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Firebase Ai Logic

Listed
just-mpm·vlatest·backend·MIT

Helps with Firebase, AI as part of developing backend services and APIs workflows.

Repository

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This skill no longer installs under the name firebase-ai-logic. just-mpm/conformai is deleted or private, so it cannot be installed from.

We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-24. We don't show a command we know will fail.

Repository install instructions

What we know about this skill

Publisher

just-mpm

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: slow-api.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    slow-api.comundeclared

    What it found

    • .claude/skills/firebase-ai-logic/features/function-calling.md:1050contacts slow-api.com
      const response = await fetch('https://slow-api.com', {

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned just-mpm/conformai at b92eb8e186.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
b92eb8e186
Manifest
.claude/skills/firebase-ai-logic/SKILL.md
Scanned
14 files, 11,128 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill integrates AI logic directly into Firebase projects. It allows you to build and deploy intelligent features within your existing Firebase infrastructure, streamlining development and enhancing application capabilities. The skill provides a framework for connecting AI models with Firebase services like Firestore and Authentication.

When to use it

  • Personalized Content Recommendations: Implement an AI-powered recommendation engine for content displayed in your Firebase app.
  • Automated Moderation: Automatically moderate user-generated content stored in Firestore using AI models.
  • Smart Chatbots: Build a chatbot that leverages AI logic and integrates with Firebase Authentication to provide personalized support.
  • Predictive Analytics: Utilize AI models to predict user behavior or trends based on data stored within your Firebase project.

Key capabilities

  • Firebase Integration
  • AI Logic Deployment
  • Firestore Connectivity
  • Authentication Support

Example prompts

  • "Deploy an AI model for content recommendation in my Firebase app."
  • "Create a rule to automatically moderate user comments using AI."
  • "Integrate this AI chatbot with my Firebase Authentication system."

Tips & gotchas

This skill requires familiarity with both Firebase and basic AI concepts. Ensure your Firebase project is properly configured before attempting to deploy AI logic using this skill.