ai-engineer
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
56
41%
Does it follow best practices?
Impact
73%
1.17xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./docs/v19.7/configuration/agent/skills_external/antigravity-awesome-skills-main/skills/ai-engineer/SKILL.mdEvaluation results
78%
25%Regulatory Document Intelligence System
Production RAG retrieval pipeline
Approved vector DB
100%
100%
Approved embedding model
0%
100%
Hybrid search
100%
100%
Reranking step
0%
100%
Chunking strategy
100%
87%
Vector index strategy
25%
100%
Safety guardrails
100%
100%
Observability setup
0%
0%
Embedding caching
37%
25%
Structured outputs
100%
100%
Error handling
0%
16%
68%
-2%Customer Support AI API Service
LLM API serving with safety and observability
FastAPI framework
100%
100%
Async processing
100%
100%
Semantic caching
10%
0%
Rate limiting / cost controls
90%
100%
Observability integration
40%
0%
PII detection
90%
100%
Prompt injection guard
100%
100%
Structured I/O
100%
100%
Circuit breaker / fallback
37%
50%
Adversarial tests
100%
100%
Streaming support
0%
0%
75%
11%Automated Competitive Intelligence Agent
Multi-agent orchestration and memory
Approved agent framework
0%
0%
Agent state management
37%
75%
Memory system
70%
100%
Tool integration
90%
100%
Structured tool outputs
62%
87%
Cost controls
90%
100%
Error handling / graceful degradation
90%
100%
Safety guardrails
90%
100%
Observability
10%
0%
Production architecture
100%
100%
Multi-agent specialization
100%
100%
- Repository
- duclm1x1/Dive-Ai
- Commit
20ba150
- Evaluated
- Agent
- Claude Code
- Model
- Claude Sonnet 4.6
Table of Contents
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