Skill UI

This protocol defines the structured communication rules for multiple specialized AI agents simulating C-suite roles (e.g., CFO, CTO, CRO). It dictates invocation syntax, response formatting, and enforces strict constraints (such as loop prevention, call depth limits, and isolation rules) to ensure coordinated, non-contradictory, and reliable cross-functional analysis for executive decision-making.

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

This pattern defines a robust, continuous loop structure for autonomous agents. It integrates crucial components like quality gates, evaluation harnesses, and explicit recovery controls. It guides complex workflows by defining decision paths (e.g., PR control, RFC decomposition) and includes strategies to mitigate common failure modes such as infinite loop churn or cost drift, ensuring measurable progress in autonomous systems.

This comprehensive guide provides advanced troubleshooting workflows for complex, microservices-based environments running on Kubernetes. It covers diagnosing issues like CrashLoopBackOff, cascade failures, resource pressure (CPU/Memory), and detailed Redis state analysis, ensuring systematic root cause identification across multiple services.

A specialized review tool for identifying critical performance bottlenecks within Django applications. It focuses on validating issues such as N+1 queries, unbounded querysets, missing database indexes, and write loops. Use this when you suspect database slowdowns or memory exhaustion due to inefficient ORM usage, ensuring findings are provable and actionable.

Master common data transformations using functional programming patterns in TypeScript. This guide covers essential techniques for arrays, objects, and complex data structures, including mapping, filtering, reducing, grouping, and safely accessing nested values. It teaches how to replace verbose, imperative loops with concise, declarative functional code, improving readability and maintainability.

Guides growth engineers through designing, launching, or optimizing referral and affiliate systems, covering loop mechanics, incentives, triggers, sharing, and measurement to turn customers into acquisition engines.

This skill provides a systematic methodology for iteratively improving complex skill documentation. By utilizing a reviewer agent, it identifies and categorizes issues (Critical, Major, Minor) in a structured loop. The process ensures that the skill meets high standards of quality, reliability, and functional completeness before deployment, moving beyond simple manual edits.

Autonomous frontend builders follow a Stitch-driven baton loop to read prompts, generate and integrate pages, refresh documentation, and hand off the next task for continuous site evolution.

A comprehensive toolkit for accelerating digital product growth. It covers essential strategies including growth hacking, SEO/ASO optimization, building viral loops, email marketing funnels, CRM implementation, and analyzing the entire customer acquisition lifecycle using AARRR metrics. Ideal for product managers and marketers aiming for exponential business expansion.

This comprehensive framework guides the design of sustainable motivation systems for products and teams, shifting focus from outdated 'carrot-and-stick' rewards to intrinsic drivers: Autonomy, Mastery, and Purpose (AMP). It provides deep insights into how to build engaging, lasting user loops and organizational incentives that foster genuine engagement and high performance, especially when traditional gamification fails.

This framework outlines the 'Hook Model' (Trigger, Action, Variable Reward, Investment) for building deeply engaging, habit-forming product loops. It guides designers in optimizing user retention, understanding behavioral psychology, and structuring product features to move users from deliberate usage to automatic, routine behavior. Use it for onboarding, feature design, and improving long-term user stickiness.