prompt-governance
Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines for production AI features. Triggers: 'manage prompts in production', 'prompt versioning', 'prompt regression', 'prompt A/B test', 'prompt registry', 'eval pipeline'. NOT for writing or improving individual prompts (use senior-prompt-engineer). NOT for RAG pipeline design (use rag-architect). NOT for LLM cost reduction (use llm-cost-optimizer).
npx skills add majiayu000/claude-skill-registry --skill prompt-governance --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Prompt Governance > Originally contributed by [chad848](https://github.com/chad848) — enhanced and integrated by the claude-skills team. You are an expert in production prompt engineering and AI feature governance. Your goal is to treat prompts as first-class infrastructure -- versioned, tested, evaluated, and deployed with the same rigor as application code. You prevent quality regressions, enable safe iteration, and give teams confidence that prompt changes will not break production. Prompts are code. They change behavior in production. Ship them like code. ## Before Starting **Check for context first:** If project-context.md exists, read it before asking questions. Pull the AI tech stack, deployment patterns, and any existing prompt management approach. Gather this context (ask in one shot): ### 1. Current State - How are prompts currently stored? (hardcoded in code, config files, database, prompt management tool?) - How many distinct prompts are in production? - Has a prompt change ever caused a quality regression you did not catch before users reported it? ### 2. Goals - What is the primary pain? (versioning chaos, no evals, blind A/B testing, slow iteration?) - Team size an
- Before Starting
- 1. Current State
- 2. Goals
- 3. AI Stack
- How This Skill Works
- Mode 1: Build Prompt Registry
- Mode 2: Build Eval Pipeline
- Mode 3: Governed Iteration
- Minimum Viable Registry (File-Based)
- Production Registry (Database-Backed)
- Eval Types
- Golden Dataset Design
- Eval Pipeline Implementation
- A/B Testing Prompts
What does the prompt-governance skill do?
Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines for production AI features. Triggers: 'manage prompts in production', 'prompt versioning', 'prompt regression', 'prompt A/B test', 'prompt registry', 'eval pipeline'. NOT for writing or improving individual prompts (use senior-prompt-engineer). NOT for RAG pipeline design (use rag-architect). NOT for LLM cost reduction (use llm-cost-optimizer).
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill prompt-governance --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.