Results for “patterns”

Migrates AEM Cloud Service code from legacy AssetManager APIs (createAssetForBinary, getAssetForBinary, removeAssetForBinary, client-facing createAsset) to Direct Binary Access or in-JVM resolver patterns, covering IMS authentication and service-user setup.

Implements concurrent Go patterns using goroutines and channels, designs and builds microservices with gRPC or REST, optimizes Go application performance with pprof, and enforces idiomatic Go with generics, interfaces, and robust error handling.

Provides a security checklist and hardened Solidity patterns for auditing AMM contracts, liquidity pools, and swap flows, covering reentrancy, CEI ordering, donation attacks, oracle manipulation, slippage, admin controls, and integer math.

Load this skill when the user says "update coding standards", "update-coding-standards", or "/update-coding-standards". Analyzes the diff of a merged PR and appends any valuable new patterns to the relevant coding standards doc — but only if something genuinely warrants documenting.

Provides foundational patterns for building type-safe frontend applications with Elm, covering The Elm Architecture, core language features, and Elm's approach to functional web development.

Foundational Erlang patterns covering OTP behaviors, fault-tolerant systems, distributed computing, pattern matching, processes, and supervision trees. Use when writing Erlang code, building concurrent systems, working with OTP frameworks, or developing distributed fault-tolerant applications. This is the entry point for Erlang development.

Turns any long-running domain (business, relationships, health, career, learning, investing) into a local knowledge project with four layers, source tags, immutable snapshots, and a concept library that learns patterns over time.

Reverse-engineers custom JavaScript-based WASM virtual machines and risk-control engines by identifying DSL VM patterns, extracting opcodes, analyzing constant tables, and tracing exported functions through static analysis and runtime injection.

Detect and exploit Server-Side Template Injection vulnerabilities across multiple template engines including Jinja2, Twig, Freemarker, and Velocity, with payloads for sandbox escape and remote code execution. Includes detection methodology, bypass techniques, and fix patterns.

Modernize deprecated MATLAB functions and patterns. Use when check_matlab_code or checkcode reports "not recommended" or "to be removed" warnings, when migrating legacy code, or when replacing deprecated APIs (trainNetwork, csvread, xlsread, datenum, eval, subplot, guide, optimset, wavread, svmtrain, uicontrol) with current equivalents.

CRUD patterns for state slices — consistent `domain/create|read|update|delete` action naming, request/success/failure triples per operation, and normalised `{ byId, allIds }` entity shapes for O(1) lookups. Use when designing a new entity slice, standardising action-type names, or refactoring array-shaped state.

VS-Enhanced Academic Style Humanizer - Transforms writing patterns to achieve authentic scholarly voice Applies transformations from G5 analysis to create natural academic prose Use when: improving AI-assisted writing quality, preparing manuscripts, enhancing scholarly voice Triggers: humanize, transform, make natural, improve writing quality, improve style

Provides file paths to language-specific reference files for polyglot test analysis skills, enabling framework-aware detection of test markers, assertions, and patterns across .NET, Python, TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++.

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working, helping inspire and improve your own ad campaigns.

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

Hunt for adversary abuse of Living Off the Land Binaries (LOLBins) by analyzing endpoint process creation logs for suspicious execution patterns of legitimate Windows system binaries used for malicious purposes.

Analyzes and recreates Uber's design language: a black-and-white palette, custom geometric display and text fonts, pill-shaped interactive elements, and editorial 4:3 illustrations for transportation and delivery interfaces.

Python code-quality anti-patterns and review checks: exception-hierarchy correctness, singleton identity comparison, narrow exception handling, wildcard-import avoidance, magic-number naming, and dead-local removal. Use when reviewing or self-reviewing Python code for correctness and readability defects that linters and reviewers should catch.

Implement signal-based reactive state management in Angular v20+. Use for creating reactive state with signal(), derived state with computed(), dependent state with linkedSignal(), and side effects with effect(). Triggers on state management questions, converting from BehaviorSubject/Observable patterns to signals, or implementing reactive data flows.

Dart 3.x language feature standards: null safety, records, sealed classes, switch pattern matching, extensions, and async/await. Use when using !, ?., ??, late, sealed classes, record types, switch expressions, or async patterns — and before introducing any new Dart 3.x construct to confirm the modern idiomatic approach.

Read BEFORE writing any code that builds or simulates OFDM systems. The default MATLAB patterns for OFDM (e.g., direct ifft/fft, awgn with 0 dBW power, missing symOffset) produce subtly incorrect results — always use ofdmmod/ofdmdemod instead of direct IFFT/FFT. This skill specifies the correct calling conventions for ofdmmod, ofdmdemod, ofdmChannelResponse, ofdmEqualize, and critical anti-patterns that must be avoided. Use when building OFDM transmitters or receivers, allocating subcarriers and guard bands, inserting pilots, computing SNR for OFDM, configuring fading channels (Rayleigh/Rician), estimating and equalizing channels, implementing timing and frequency synchronization, adding LDPC coding, designing resource grids, or setting up OFDM link simulations.

Detects credential stuffing attacks by analyzing authentication logs for login velocity anomalies, ASN diversity, password spray patterns, and geographic distribution of failed logins using statistical analysis on Splunk or raw log data.

Guides the agent to research existing tools, libraries, and patterns before writing custom code, using parallel searches across package registries, MCP servers, skills, and GitHub, then evaluating and deciding to adopt, extend, or build.

Manage project learnings. Review, search, prune, and export what gstack has learned across sessions. Use when asked to "what have we learned", "show learnings", "prune stale learnings", or "export learnings". Proactively suggest when the user asks about past patterns or wonders "didn't we fix this before?"

Justfile authoring, reviewing, and planning for the just command runner. Use when creating new justfiles, adding recipes, reviewing existing justfiles for quality, planning recipe sets for new projects, or upgrading justfiles as projects mature. Covers syntax patterns, module system, recipe groups, language-specific templates, and maturity assessment.

Writing maintainable code - readability principles, SOLID patterns applied pragmatically, and the judgment to know when rules should bendUse when "code quality, clean code, readability, naming, SOLID, refactor, code review, best practices, maintainable, how should I structure, clean-code, solid, readability, maintainability, code-review, naming, functions, principles" mentioned.

Detect NTLM relay attacks by analyzing Windows Event 4624 logon type 3 with NTLMSSP authentication, identifying IP-to-hostname mismatches, Responder traffic signatures, SMB signing status, and suspicious authentication patterns across the domain.

Foundational Java patterns covering core syntax, object-oriented programming, generics, collections, streams, lambdas, and modern Java features. Use when writing Java code, understanding the type system, working with collections/streams, or needing guidance on which specialized Java skill to use. This is the entry point for Java development.

C++-specific library development patterns. Use when creating C++ libraries, designing header-only vs compiled libraries, configuring CMake for library targets, managing ABI stability and versioning, integrating with Conan/vcpkg, documenting with Doxygen, or testing with GoogleTest/Catch2. Extends meta-library-dev with C++ tooling and idioms.

Detect anomalies in DNP3 protocol communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

Detect WMI-based lateral movement by analyzing Windows Event ID 4688 process creation and Sysmon Event ID 1 for WmiPrvSE.exe child process patterns, remote process execution, and WMI event subscription persistence.

Detect process injection techniques (T1055) including classic DLL injection, process hollowing, and APC injection by analyzing Sysmon events for cross-process memory operations, remote thread creation, and anomalous DLL loading patterns.

Call Apex methods imperatively from Lightning Web Components for button clicks, lifecycle hooks, and conditional logic, covering import syntax, cacheable vs non-cacheable methods, async/await patterns, error handling, loading states, and parallel calls with Promise.all.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Detects and fixes patterns including: inflated symbolism, promotional language, superficial analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Detects and fixes patterns including: inflated symbolism, promotional language, superficial analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Provides domain-specific best practices for Node.js development with TypeScript, covering type stripping, async patterns, error handling, streams, modules, testing, performance, caching, logging, and more. Use when setting up Node.js projects with native TypeScript support, configuring type stripping (--experimental-strip-types), writing Node 22+ TypeScript without a build step, or when the user mentions 'native TypeScript in Node', 'strip types', 'Node 22 TypeScript', '.ts files without compilation', 'ts-node alternative', or needs guidance on error handling, graceful shutdown, flaky tests, profiling, or environment configuration in Node.js. Helps configure tsconfig.json for type stripping, set up package.json scripts, handle module resolution and import extensions, and apply robust patterns across the full Node.js stack.