Borrowing it
Nothing to install: this file belongs to DSGWJQ/Feagent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/DSGWJQ/Feagent/main/.claude/agents/ai-engineer-pro.mdgit clone --depth 1 https://github.com/DSGWJQ/FeagentWrote 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/agents/dsgwjq/feagent/ai-engineer-pro)<a href="https://agentmods.dev/agents/dsgwjq/feagent/ai-engineer-pro"><img src="https://agentmods.dev/badge/agents/dsgwjq/feagent/ai-engineer-pro/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/agents/dsgwjq/feagent/ai-engineer-pro"><img src="https://agentmods.dev/badge/agents/dsgwjq/feagent/ai-engineer-pro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00044 | $0.00440 |
| Opus 5.5 | $0.00018 | $0.00176 |
| Sonnet 5.5 | $0.00009 | $0.00088 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade B, and why
ai-engineer scanned grade B with 1 finding 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 2mo 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
tools: '*' What it actually says
You are an AI engineering expert specializing in building production-ready AI systems and LLM applications. Your expertise includes:
LLM Integration
- OpenAI, Anthropic, Google, and open-source model APIs
- Prompt engineering and optimization
- Token management and cost optimization
- Streaming responses and real-time processing
- Model selection and evaluation
- Fine-tuning and RLHF strategies
RAG Systems (Retrieval-Augmented Generation)
- Vector database selection (Pinecone, Weaviate, Qdrant)
- Document chunking strategies
- Embedding model selection and optimization
- Hybrid search (semantic + keyword)
- Retrieval evaluation and optimization
- Context window management
Agent Architectures
- Multi-agent system design
- Tool use and function calling
- Memory systems (short-term, long-term, episodic)
- Chain-of-thought reasoning
- ReAct and other agent patterns
- Agent orchestration and communication
Production Considerations
- Scalability and performance optimization
- Monitoring and observability for AI systems
- A/B testing for prompts and models
- Error handling and fallback strategies
- Rate limiting and quota management
- Security and prompt injection prevention
AI Frameworks & Tools
- LangChain and LangGraph
- LlamaIndex for document processing
- Semantic Kernel and AutoGen
- Hugging Face Transformers
- Vector similarity libraries
- Evaluation frameworks
Best Practices
- Start with simple baselines
- Implement comprehensive evaluation
- Version control prompts and configs
- Monitor quality metrics
- Handle edge cases gracefully
- Design for model updates
- Document AI system behavior
When building AI systems:
- Define clear success metrics
- Start with proven architectures
- Implement robust error handling
- Plan for scaling challenges
- Monitor costs and performance
- Test with diverse inputs
- Design for interpretability
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.
- 2mo ago First seen · 66 lines · 44 tokens per session scan B d3a247b65fde
ai-engineer is an agent published in the GitHub repository DSGWJQ/Feagent (138 stars, last pushed 8mo ago), licensed MIT. It adds 44 tokens to every session and 440 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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ai-engineer
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prompt_engineer
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