Skill UI

This skill mines offline Telegram Desktop chat exports (result.json) to identify unmet market needs and product opportunities. It uses chunked streaming to prevent memory crashes on large files and ensures verbatim quote grounding for accuracy. It applies cross-chat multiplicity laws to filter noise and hallucinations, supporting both English and Russian lexicons for pain point extraction without network requests.

Deep expert in Claude Code - Anthropic's CLI. Maximizes productivity with shortcuts, hooks, MCPs, advanced configurations, workflows, CLAUDE.md, memory, sub-agents, permissions, and ecosystem integration.

This skill reviews generated or changed production code against Clean Code principles (SOLID, DRY, KISS, YAGNI) and LLM-specific failure modes. It operates in guard-pass, live, and review modes to ensure code quality before delivery, fixing violations and preventing systematic AI errors.

Expert guidance on AWS CloudFormation template optimization, nested stacks, drift detection, and production-ready patterns. Use when writing or reviewing CF templates for maintainability, cost, and safety.

This skill simulates a senior engineer's final, deep audit of an entire codebase before committing or pushing to a remote repository. It systematically checks for junk files, dead code, security vulnerabilities (secrets, injection flaws), and performance bottlenecks (N+1 queries). Use this pre-flight check before any major release or public deployment to ensure maximum code quality and production readiness.

A robust, production-grade REST API gateway designed to wrap ComfyUI servers. It provides comprehensive features including workflow templating, job queuing (with priorities), webhooks, result caching, authentication, and rate limiting. It transforms ComfyUI into a universal, scalable, and secure service for automated image generation pipelines.

Harden Docker and container images with secure base images, non-root users, and CVE scanning. Covers SBOM signing, seccomp, AppArmor, and Kubernetes pod security controls for production deployments.

This skill covers predictable performance degradation patterns in language models as context length increases, including lost-in-middle effects, context poisoning, and distraction. It helps diagnose agent failures and design resilient systems by understanding attention mechanics and context engineering strategies for production environments.

A methodology for managing project context as structured artifacts alongside code to ensure consistent AI interactions and team alignment. It involves defining product vision, tech stack, and workflows before implementation, supporting both new and existing projects.

This skill provides production-tested patterns for building AI agents that autonomously discover, evaluate, and acquire token listings for cryptocurrency exchanges. It covers systematic crypto business development, including multi-chain scanning, token scoring systems, wallet forensics for safety verification, and managing outreach pipelines with human oversight. Built from real-world experience, it teaches LLM cascade patterns and on-chain identity registration.

Generates production-grade Cypress E2E and component tests in JavaScript or TypeScript. Supports local execution and TestMu AI cloud for cross-browser testing. Includes patterns for command chaining, network interception, and custom commands to ensure reliable automation workflows.

A framework for building production-ready, low-latency, multimodal AI agents. It allows developers to orchestrate complex pipelines that seamlessly handle real-time audio, video, and text data. Key capabilities include integrating multiple AI services (LLMs, STT, TTS), managing conversation context, and enabling tool use and function calling for advanced, interactive AI applications.