Agent skill · writing content · borghei
senior-prompt-engineer
Prompt engineering and LLM evaluation. Use when optimizing prompts, designing prompt templates, evaluating LLM outputs, building agentic systems, implementing RAG, creating few- shot examples, or designing structured-output workflows.
Why this skill is useful
Adds 3 executable scripts for prompt optimization, RAG evaluation, and agent orchestration that extend the AI's capabilities in prompt engineering and evaluation.
What it needs
Requires python installed locally. About 3k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
Senior Prompt Engineer Prompt engineering patterns, LLM evaluation frameworks, and agentic system design. Provides static (deterministic) analysis tools to optimize prompts, evaluate RAG retrieval and generation quality, and validate/visualize agent workflows — plus deep reference libraries of prompt patterns, evaluation metrics, and agent architectures. Core Capabilities Prompt optimization — token counting and cost estimation, clarity/structure scoring, ambiguity and redundancy detection, and generation of optimized prompt versions. Few-shot & structured output design — extract/manage few-shot examples, design diverse example sets (simple/edge/complex/negative), and enforce reliable JSON/XML schema outputs. RAG evaluation — context relevance, answer faithfulness, groundedness (ROUGE-L), and retrieval metrics (Precision@K, MRR, NDCG) over pre-retrieved contexts. Agentic system design — validate agent configs, visualize flows (ASCII/Mermaid), estimate token cost per run, and apply ReAct / Plan-Execute / Tool-Use / multi-agent patterns. Pattern library — 10 prompt patterns, evaluation frameworks (A/B testing, benchmarks, human eval), and agent architectures with pseudocode. When to Use Optimizing an existing prompt's performance or reducing token costs. Designing prompt templates, few-shot examples, or structured-output workflows. Evaluating LLM outputs or RAG retrieval/generation quality. Building or validating agentic systems and tool-calling workflows. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/senior-prompt-engineer