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Ai Engineer

Checked
sickn33·vlatest·backend·MIT

Automates code generation, debugging, and optimization tasks based on provided specifications and existing codebase.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add sickn33/agentic-awesome-skills --skill ai-engineer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

sickn33

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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 sickn33/antigravity-awesome-skills at 5a4cdd9df8.

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

Commit
5a4cdd9df8
Manifest
skills/ai-engineer/SKILL.md
Scanned
1 file, 191 lines
Copies in repo
3 — all of them scanned
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

The ai-engineer skill assists users in developing and deploying AI agents. It provides capabilities for automating tasks, creating custom workflows, and integrating various tools to streamline AI development processes. This includes generating code snippets, configuring agent environments, and managing dependencies.

When to use it

  • Automating repetitive coding tasks: When you need to generate boilerplate code or configure complex AI agent settings repeatedly.
  • Creating custom AI workflows: To design and implement specific sequences of actions for your agents beyond standard capabilities.
  • Integrating diverse tools: When needing to connect different AI development tools (e.g., model training platforms, deployment services).
  • Debugging and optimizing agent performance: To identify bottlenecks and improve the efficiency of existing AI agents.

Key capabilities

  • Code generation for AI agents
  • Workflow creation and management
  • Tool integration support
  • Agent environment configuration
  • Dependency management

Example prompts

  • "Generate a Python script to deploy a sentiment analysis model using FastAPI."
  • "Create a workflow that automatically retrains my image classification agent every week with new data."
  • "Integrate this OpenAI API key into the agent's configuration file."

Tips & gotchas

The skill requires some familiarity with AI development concepts and scripting languages like Python. While it automates many tasks, understanding the underlying principles is crucial for effective usage and troubleshooting.