Micro Saas Launcher

C++ and Rust memory model skill for concurrent programming. Use when understanding memory ordering, writing lock-free data structures, using std::atomic or Rust atomics, diagnosing data races, or selecting the correct memory order for atomic operations. Activates on queries about memory ordering, acquire-release, seq_cst, relaxed atomics, happens-before, memory barriers, std::atomic, or Rust atomic ordering.

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

Reference library of 35+ hook and headline tactic types. Use this when a user asks for hooks organized by tactic, wants to know which tactic to use for a given situation, or requests hooks "by tactic type." This defines what each tactic is and when to deploy it. Always pair with hook-writing for execution — tactics define the frame, psychological triggers are the mechanism inside the frame.

Analytics tracking, interpretation, funnel analysis, product metrics, and ROI measurement. Use when setting up GA4/GTM tracking, interpreting analytics data, analyzing conversion funnels, calculating ROI, or measuring product engagement. Triggers on "analytics," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "funnel analysis," "conversion rates," "user flow," "cohort analysis," "retention," "product metrics," "North Star metric," "ROI," "break-even," "payback period," "investment analysis," "validate my funnel," "why isn't my funnel converting," or "executive financial report." For A/B test setup, see ab-test-setup.

Design and create a new hive task through guided conversation. Walks the user through problem definition, eval design, constraint specification, repo scaffolding, baseline testing with iteration, and upload. Use when user wants to create a new task, add a benchmark, or publish a challenge to the swarm.

Runs real-user dogfooding sessions through the product's public interfaces: a persona walks a journey in the browser, takes a thematic tour, probes edges, hunts paper cuts, and reports what a real user would experience. Reads its plan from the living QA docs tree (<qa-docs-path>, default docs/qa/). Use when validating a release candidate, branch diff, migration, or user-facing change against production-like behavior. For planning that tree — personas, journeys, charters, the bug registry — use qa-report; for CI gate runs, AI implementation audits, or integration/security/performance suites, use agent-output-audit.