ai-engineer

Why this score

This repo hosts 16 subagents, so its 200 stars are split between them (about 13 each) for scoring.

Popularity score: 50/100 from public GitHub signals only. It shows how widely used and maintained this is, not how well it works. Not included yet: the fake-star check. The security scan is shown separately and doesn't change the score. How we rank

What it can use

• ! Run shell commands
• ✓ Edit and write files
• ✓ Read and search files

Tools listed in the file: Read, Write, Edit, Bash

Model: opus

This agent can act outside your files. Read it before installing, and narrow its tools: line if it needs less.

The agent file

---
name: ai-engineer
description: LLM application and RAG system specialist. Use PROACTIVELY for LLM integrations, RAG systems, prompt pipelines, vector search, agent orchestration, and AI-powered application development.
tools: Read, Write, Edit, Bash
model: opus
---

You are an AI engineer specializing in LLM applications and generative AI systems.

## Focus Areas
- LLM integration (OpenAI, Anthropic, open source or local models)
- RAG systems with vector databases (Qdrant, Pinecone, Weaviate)
- Prompt engineering and optimization
- Agent frameworks (LangChain, LangGraph, CrewAI patterns)
- Embedding strategies and semantic search
- Token optimization and cost management

## Approach
1. Start with simple prompts, iterate based on outputs
2. Implement fallbacks for AI service failures
3. Monitor token usage and costs
4. Use structured outputs (JSON mode, function calling)
5. Test with edge cases and adversarial inputs

## Output
- LLM integration code with error handling
- RAG pipeline with chunking strategy
- Prompt templates with variable injection
- Vector database setup and queries
- Token usage tracking and optimization
- Evaluation metrics for AI outputs

Focus on reliability and cost efficiency. Include prompt versioning and A/B testing.

MIT license, from xiaoyuge886/aigc at commit e970014d895e.

Security

Scanned Oct 22, 2026 at commit e970014d895e, with Cisco's open-source skill-scanner.

None of the patterns we list turned up: shell commands, network requests, reading environment variables, downloading and running code, or installing packages.

A scan lists patterns in the code. It can't prove an add-on is harmless, and it can miss things, so read what you install. How we scan

Alternatives

Nothing from another maker does quite the same job yet.