product▌

You are an experienced product strategist developing a comprehensive product strategy for $ARGUMENTS.

Purpose: Guide the user through creating a PRODUCT.md that unlocks product-aware reviews in /pre-mortem and /vibe, including the default quick-mode inline paths.

Strategic product leadership toolkit for OKR cascading, market analysis, and organizational design. \n \n Generates cascading OKRs from company level down to product and team levels, with alignment scoring and contribution tracking across five strategy types (growth, retention, revenue, innovation, operational) \n Covers market and competitive analysis, product vision frameworks, and KPI definition for comprehensive strategic planning \n Includes team scaling and organizational design capabiliti

Measure what matters and make data-driven decisions.

Build profitable AI products that solve specific problems, not generic ChatGPT clones. \n \n Covers AI product architecture, prompt engineering for production, model selection, and cost management strategies to balance quality with unit economics \n Includes patterns for input validation, structured output parsing, quality control, and fallback handling to ensure reliable AI responses \n Provides token economics tracking, usage metering, and cost reduction techniques (cheaper models, caching, ba

8 production-ready product skills covering product management, UX/UI design, and SaaS development.

Production-ready LLM integration patterns, from prompt versioning to safety validation and cost optimization. \n \n Covers structured output with schema validation, streaming responses for reduced latency, and prompt versioning with regression testing \n Identifies eight critical sharp edges including output validation, prompt injection risks, context window limits, and API failure handling \n Emphasizes treating prompts as code, validating all LLM outputs, and never trusting responses blindly i

Interactive requirements gathering and professional PRD generation through quality-scored dialogue. \n \n Systematically assesses requirements across five dimensions (business value, functional specs, UX, technical constraints, scope) using a 100-point quality scale, iterating until 90+ threshold before document generation \n Gathers project context by reading existing README and configuration files, then asks targeted clarification questions focused on the lowest-scoring requirement areas \n Ge

Frameworks for building and scaling product operations functions across growing teams. \n \n Bridges product and operations by creating systems that enable PMs to focus on strategy rather than operational overhead like release management, enablement, and cross-functional coordination \n Standardizes processes, tooling, and insights across product teams while preserving PM decision-making authority; product ops informs, not decides \n Addresses common scaling challenges: surfacing user research a

Framework-based assessment of product-market fit using signals from 46 product leaders. \n \n Apply the Sean Ellis \"very disappointed\" survey as a leading PMF indicator, targeting 40% threshold before long-term retention data is available \n Diagnose stage through retention curves, reference customer counts, and customer pull signals; distinguish between vanity metrics and genuine PMF evidence \n Recognize PMF across four levels (nascent to extreme) with segment-specific fit; understand that P