productivity▌

Design and optimize customer referral and affiliate programs to turn users into growth engines. \n \n Covers both customer referral programs (existing users recommending to networks) and affiliate programs (ongoing commission relationships with creators and partners) \n Provides step-by-step referral loop design: trigger moments, share mechanisms, incentive structures (single-sided, double-sided, tiered), and conversion optimization \n Includes A/B testing frameworks, fraud prevention, and measu

Purpose: Enable multiple Claude Code sessions across a team to coordinate and work together without conflicts. Manages shared state, todo claiming, decision syncing, and session awareness.

Use when:

template-skill

Create clear, comprehensive technical documentation for specs, architecture, runbooks, and APIs. \n \n Provides templates and step-by-step guidance for five document types: technical specifications, architecture documents, runbooks, API documentation, and changelogs \n Includes audience-specific writing strategies for developers, operations teams, managers, and end users with tailored content focus \n Offers visual aid support via Mermaid diagrams, flowcharts, tables, and code examples with synt

Evaluate code review feedback with technical rigor before implementing, avoiding performative agreement and blind implementation. \n \n Verify feedback against actual codebase behavior, test coverage, and architectural context before proceeding \n Ask for clarification on unclear items before implementing anything; partial understanding leads to wrong fixes \n Push back on suggestions that break functionality, lack context, violate YAGNI, or conflict with established decisions using technical re

Generate structured, AI-optimized specification documents with standardized templates and machine-readable formatting. \n \n Creates specification files in /spec/ directory following naming convention spec-[purpose]-[type].md with YAML front matter for metadata \n Enforces structured markdown with 11 standard sections covering purpose, requirements, interfaces, acceptance criteria, and validation \n Includes explicit guidelines for unambiguous language, acronym definitions, and self-contained do

Analyze and redesign features to match your design system standards and ensure consistency. \n \n Requires upfront design system discovery—searches for documentation, UI guidelines, and design tokens before making changes; asks clarifying questions rather than guessing at principles \n Systematically normalizes typography, color, spacing, components, motion, responsive behavior, and accessibility across eight key dimensions \n Prioritizes UX consistency and usability over visual polish; replaces

Web search and content extraction via Tavily and Exa APIs through inference.sh CLI. \n \n Five search and extraction apps: Tavily Search Assistant (AI-powered answers with sources), Tavily Extract (multi-URL content extraction), Exa Search (smart web search), Exa Answer (direct factual responses), and Exa Extract (web page analysis) \n Designed for research workflows, RAG pipelines, fact-checking, and content aggregation with LLM integration examples \n Requires inference.sh CLI ( infsh ) instal

Design or improve onboarding flows that get users to their \"aha moment\" quickly and successfully. \n \n Assess onboarding needs by identifying user challenges, experience level, and the key action you want them to take, then define measurable success metrics \n Follow core principles: show don't tell, make it optional, prioritize time to value, teach contextually, and respect user intelligence \n Design for multiple contexts: initial product onboarding (welcome, setup, core concepts, first suc