prompt-engineer-toolkit

# Prompt Engineer Toolkit

## Overview

Use this skill to move prompts from ad-hoc drafts to production assets with repeatable testing, versioning, and regression safety. It emphasizes measurable quality over intuition. Apply it when launching a new LLM feature that needs reliable outputs, when prompt quality degrades after model or instruction changes, when multiple team members edit prompts and need history/diffs, when you need evidence-based prompt choice for production rollout, or when you want consistent prompt governance across environments.

## Core Capabilities

- A/B prompt evaluation against structured test cases
- Quantitative scoring for adherence, relevance, and safety checks
- Prompt version tracking with immutable history and changelog
- Prompt diffs to review behavior-impacting edits
- Reusable prompt templates and selection guidance
- Regression-friendly workflows for model/prompt updates

## Key Workflows

### 1. Run Prompt A/B Test

Prepare JSON test cases and run:

```bash
python3 scripts/prompt_tester.py \
  --prompt-a-file prompts/a.txt \
  --prompt-b-file prompts/b.txt \
  --cases-file testcases.json \
  --runner-cmd 'my-llm-cli --prompt {prompt} --input {input}' \
  --format text
```

Input can also come from stdin/`--input` JSON payload.

### 2. Choose Winner With Evidence

The tester scores outputs per case and aggregates:

- expected content coverage
- forbidden content violations
- regex/format compliance
- output length sanity

Use the higher-scoring prompt as candidate baseline, then run regression suite.

### 3. Version Prompts

```bash
# Add version
python3 scripts/prompt_versioner.py add \
  --name support_classifier \
  --prompt-file prompts/support_v3.txt \
  --author alice

# Diff versions
python3 scripts/prompt_versioner.py diff --name support_classifier --from-version 2 --to-version 3

# Changelog
python3 scripts/prompt_versioner.py changelog --name support_classifier
```

### 4. Regression Loop

1. Store baseline version.
2. Pr...

# Prompt Engineer Toolkit

Production toolkit for evaluating and versioning prompts with measurable quality signals. Includes A/B testing automation and prompt history management with diffs.

## Quick Start

```bash
# Run A/B prompt evaluation
python3 scripts/prompt_tester.py \
  --prompt-a-file prompts/a.txt \
  --prompt-b-file prompts/b.txt \
  --cases-file testcases.json \
  --format text

# Store a prompt version
python3 scripts/prompt_versioner.py add \
  --name support_classifier \
  --prompt-file prompts/a.txt \
  --author team
```

## Included Tools

- `scripts/prompt_tester.py`: A/B testing with per-case scoring and aggregate winner
- `scripts/prompt_versioner.py`: prompt history (`add`, `list`, `diff`, `changelog`) in local JSONL store

## References

- `references/prompt-templates.md`
- `references/technique-guide.md`
- `references/evaluation-rubric.md`

## Installation

### Claude Code

```bash
cp -R marketing-skill/prompt-engineer-toolkit ~/.claude/skills/prompt-engineer-toolkit
```

### OpenAI Codex

```bash
cp -R marketing-skill/prompt-engineer-toolkit ~/.codex/skills/prompt-engineer-toolkit
```

### OpenClaw

```bash
cp -R marketing-skill/prompt-engineer-toolkit ~/.openclaw/skills/prompt-engineer-toolkit
```