prompt-evalEvaluate and improve any AI prompt (`prompt_a`) through a staged, evidence-based pipeline. Functional evaluation checks whether the prompt follows rules, output contracts, quality requirements, and safety boundaries. Optional effect evaluation checks whether outputs work for intended readers through
Install via ClawdBot CLI:
clawdbot install rivin-dong/prompt-evalGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://example.com/trialAudited Apr 17, 2026 · audit v1.0
Generated Aug 5, 2026
An online retailer wants to generate engaging and persuasive product descriptions from customer reviews. The prompt should extract key features, benefits, and emotional appeal from reviews to create compelling copy.
A SaaS company needs to draft empathetic and clear email responses to customer complaints or inquiries. The prompt must handle varying tones and ensure the response addresses the customer's issue while maintaining brand voice.
A creative agency wants to generate catchy and persuasive taglines for a new product launch. The prompt should produce multiple options and evaluate them for memorability and appeal.
A health information website needs to summarize complex medical articles for lay readers. The prompt must ensure accuracy, clarity, and safety, avoiding any harmful or misleading content.
A fintech startup is building a chatbot that provides personalized financial tips. The prompt must handle sensitive data, avoid giving unsafe advice, and maintain a helpful and engaging tone.
Offer basic prompt evaluation for free, but charge for advanced analytics, unlimited test cases, or priority support.
Provide an API for prompt evaluation where businesses pay per evaluation or per test case. Ideal for high-volume users.
Sell annual licenses to large companies for on-premise deployment, custom integrations, and dedicated support.
💬 Integration Tip
Start with the CSV output format for easy analysis, and gradually introduce the JSON backup for deeper programmatic processing.
Scored Sep 21, 2026
This skill should be used when the user asks to "optimize prompts", "design prompt templates", "evaluate LLM outputs", "build agentic systems", "implement RA...
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