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Found 198 Skills
Intelligent loading performance analysis with automated workflows for TTFB investigation (DNS/connection/server breakdown), render-blocking detection, script performance deep dive (first vs third-party attribution), font optimization, and resource hints validation. Includes decision trees that automatically analyze TTFB sub-parts when slow, detect script loading anti-patterns (async/defer/preload conflicts), identify render-blocking resources, and validate resource hints usage. Features workflows for complete loading audit (6 phases), backend performance investigation, and priority optimization. Cross-skill integration with Core Web Vitals (LCP resource loading), Interaction (script execution blocking), and Media (lazy loading strategy). Use when the user asks about TTFB, FCP, render-blocking, slow loading, font performance, script optimization, or resource hints. Compatible with Chrome DevTools MCP.
Detects framework-specific anti-patterns, convention violations, and idiom misuse across PHP/Laravel, React/Next.js, and Python/Django/FastAPI codebases. Loads framework-specific reference guides and checks against framework conventions. Generates severity-scored findings with copy-pasteable fix prompts. Trigger phrases: "framework review", "framework check", "laravel best practices", "react best practices", "framework audit", "framework-specific review".
Analyzes the variety and depth of assertions across .NET test suites. Use when the user asks to evaluate assertion quality, find shallow testing, identify assertion-free tests (no assertions or only trivial ones like Assert.IsNotNull), flag self-referential or tautological assertions (output equals input on identity/round-trip operations), measure assertion coverage diversity, or audit whether tests verify different facets of correctness. Produces metrics and actionable recommendations. Works with MSTest, xUnit, NUnit, TUnit. DO NOT USE FOR: writing new tests (use writing-mstest-tests), other anti-patterns like flakiness or duplication (use test-anti-patterns), or fixing assertions.
Autonomously set up an OpenClaw bot on a fresh Yandex Cloud VM in Kazakhstan (kz1-a, Karaganda). Asks the user for exactly two things — a Telegram bot token and one of three LLM access options (Anthropic API key, OpenRouter API key, or OpenAI Codex OAuth via ChatGPT Plus/Pro subscription) — then handles VM creation, hardening, OpenClaw install, CEO AI OS workspace seeding, Telegram pairing, chat_id auto-detection, and bot-reply verification on its own. The only other actions the user performs are pressing /start in Telegram once and (if Codex) confirming a device code on auth.openai.com. Use when the user says install OpenClaw to Yandex Cloud, deploy OpenClaw to YC Kazakhstan, set up my CEO bot in YC KZ, I am at OpenClaw workshop and need my own bot, create a Yandex Cloud VM for OpenClaw, or any close paraphrase. Targets a ~15-minute end-to-end run for non-DevOps users (founders, CEOs, marketing leads). Supports two modes of accessing Yandex Cloud — Plan A (the user's own YC Kazakhstan account via OAuth) and Plan B (a workshop-key bundle provided by the workshop organizer, for participants without their own YC account). The mode is auto-detected from the inputs. For local-machine OpenClaw install, use openclaw/install.sh in this repo instead. Companion skill openclaw-guide is required; prepare-yc-workshop is the matching organizer-side skill that produces the bundles consumed in Plan B; openclaw-user-onboarding is auto-invoked after Step 5 to collect the five basic facts about the user (identity, focus, style, tools, anti-patterns) and write them into USER.md so the bot is useful from message one.
Deep Agents framework — architectural decisions (when to use Deep Agents vs alternatives, backend strategies, subagent design, middleware approaches) AND code review (bugs, anti-patterns, improvements when reviewing Deep Agents code). Use when working with Deep Agents — designing a new system or reviewing existing code.
Capture a writer's voice DNA through collaborative interview and sample analysis. Use when someone wants to document their writing voice for use with a ghost writer skill. Produces a Voice DNA Document with patterns, anti-patterns, and actionable guidance. Handles one register/mode per session, supports refinement over time.
Comprehensive Rust coding guidelines with 179 rules across 14 categories. Use when writing, reviewing, or refactoring Rust code. Covers ownership, error handling, async patterns, API design, memory optimization, performance, testing, and common anti-patterns. Invoke with /rust-skills.
Brutally honest Rails code review from DHH's perspective. Use when reviewing Rails code for anti-patterns, JS framework contamination, or violations of Rails conventions.
Helps engineering managers measure and improve team delivery — produces a history of why common metrics fail, the DORA four-key-metrics framework (deployment frequency, lead time, change failure rate, MTTR), DevEx's three dimensions (feedback loops, cognitive load, flow state), a translation layer from engineering metrics to business outcomes, and a list of measurement anti-patterns to avoid. Use when the user says "how do I measure productivity," "DORA metrics," "velocity," "cycle time," "developer experience," "DevEx," "how do I show our team is performing well," "metrics for engineering," "team is slow," "engineering performance," or "connect engineering to business." Do NOT use for managing an underperforming individual — use performance-reviews instead.
Review UI changes against Swiss International Style design system. Checks colors, typography, borders, shadows, spacing, and anti-patterns. Use before committing any frontend UI changes.
Automates architecture validation for Clean Architecture, Hexagonal, Layered, and MVC patterns. Detects layer boundary violations, dependency rule breaches, and architectural anti-patterns. Use when asked to "validate architecture", "check layer boundaries", "architectural review", before major refactoring, or as pre-commit quality gate. Adapts to project's architectural style by reading ARCHITECTURE.md.
Refactor Spring Boot and Java code to improve maintainability, readability, and adherence to enterprise best practices. This skill transforms messy Spring Boot applications into clean, well-structured solutions following SOLID principles and Spring Boot 3.x conventions. It addresses fat controllers, improper transaction boundaries, field injection anti-patterns, and scattered configuration. Leverages Java 21+ features including record patterns, pattern matching for switch, virtual threads, and sequenced collections.