From prompt-architecture
Guides versioning prompts like code with Git, testing changes via regression/A/B tests, and managing deployments/rollbacks. Useful for prompt engineering workflows to track iterations and avoid regressions.
npx claudepluginhub owl-listener/ai-design-skills --plugin prompt-architectureThis skill uses the workspace's default tool permissions.
Prompts are code. They should be versioned, tested, reviewed, and deployed with the same rigor as software. Treating prompts as casual text that anyone can edit leads to quality regressions, inconsistent behavior, and debugging nightmares.
Analyzes LLM prompt failure modes, generates variants (zero-shot, few-shot, CoT), designs evaluation rubrics, and creates test suites for optimization.
Improves prompts using Anthropic's 4-step workflow. Handles direct text, files, conversation context, iteration; adds XML, chain-of-thought, examples, clear formats.
Designs, tests, versions, and optimizes prompts for LLMs using patterns like zero-shot, few-shot, CoT, ReAct; covers injection prevention, evaluation, and A/B testing.
Share bugs, ideas, or general feedback.
Prompts are code. They should be versioned, tested, reviewed, and deployed with the same rigor as software. Treating prompts as casual text that anyone can edit leads to quality regressions, inconsistent behavior, and debugging nightmares.
Before deploying a prompt change: