Contents

Chapter 1

Chapter 1: Prompt Template System

Template Architecture

The Prompt Engineering Kit provides eight structured prompt templates

organized by reasoning strategy. Each template is a Jinja-like text file

with {placeholder} variables, chain-of-thought scaffolding, and optional

few-shot examples.

Template Structure

templates/
├── zero-shot/
│   ├── summarize.txt
│   └── classify.txt
├── few-shot/
│   ├── code-review.txt
│   └── extract-entities.txt
├── chain-of-thought/
│   ├── solve-math.txt
│   └── debug-reasoning.txt
├── role-play/
│   └── interview-trainer.txt
└── structured-output/
    └── json-extract.txt

Building a Prompt

bash
python src/prompt_engineering_kit.py --build code-review --vars \
  '{"language":"python","context":"auth microservice","focus":"security"}'

This produces a formatted prompt ready to paste into any LLM chat interface:

You are a senior engineer reviewing Python code for an auth microservice.
Focus specifically on security vulnerabilities.

Code:
[code to review]

Checklist:
- Injection vulnerabilities
- Authentication bypasses
- Hardcoded credentials
- Input validation gaps
- Proper error handling

Variable Injection

The kit validates all placeholders at build time. Missing variables produce

a clear error listing exactly which template fields need values:

bash
python src/prompt_engineering_kit.py --build summarize --vars '{}'
# Error: Template 'summarize' requires: text, length, style

Prompt Scoring

The quality analyzer rates prompts on a 0-100 scale across four dimensions:

bash
python src/prompt_engineering_kit.py --score "Explain quantum computing simply"
# Length:  42/100  (too short — expand the prompt)
# Clarity: 78/100  (decent, but define "quantum computing")
# Structure: 35/100 (add sections for depth, audience, format)
# Specificity: 12/100 (no constraints on format or depth)

For multi-step reasoning chains, see 02_chain-of-thought-templates.md.

Chapter 2

Project Structure

Follow this guide to get Prompt Engineering Kit up and running in your environment.

Project Structure

prompt-engineering-kit/
├── README.md
├── LICENSE
├── src/
│   └── prompt_engineering_kit.py    # Core engine (~400 lines)
└── examples/
    ├── basic_usage.py               # Programmatic usage example
    └── custom_templates.json        # Sample custom template library

CLI Reference

FlagDescription
--listList all templates and chains
--template NAMEShow a specific template
--build NAME --vars JSONBuild a prompt from a template
--chain NAME --vars JSONRender a multi-step prompt chain
--score "TEXT"Score a prompt string for quality
--score-file FILEScore a prompt loaded from a file
--export-library FILEExport the full library to JSON
Chapter 3
🔒 Available in full product

Built-in Templates

Chapter 4
🔒 Available in full product

FAQ

You’ve reached the end of the free preview

Get the full Prompt Engineering Kit and unlock everything.

All Chapters

Get the complete guide with every chapter unlocked, including code samples, diagrams, and best practices.

Full Tool Suite

Access all interactive tools with complete data, all workload profiles, and the full scenario library.

Source Files

Downloadable source code, configuration files, and working examples from every chapter.

Lifetime Updates

Free updates for life. Every new chapter, tool, and improvement included.

Buy Now — $29 →
📦 Free sample included — download another copy for the full product.
Prompt Engineering Kit v1.0.0 — Free Preview