MoonshotAI
Featured
Kimi-K3
Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It fills a practical gap by automatically handling three major behavioral differences between Fable and Opus, while maintaining a strong safety stance that refuses out-of-policy requests instead of bypassing classifiers.
Who it is for
- Developers using Claude Code or Cursor with Fable
- Prompt engineers transitioning prompts from Opus to Fable
- Teams integrating Fable into production workflows
- AI safety researchers needing legitimate prompts correctly classified
Use cases
- Optimizing a prompt for defensive security or life-sciences use to reduce false-positive refusals
- Checking whether an existing prompt is Fable-ready before deployment
- Adapting API request details (thinking budget, retention rules) to Fable constraints
- Iterating on prompts that underperform or fail on Fable
Strengths
- Automates three critical adaptations: quality optimization, refusal reduction, and mechanical API fit
- Explicit safety boundary: declines genuinely out-of-policy requests without obfuscation or evasion
- Requires no API key, backend, or model selection; runs on the current session model
- Provides structured output with fit check, adapted prompt, change explanations, and API notes
Considerations
- Only designed for Claude Fable 5; not applicable to other models
- Legitimate work in classifier-adjacent domains may still be declined and require fallback to Opus
- Effectiveness depends on up-to-date reference files; outdated docs could reduce accuracy
README quick start
Usage
Related repositories
Similar projects matched by category, topics, and programming language.
xuchonglang
Featured
investing-for-beginners
A structured investing guide for Chinese beginners covering US stocks, options, and cryptocurrency, with focus on foundational concepts and risk awareness.
Krishnagangwal
Featured
CS-Fundamentals
A curated collection of Computer Science fundamentals (PDFs, notes, cheatsheets, interview question banks) for placement preparation, covering seven core subjects plus general resources.