cove-prompt-design
Explain how and when to use Chain of Verification (CoVe) in prompt design. Use when designing prompts that require factual accuracy, self checking, or reduction of hallucinations.
npx skills add majiayu000/claude-skill-registry --skill cove-prompt-design --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.
# Chain of Verification (CoVe) for Prompt Design This skill documents **what CoVe is**, **when to use it**, and **how to apply it correctly** in prompt design. CoVe is a prompt design pattern that improves factual reliability by separating _generation_ from _verification_. The model first produces an answer, then independently verifies that answer through structured checks, and finally produces a corrected or confirmed result. This is **not** chain of thought exposure. The verification steps are explicit instructions, not hidden reasoning. --- ## What CoVe Is Chain of Verification (CoVe) is a structured prompting approach with three phases: 1. **Initial answer generation** 2. **Independent verification questions** 3. **Final validated answer** The key idea is that the model should not assume its first answer is correct. It must actively test it. --- ## When to Use CoVe Use CoVe when **any of the following are true**: - The task requires factual accuracy (dates, specs, standards, APIs). - Hallucinations would be costly or misleading. - The answer depends on multiple independent facts. - The model may rely on weak priors or pattern completion. - You want the model to challenge its ow
- What CoVe Is
- When to Use CoVe
- Core CoVe Structure
- Verification Question Design Rules
- Example: Without CoVe
- Example: With CoVe
- CoVe vs Chain of Thought
- Failure Modes to Watch For
- Practical Prompt Template
- Output Control
- Summary
What does the cove-prompt-design skill do?
Explain how and when to use Chain of Verification (CoVe) in prompt design. Use when designing prompts that require factual accuracy, self checking, or reduction of hallucinations.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill cove-prompt-design --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.