vstorm-co

Building, compiling, and resolving dependency issues across languages

Systematic code review for bugs, security, style, and performance

Working with diverse data formats: binary, text, structured, and custom

Systematic exploration of unknown environments before starting work

Git operations: commits, branches, PRs, and conflict resolution

Writing efficient code that handles large data and tight constraints

Refactor code to improve structure and maintainability

Create new reusable skills from conversation context

Content studio with brand consistency. Use this skill whenever the user wants to create content — blog posts, social media (X/Twitter, LinkedIn, Reddit, HN), presentations (Slidev/Reveal/Spectacle), infographics, image prompts, video scripts (Remotion), editorial calendars, or content audits. Also triggers on brand setup, voice profiling, content repurposing, and content strategy. Covers any request involving writing, publishing, visual content creation, or content planning. Even if the user doesn't say "content" explicitly — if they're asking to write a blog post, create slides, draft a thread, plan a content calendar, or check content quality — use this skill.

Content quality audit with anti-slop detection and brand consistency scoring. Use when user wants to check content quality, audit a draft, score content, verify brand consistency, detect AI-generated patterns, or run a quality check before publishing.

Long-form blog post generation with brand voice integration and anti-slop enforcement. Use when user wants to write a blog post, article, tutorial, case study, opinion piece, deep dive, or listicle.

Editorial calendar planning and content scheduling. Use when user wants to plan a content calendar, create a publishing schedule, organize content across platforms, or plan a content series.

Hacker News post generation for Show HN, Ask HN, and submissions. Use when user wants to post to Hacker News or write a Show HN/Ask HN post.

Image prompt engineering for AI image generation models. Use when user wants to generate images, create image prompts, or optimize prompts for DALL-E, Midjourney, Stable Diffusion, or other image generation tools.

Generate SVG and HTML infographics with brand-aware design. Use when user wants to create an infographic, data visualization, process flow, comparison chart, stat card, or visual data summary.

LinkedIn post generation with professional brand voice adaptation. Use when user wants to create a LinkedIn post, professional update, or LinkedIn content.

Main orchestrator for the production-stack-skills pack. Routes /production subcommands to specialized skills. Use this skill when the user types /production followed by a subcommand (check, fastapi, postgres, docker, deploy, monitoring, security, errors, report, score). Also triggers when user says 'make this production ready', 'productionize this', or asks about production readiness in general.

Full production readiness audit with 0-100 score — scans the entire project across security, error handling, observability, deployment readiness, database patterns, and container hygiene. Launches parallel analysis, classifies findings by severity, and produces a prioritized action plan. Use this skill when user says /production check, /production score, asks 'is this production ready', 'audit this project', 'how production ready is this', or wants a comprehensive codebase health check.

Pre-deployment validation and release management — structured checklists for database migrations, environment variables, rollback plans, backward compatibility, and deployment strategies. Use this skill when the user mentions deploy, release, ship to prod, merge to main, CI/CD pipeline, or says /production deploy. Triggers on deployment-related discussions, release planning, or pre-release validation.

Docker production hardening — multi-stage builds, non-root users, distroless images, BuildKit secrets, layer optimization, security scanning, and compose best practices. Use this skill when the user is creating or modifying Dockerfiles, docker-compose files, .dockerignore, or containerizing applications. Triggers on any Dockerfile, docker-compose.yml, .dockerignore, or when user mentions Docker, containers, or images. Also trigger when user says /production docker.

Production error handling patterns — error taxonomy, retry with exponential backoff, circuit breakers, graceful degradation, dead-letter queues, and structured error logging. Use this skill when the user writes error-prone code (external API calls, database operations, file I/O, network calls), implements retry logic, or asks about resilience patterns. Also trigger when user says /production errors.

Production-grade FastAPI patterns — structured logging, health checks, graceful shutdown, middleware, Pydantic v2, async patterns, error handling, and security hardening. Use this skill when the user is building or modifying a FastAPI application, working with Pydantic models, configuring Starlette middleware, setting up Uvicorn/Gunicorn, or asks about FastAPI best practices. Triggers when importing fastapi, starlette, pydantic, or uvicorn. Also trigger when user says /production fastapi. DO NOT trigger for Django or Flask unless explicitly asked.

Production observability — OpenTelemetry traces, structured logging, metrics, alerting, health endpoints, and SLO definition. Use this skill when the user mentions monitoring, observability, logging, metrics, traces, alerts, SLOs, or says /production monitoring. Triggers on observability discussions, OTEL setup, structured logging configuration, Prometheus/Grafana setup, or alerting rules.

Architecture planning for production systems — guides system design with scalability, reliability, security, and operational concerns from day one. Use this skill when the user asks to plan architecture, design a system, plan a new service, discuss system design, or says 'plan this', 'how should I architect this', 'design the system for'. Triggers on architecture discussions, system design, API design, data modeling, and infrastructure planning.

Add a new tool/function the AI agent can call (e.g. look something up, hit an external API, perform an action). Use when extending the assistant's capabilities, wiring a new function into the agent, or when the model needs a new action. This project uses {{ cookiecutter.ai_framework }}.

Create, review, and apply database schema changes with Alembic. Use whenever a SQLAlchemy model is added or changed, a column/index/constraint needs to change, or a data backfill is required — anything that alters the PostgreSQL schema.

Add or modify work that runs outside the request/response cycle — emails, document ingestion, webhooks, cleanups, scheduled jobs. Use when something is slow or fire-and-forget, or when adding a periodic/cron task. This project's queue is {{ cookiecutter.background_tasks }}.

Work with Stripe billing — subscriptions, plans/prices, the Customer Portal, credits, usage metering, invoices, and webhook events. Use when changing plans, handling a new Stripe webhook, debugging a payment/subscription flow, or touching credit balances and usage.

Work with messaging-channel bots (Telegram / Slack) — register a bot, route inbound messages through the AI agent, handle webhooks vs polling, or add a new channel adapter. Use when wiring chat into a messaging platform or debugging bot delivery.

Build a new page, view, or data-driven feature in the Next.js frontend. Use when adding a route under the dashboard/marketing area, wiring UI to a backend endpoint, adding client state, or creating a localized page. Covers App Router, data fetching, Zustand stores, and i18n.

Write or extend the backend test suite following this project's conventions. Use when adding tests for a new service/route/repository, when coverage is missing, or when asked to test a feature. Knows the mocked-session + httpx AsyncClient setup so tests run with no database.

Work with the RAG knowledge base — ingest documents, run semantic search, manage collections, or add a sync source/connector (Google Drive, S3). Use when populating or debugging the knowledge base, tuning retrieval, or adding a new document source. This project uses {{ cookiecutter.vector_store }} + {{ cookiecutter.embedding_provider }} embeddings.