3.5K skills · sorted by relevance
Post-deploy canary monitoring. Watches the live app for console errors, performance regressions, and page failures using the browse daemon. Takes periodic screenshots, compares against pre-deploy baselines, and alerts on anomalies. Use when: "monitor deploy", "canary", "post-deploy check", "watch production", "verify deploy". (gstack)
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Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan". Proactively suggest when the user has a plan or design doc and is about to start coding — to catch architecture issues before implementation. (gstack) Voice triggers (speech-to-text aliases): "tech review", "technical review", "plan engineering review".
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Cross-model benchmark for gstack skills. Runs the same prompt through Claude, GPT (via Codex CLI), and Gemini side-by-side — compares latency, tokens, cost, and optionally quality via LLM judge. Answers "which model is actually best for this skill?" with data instead of vibes. Separate from /benchmark, which measures web page performance. Use when: "benchmark models", "compare models", "which model is best for X", "cross-model comparison", "model shootout". (gstack) Voice triggers (speech-to-text aliases): "compare models", "model shootout", "which model is best".
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Single entry point for all AEM as a Cloud Service Dispatcher skills. Covers config authoring, technical advisory, incident response, performance tuning, security hardening, and full lifecycle orchestration for the Adobe Dispatcher Apache HTTP Server module and its HTTPD/dispatcher configuration.
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Orchestrates end-to-end replication workflows spanning multiple concerns: new environment setup, production incident response, and performance optimization for AEM 6.5 LTS.
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Review code for AEM Edge Delivery Services projects. Use at the end of development (before PR) for self-review, or to review pull requests. Validates code quality, performance, accessibility, and adherence to EDS best practices.
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Audit an AEM Edge Delivery Services page for content quality, SEO, accessibility, performance, and EDS best practices. Produces a prioritized fix list with specific remediation steps. Use when reviewing page quality, preparing for launch, or optimizing existing content.
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Microsoft Pragmatic Rust Guidelines for implementing, reviewing, and documenting idiomatic Rust. Use when working on Rust APIs, error handling, unsafe code, concurrency, async code, performance, testing, documentation, or agent-facing design.
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iOS and Swift/SwiftUI development guidance, including App Clips, haptics, UI patterns, Liquid Glass styling, performance audits, view refactors, Swift concurrency, and iOS debugging. Use when building or reviewing iOS apps, SwiftUI views, or troubleshooting iOS issues.
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Refactor code to improve quality while maintaining functionality. Use when you need to improve code structure, eliminate duplication, optimize performance, or enhance maintainability without changing behavior.
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Semantic Design System Skill for Google Stitch. Generates agent-friendly DESIGN.md files that enforce premium, anti-generic UI standards — strict typography, calibrated color, asymmetric layouts, perpetual micro-motion, and hardware-accelerated performance.
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Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.
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Provides Rust coding best practices for structure, patterns, performance, and error handling. Use when writing or reviewing Rust code, or when the user asks for Rust style guidance.
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iOS and Swift/SwiftUI development guidance, including UI patterns, Liquid Glass styling, performance audits, view refactors, Swift concurrency, and iOS debugging. Use when building or reviewing iOS apps, SwiftUI views, or troubleshooting iOS issues.
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Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).
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Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.
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Codified expertise for managing carrier portfolios, negotiating freight rates, tracking carrier performance, allocating freight, and maintaining strategic carrier relationships.
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ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
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Frontend development patterns for React, Next.js, state management, performance optimization, and UI best practices.
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Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
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Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
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Azure Application Insights SDK for .NET. Application performance monitoring and observability resource management.
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Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
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Build content-focused websites with Astro — zero JS by default, islands architecture, multi-framework components, and Markdown/MDX support.
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