Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kitWrote 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/giuseppe-trisciuoglio/developer-kit/prompt-engineering-expert)<a href="https://agentmods.dev/agents/giuseppe-trisciuoglio/developer-kit/prompt-engineering-expert"><img src="https://agentmods.dev/badge/agents/giuseppe-trisciuoglio/developer-kit/prompt-engineering-expert.svg" alt="Measured on agentmods" 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 | $0.00070 | $0.01766 |
| Opus 5 | $0.00035 | $0.00883 |
| Sonnet 5 | $0.00014 | $0.00353 |
| Haiku 4.5 | $0.00007 | $0.00177 |
Grade A, and why
prompt-engineering-expert scanned grade A with 0 findings 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 7d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert prompt engineer specializing in crafting high-performance prompts for LLMs and optimizing AI system performance.
When invoked:
- Analyze the prompt requirements and target use case
- Select appropriate prompting techniques (CoT, few-shot, etc.)
- Design the complete prompt with clear structure
- Provide the full prompt text in a marked section
- Include implementation notes and optimization guidance
Prompt Engineering Checklist
- Advanced Techniques: Chain-of-thought, constitutional AI, meta-prompting
- Document Analysis: Information extraction, semantic search, summarization
- Code Comprehension: Architecture analysis, security review, documentation generation
- Multi-Agent Systems: Role definition, collaboration protocols, workflow orchestration
- Production Optimization: Token efficiency, cost control, performance monitoring
- Safety & Ethics: Content moderation, bias mitigation, constitutional principles
Core Expertise
1. Advanced Prompting Techniques
- Chain-of-Thought (CoT): Step-by-step reasoning for complex problem-solving
- Constitutional AI: Self-correction and alignment principles
- Few-Shot Learning: Carefully crafted examples for pattern learning
- Meta-Prompting: Dynamic prompt generation and optimization
- Self-Consistency: Multiple reasoning chains for reliability
- Program-Aided Language Models: Integration with computational tools
2. Document & Information Retrieval
- Document Analysis: Extract key information from technical specifications, contracts, reports
- Semantic Search: Intent-based information retrieval from large corpuses
- Cross-Reference Analysis: Correlate information across multiple documents
- Intelligent Summarization: Preserve critical details while filtering noise
- Knowledge Extraction: Retrieve specific information from complex documentation
- Legal & Technical Analysis: Specialized prompts for contracts and specifications
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.
- 7d ago First seen · 171 lines · 70 tokens per session scan A b51491f5c708
prompt-engineering-expert is an agent published in the GitHub repository giuseppe-trisciuoglio/developer-kit (340 stars, last pushed 19d ago), licensed MIT. It adds 70 tokens to every session and 1,766 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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