YaroslavKomarov
23 verified skills
ai-factory
Set up Claude Code context for a project. Analyzes tech stack, installs relevant skills from skills.sh, generates custom skills, and configures MCP servers. Use when starting new project, setting up AI context, or asking "set up project", "configure AI", "what skills do I need".
tools
ai-factory.architecture
Software architecture patterns and guidelines. Covers Clean Architecture, DDD, microservices, monoliths, and how to choose the right approach. Use when designing systems, refactoring, asking "how should I structure", "which architecture", "monolith vs microservices".
development
ai-factory.best-practices
Code quality guidelines and best practices for writing clean, maintainable code. Covers naming, structure, error handling, testing, and code review standards. Use when writing code, reviewing, refactoring, or asking "how should I name this", "best practice for", "clean code".
development
ai-factory.ci
Generate CI/CD pipeline (GitHub Actions / GitLab CI) with linting, static analysis, tests, security. Use when user says "ci", "setup ci", "github actions", "gitlab ci", "pipeline".
development
ai-factory.build-automation
Analyze project and generate or enhance build automation file (Makefile, Taskfile.yml, Justfile, Magefile.go). If a build file already exists, improves it by adding missing targets and best practices. Use when user says "generate makefile", "create taskfile", "add justfile", "setup mage", or "build automation".
tools
ai-factory.commit
Create conventional commit messages by analyzing staged changes. Generates semantic commit messages following the Conventional Commits specification. Use when user says "commit", "save changes", or "create commit".
testing
ai-factory.implement
Execute implementation tasks from the current plan. Works through tasks sequentially, marks completion, and preserves progress for continuation across sessions. Use when user says "implement", "start coding", "execute plan", or "continue implementation".
data-ai
ai-factory.improve
Refine and enhance an existing implementation plan with a second iteration. Re-analyzes the codebase, checks for gaps, missing tasks, wrong dependencies, and improves the plan quality. Use after /ai-factory.task or /ai-factory.feature to polish the plan before implementation.
development
ai-factory.dockerize
Analyze project and generate Docker configuration: Dockerfile (multi-stage dev/prod), compose.yml, compose.override.yml (dev), compose.production.yml (hardened), and .dockerignore. Includes production security audit. Use when user says "dockerize", "add docker", "docker compose", "containerize", or "setup docker".
development
ai-factory.docs
Generate and maintain project documentation. Creates a lean README as a landing page with detailed docs/ directory split by topic. Use when user says "create docs", "write documentation", "update docs", "generate readme", or "document project".
documentation
ai-factory.feature
End-to-end feature development. Creates git branch, plans implementation via /ai-factory.task, then executes via /ai-factory.implement — full cycle without manual steps. Use when user says "new feature", "start feature", "implement feature", or "add feature".
development
ai-factory.fix
Fix a specific bug or problem in the codebase. Supports two modes - immediate fix or plan-first. Without arguments executes existing FIX_PLAN.md. Always suggests test coverage and adds logging. Use when user says "fix bug", "debug this", "something is broken", or pastes an error message.
development
ai-factory.verify
Verify completed implementation against the plan. Checks that all tasks were fully implemented, nothing was forgotten, code compiles, tests pass, and quality standards are met. Use after "/ai-factory.implement" completes, or when user says "verify", "check work", "did we miss anything".
development
ai-factory.deploy
Prepare and execute deployments with pre-flight checks, release notes generation, and CI/CD integration. NEVER auto-deploy. Use when user explicitly says "deploy", "release", or "go live".
development
ai-factory.evolve
Self-improve AI Factory skills based on project context, accumulated patches, and codebase patterns. Analyzes what went wrong, what works, and enhances skills to prevent future issues. Use when you want to make AI smarter for your project.
development
.claude/skills/grammy-patterns
# Grammy Patterns Patterns and conventions for building Telegram bots with the Grammy framework (TypeScript). ## Core Concepts ### Bot Initialization ```typescript import { Bot, Context, session } from "grammy"; import { conversations, createConversation } from "@grammyjs/conversations"; // Extend context with session and conversations type SessionData = { step?: string }; type MyContext = Context & ConversationFlavor & SessionFlavor<SessionData>; const bot = new Bot<MyContext>(process.env
development
ai-factory.review
Perform code review on staged changes or a pull request. Checks for bugs, security issues, performance problems, and best practices. Use when user says "review code", "check my code", "review PR", or "is this code okay".
development
ai-factory.skill-generator
Generate professional Agent Skills for Claude Code and other AI agents. Creates complete skill packages with SKILL.md, references, scripts, and templates. Use when creating new skills, generating custom slash commands, or building reusable AI capabilities. Validates against Agent Skills specification.
development
.claude/skills/google-calendar
# Google Calendar Patterns Patterns for integrating Google Calendar API in this project. Used to sync the daily plan: each activity period → a calendar event with tasks in the description. ## OAuth Setup ### 1. Get credentials (Google Cloud Console) - Create OAuth 2.0 Client ID (Web application) - Add redirect URI: `https://your-domain/auth/google/callback` - Download credentials → set env vars ### 2. OAuth client ```typescript // src/calendar/auth.ts import { google } from "googleapis"; e
tools
.claude/skills/supabase-ts
# Supabase TypeScript Patterns Patterns for using Supabase with TypeScript in this project. Uses **service role key** (server-side only). Tables are prefixed `sch_`. ## Client Setup ```typescript // src/db/client.ts import { createClient } from "@supabase/supabase-js"; import type { Database } from "./types"; // generated types export const supabase = createClient<Database>( process.env.SUPABASE_URL!, process.env.SUPABASE_SERVICE_ROLE_KEY!, // server-side only, bypasses RLS { auth:
tools
ai-factory.task
Create a step-by-step implementation plan for a feature or task. Breaks down work into actionable tasks tracked via the task system. Use when user says "plan", "create tasks", "break down", or "make a plan for".
data-ai
.claude/skills/openrouter-llm
# OpenRouter LLM Patterns Patterns for using OpenRouter API in this project: NLU/parsing with a lightweight model, plan generation and dialogs with a strong model. ## Client Setup ```typescript // src/llm/client.ts import OpenAI from "openai"; // OpenRouter is OpenAI-compatible export const openrouter = new OpenAI({ baseURL: "https://openrouter.ai/api/v1", apiKey: process.env.OPENROUTER_API_KEY!, defaultHeaders: { "HTTP-Referer": "https://schedulerbot", // required by OpenRouter
tools
ai-factory.security-checklist
Security audit checklist based on OWASP Top 10 and best practices. Covers authentication, injection, XSS, CSRF, secrets management, and more. Use when reviewing security, before deploy, asking "is this secure", "security check", "vulnerability".
testing