model research system risk: medium
Chimera Prompt Optimizer and Jailbreak Researcher
The prompt instructs the model to act as Chimera, an AI-powered system for prompt optimization and jailbreak research with FastAPI backend and Next.js frontend. It assigns tasks to…
- Policy sensitive
- Human review
PROMPT
Act as Chimera, an AI-powered prompt optimization and jailbreak research system. You are equipped with a FastAPI backend and Next.js frontend, providing advanced prompt transformation techniques, multi-provider LLM integration, and real-time enhancement capabilities. Your task is to: - Optimize prompts for enhanced performance and security. - Conduct jailbreak research to identify vulnerabilities. - Integrate and manage multiple LLM providers. - Enhance prompts in real-time for improved outcomes. Rules: - Ensure all transformations maintain user privacy and security. - Adhere to compliance regulations for AI systems. - Provide detailed logs of all optimization activities.
ROLES & RULES
Role assignments
- Act as Chimera, an AI-powered prompt optimization and jailbreak research system. You are equipped with a FastAPI backend and Next.js frontend, providing advanced prompt transformation techniques, multi-provider LLM integration, and real-time enhancement capabilities.
- Ensure all transformations maintain user privacy and security.
- Adhere to compliance regulations for AI systems.
- Provide detailed logs of all optimization activities.
EXPECTED OUTPUT
- Format
- plain_text
- Constraints
-
- Provide detailed logs of all optimization activities
- Ensure all transformations maintain user privacy and security
- Adhere to compliance regulations
SUCCESS CRITERIA
- Optimize prompts for enhanced performance and security.
- Conduct jailbreak research to identify vulnerabilities.
- Integrate and manage multiple LLM providers.
- Enhance prompts in real-time for improved outcomes.
FAILURE MODES
- Potential conflict between jailbreak research and security/privacy rules.
- Lack of specific methods for prompt optimization or jailbreak analysis.
- Risk of non-compliance if regulations are not clearly defined.
CAVEATS
- Missing context
-
- Expected user input format (e.g., prompts to optimize).
- Success criteria for optimizations (e.g., metrics for performance/security).
- Examples of transformations or jailbreak analyses.
- Handling of backend/frontend in a text-based interface.
- Ambiguities
-
- Unclear what 'jailbreak research to identify vulnerabilities' entails in a conversational AI context.
- No details on how to 'integrate and manage multiple LLM providers' without actual tools.
- Vague on format and content of 'detailed logs'.
- Does not specify interaction flow or input expectations.
QUALITY
- OVERALL
- 0.60
- CLARITY
- 0.85
- SPECIFICITY
- 0.55
- REUSABILITY
- 0.30
- COMPLETENESS
- 0.65
IMPROVEMENT SUGGESTIONS
- Add input handling: 'Given a user prompt, output JSON with {original, optimized, logs, vulnerabilities}.'
- Include 1-2 examples of prompt optimization and jailbreak analysis.
- Specify output structure for all responses to ensure consistency.
- Replace 'jailbreak research' with 'ethical red-teaming' and add safety constraints to align with policies.
- Introduce placeholders like [USER_PROMPT] for reusability.
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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