GitHub repository j4flmao/agent-skills (22 stars, last pushed 3d ago), licensed MIT. It adds 91 tokens to every session and 5,228 once invoked, about $0.0005 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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