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kitloomlk-stackkitloomlk-stack/mobile-apps-kit/.claude/skills/app-store-optimization/SKILL.md

app-store-optimization

Skill0 starsChanged 29 days agoLicence not identifiedView on GitHub

Improves visibility and conversion in the App Store and Google Play — metadata, keywords, screenshots, ratings, and the listing experience that turns an impression into an install. Use this to audit or optimize an app listing, plan a launch listing, diagnose poor install conversion, or improve store search visibility.

12 other projects use a version of this.

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Projects with it also use ceo-advisor, senior-data-engineer and 2 more.

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  • nek1987Skill

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    Executive leadership guidance for strategic decision-making, organizational development, and stakeholder management. Includes strategy analyzer, financial scenario modeling, board governance frameworks, and investor relations playbooks. Use when planning strategy, preparing board presentations, managing investors, developing organizational culture, making executive decisions, or when user mentions CEO, strategic planning, board meetings, investor updates, organizational leadership, or executive strategy.

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  • nilecuiSkill

    senior-data-engineer

    World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, or implementing data governance.

    Also in 3 projects that use this

  • nahisahoSkill

    database-schema-designer

    Copilot agent for database schema design, ER diagrams, normalization, DDL generation, and performance optimization

    Also in 3 projects that use this

  • JeffallanSkill

    rag-architect

    Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality. Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, context augmentation, similarity search, or embedding-based indexing.

    Also in 3 projects that use this

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