Generates robust, multi-AI validated software specifications to surface architectural blindspots before development begins.
The flow-spec skill for Claude Code automates the creation of high-fidelity NLSpec documentation by leveraging a multi-model consensus approach. By orchestrating research across up to 8 different AI models, it identifies edge cases, hidden constraints, and complex behaviors that a single model might overlook. The skill follows a rigorous 8-step execution contract including mandatory clarifying questions, multi-provider synthesis via the Octopus engine, and an adversarial completeness challenge to ensure your project requirements are production-ready and technically sound.
주요 기능
01Automated NLSpec Template Generation
02State-Managed Design Workflows
03Adversarial Spec Review Mode
043,352 GitHub stars
05Complexity-Aware Acceptance Criteria
06Multi-AI Consensus Research
사용 사례
01Generating structured documentation for system stakeholders
02Defining complex feature behaviors and edge cases
03Performing architectural research across multiple AI providers
