Phalanx is an open‑source, polyglot‑based automation framework for Kali Linux that coordinates Python, Bash and other scripts, provides a planner, engine and reporting modules, integrates with tools like Nmap and Metasploit, and generates traceable logs for efficient and flexible penetration testing.
This guide presents 20 practical Python skills for API testing, covering basic request handling, pytest fixtures, JSON validation, database helpers, framework abstraction, dynamic data generation, Allure reporting, CI pipeline integration, AI‑driven test case creation, intelligent retries, performance and security testing, and engineering best practices to transform manual testing into an intelligent, automated workflow.
This article introduces Hermes Agent, an open‑source self‑evolving AI assistant that remembers your preferences across sessions, outlines its core capabilities, walks through system requirements, one‑click installation, model configuration, common commands, advanced features like cron jobs and browser integration, and provides troubleshooting tips.
This article explains how to choose between ChatGPT, Claude, Claude Code, and Codex, detailing Codex's seven core capabilities—including local file access, persistent memory, plugins, skills, image generation, computer control, automation, and the Chronicle screen‑monitoring feature—through concrete examples and step‑by‑step walkthroughs.
This tutorial walks through configuring an enterprise WeChat robot, linking it to Hermes' message gateway, building a skill that runs CPU and memory checks, scheduling periodic inspections, and automatically sending the results to the WeChat robot for hands‑free server performance monitoring.
This article reviews eleven Claude Code Skills, explaining how each plugin—such as Superpowers, planning‑with‑files, frontend‑design, and Commit Helper—adds structure, memory, and automation to AI‑assisted development, and offers practical recommendations on which to install first.
ml‑intern, an open‑source AI agent from Hugging Face, automates the full ML workflow—reading papers, generating code, training and deploying models—using an asynchronous event‑driven loop with submission and event queues, supporting interactive and headless modes, Slack notifications, and multiple LLM back‑ends.
This guide explains the simple file structure of a Claude Skill, compares it with CLAUDE.md, shows where to store skills at personal, project, or plugin level, and provides detailed best‑practice tips, code examples, and validation steps for creating effective, on‑demand AI agent skills.
This article introduces five Claude Code Skills—pr-summary, fix-issue, deep-research, commit, and explain-code—that turn repetitive development tasks into single‑command automations, showing concrete examples, usage scenarios, and how to share them across a team.
This article presents a practical collection of high‑frequency tools—including Python, Shell, SQL, Mermaid, Pandoc, curl, ImageMagick, and PlantUML—that can be wrapped as Agent Skills to give AI agents real execution power, illustrated with concrete prompts and scripts that cut manual work from hours to seconds.
The article explains how Claude Code’s Code Review plugin automates multi‑agent PR reviews with confidence scoring, details installation and configuration steps, shows the end‑to‑end workflow, compares it to Superpowers plugins, and lists alternative review approaches for developers.
The article explains how a self‑healing platform improves SRE reliability by reducing MTTR, preserving error‑budget, automating high‑impact incident remediation, enforcing safety guardrails, and shifting team focus from firefighting to sustainable reliability engineering.
When an HTTPS certificate expires, browsers show warnings, users abandon sites, services become unavailable, and security is weakened, so this article explains the TLS fundamentals, the risks of expiration, real‑world outage cases, and provides step‑by‑step guidance on acquisition, deployment, automated renewal, monitoring, and best‑practice procedures for reliable certificate management.
A publicly exposed server revealed a large‑scale automated attack in which threat actors used the Bissa scanner tool, AI‑assisted code, and hard‑coded Telegram bots to exploit the React2Shell (CVE‑2025‑55182) vulnerability, stealing credentials from more than 900 enterprises and reporting each success in real time.
The article explains that large‑scale incidents overwhelm on‑call engineers who must manually piece together context from countless signals, and shows how a self‑healing automation platform can take over repetitive, known failure patterns, verify fixes, and reduce fatigue while keeping humans in the loop for oversight.
This article details Coohom's AI‑driven, automated workflow for multilingual testing, covering the four main localization pain points, the construction of an AI language‑validation system, practical implementations for UI and API testing, and measurable results that reduced defect rates and cut regression time from a week to minutes.
The article examines AppleScript’s core capabilities—inter‑application communication, UI scripting, and system commands—while revealing the lower‑level macOS APIs such as Apple Events, Accessibility, JXA, and XPC that developers can use for faster, more powerful automation.
The article presents a data‑driven review of more than 50 AI Skills, grouped into five core scenarios, detailing their installation counts, key functions, and practical impact, to help senior developers choose the most effective plugins for accelerating development, design, documentation, and product growth.
The Claude Code plugin ecosystem has exploded to over 9,000 extensions with the leading plugins surpassing 50‑100k installs; this guide explains the five plugin architecture types, evaluates six functional directions, and recommends tailored plugin combos for full‑stack engineers, frontend developers, solo creators, and team leads.
The article details ClawSweeper, an AI‑driven maintenance bot for OpenClaw that scans and automatically closes thousands of stale issues and pull requests each day, explains its decision criteria, workflow, rate‑limit constraints, and how it turns the README into a live dashboard.
The article outlines fifteen mature AI Agent scenarios across office productivity, customer service, software development, and data analysis, explains how each works, ranks their readiness, and discusses why some applications are ready for large‑scale use while others remain experimental.
Agent Skills is an open‑source standard that defines reusable SKILL.md packages, a unified directory layout, and a progressive‑disclosure workflow, enabling AI agents across tools such as Antigravity to automatically discover, activate, and execute shared capabilities for faster, more consistent automation.
The author reflects on automating reading with AI, distinguishing information gathering from thinking exercises, and proposes a three‑question framework to decide when automation adds value versus when personal reading is essential, ultimately choosing to limit AI to pre‑ and post‑reading tasks.
This guide explains why AI Agent Operators are emerging as a new profession, contrasts the role with Prompt Engineers, outlines four core skills—CLI, agents.md, structured inputs, and business judgment—provides a step‑by‑step workflow, a 90‑day training roadmap, common pitfalls, and references from Deloitte and McKinsey.
The article introduces drawio‑mcp, an official open‑source MCP server that lets Claude‑series AI generate editable draw.io XML diagrams instantly, eliminating tedious manual dragging, alignment, and styling, and outlines four integration methods—MCP App Server, MCP Tool Server, Claude Code Skill, and Project Instructions—plus export formats, built‑in shape library, and maintenance workflow.
Healthpeak, a large medical‑real‑estate REIT, replaced fragmented spreadsheets and manual data entry with Palantir AIP’s ontology‑driven AI operating system, achieving automated billing, voice‑driven workflows, reduced errors, and a scalable, data‑centric operation that frees managers to focus on tenant relationships.
OpenAI’s official ChatGPT for Excel plugin embeds AI directly into Excel, offering natural‑language commands and a suite of AI‑prefixed functions that can generate tables, clean data, extract information, auto‑fill, translate, and even pull financial data, dramatically reducing manual spreadsheet work.
Harness Engineering, now buzzing across the tech community, promises a ten‑fold productivity boost by replacing hand‑written code with a structured AI‑driven system, and the article breaks down its definition, evolution from Prompt to Context to Harness, core components, real‑world examples, and the associated risks and debates.
In 2026, a leading e‑commerce platform cut A/B test preparation from 3.2 days to 47 minutes, boosted experiment throughput 4.3× and GMV 2.8% by applying a three‑step automation workflow, an intelligent analysis engine with three‑level reasoning, and a three‑tier human‑machine decision guard.
The article explains how fragile UI automation scripts hinder performance testing and shows a three‑layer self‑healing approach using Playwright and Python that reduces script failures, cuts maintenance time, and integrates with monitoring to quickly detect UI performance issues.
This talk details how Tencent Games leverages AI to transform its data governance from rule‑based, passive processes into a semantic, service‑oriented paradigm, addressing resource waste, low collaboration efficiency, and scalability challenges while delivering measurable improvements in cost, speed, and asset quality.
This guide breaks down a 103‑minute Codex tutorial into practical steps, showing how to organize projects, run multiple agents in parallel, and turn one‑off prompts into reusable Skills and automated workflows for AI‑assisted software development.
This article provides a Bash script that automatically gathers Linux system information—including OS details, uptime, CPU and memory usage, disk utilization with tiered alerts, network interfaces, top memory‑consuming processes, key service status, pending updates, recent error logs, load average, TCP connections, and zombie processes—and shows how to schedule it with cron for daily reporting.
This guide presents 35 concrete Claude Code techniques—each with a ready command or prompt—to streamline project bootstrapping, session handling, code quality, architecture, API design, automation, debugging, and recovery for faster, more reliable software development.
OpenAI’s new ChatGPT Workspace Agent preview transforms the chatbot from a passive assistant into an autonomous digital employee that can fetch data, run analyses, generate reports, and interact with enterprise systems, promising higher ROI for businesses while raising security, ethical, and employment concerns.
This article presents 35 hands‑on Claude Code techniques, each paired with a ready‑to‑use command or prompt, covering project initialization, session management, code quality, architecture review, automation, documentation, dependency handling, debugging, and recovery to help developers harness the AI coding assistant efficiently.
The author recounts how a bare‑bones Claude implementation missed edge cases, then introduces ten open‑source Claude Code Skills that embed a disciplined workflow—brainstorming, planning, execution, TDD, systematic debugging, parallel reviews, git worktrees, and diagram generation—showing installation commands, real‑world examples, and concrete benefits.
This comprehensive guide walks you through Claude Code’s market dominance, core design philosophy, step‑by‑step installation, a complete reference of basic and advanced CLI commands, slash commands, keyboard shortcuts, work modes, and real‑world workflows, helping developers unlock the full power of the AI‑driven programming assistant.
This guide shows how to streamline Python API testing by using ten practical decorators—covering automatic retries, timing, token injection, detailed logging, environment skipping, schema validation, timeout enforcement, cleanup, HTTP recording, and concurrent stress testing—each illustrated with real‑world code examples and usage patterns.
This guide explains what Agent Skills are, how they differ from traditional prompts, the three core design mechanisms, step‑by‑step creation of a Skill—including file structure, YAML metadata, and markdown instructions—plus advanced tips, real‑world use cases, and troubleshooting advice.
This article analyses the evolution of software engineering, examines the U.S. Department of Defense’s distributed software‑factory network, identifies governance and integration challenges for large defence organisations, and proposes a “total‑branch” design that unifies platform, process and team structures to achieve scalable, secure DevSecOps delivery.
The article analyzes how leading internet companies embed AI agents across the entire data‑warehouse lifecycle to automate governance, presenting real‑world case studies from Alibaba, ByteDance, JD.com and Tencent, and quantifies benefits such as over 65% reduction in manual effort, 50% drop in metric duplication, and a 40% boost in resource utilization.
The article explains how the emerging "Harness Engineering" paradigm—highlighted by OpenAI, Stripe and Anthropic—shifts AI development from prompt tweaking to building full control systems, promising ten‑fold efficiency gains, new architectural components, and both opportunities and risks for developers.
This article explains multi‑agent AI collaboration, outlines its core characteristics, breaks down the technical workflow of task decomposition, role assignment, communication and conflict resolution, compares leading frameworks, and showcases three practical scenarios—from financial report automation to game NPC ecosystems and intelligent customer service.
After months of using Claude Code, the author discovers that the real performance gap comes from the Skills you add—not the model itself—showing how ten carefully chosen Skills can transform Claude Code from a simple coding assistant into a versatile, repeatable digital teammate for browsing, summarizing, testing, refactoring, and more.
The article details how a three‑engineer team used OpenAI's Codex agents to generate an entire production‑ready software stack—including over a million lines of code, 1,500 pull requests, and a full CI/CD pipeline—in roughly one‑tenth the effort of manual coding, while describing the architectural, operational, and organizational adjustments required for such agent‑first development.
The article reviews four open‑source projects—BuilderPulse, AutoProber, wx‑favorites‑report, and awesome‑claude‑design—that automate daily research, hardware probing, personal data visualization, and design system creation, helping indie developers cut hours of repetitive work each week.
The article explains how conventional "smart" apps merely react to user commands, while AI Agents combine large language models, tool‑calling capabilities, and explicit goals to autonomously plan, act, and iterate, offering a new software paradigm with both promising use cases and current limitations.
This article provides an in‑depth, eight‑dimension comparison of Hermes Agent and OpenClaw, examining their core philosophies, learning abilities, integration options, deployment ease, security, standout features, overall strengths, and guidance on selecting the right AI agent for different user scenarios.
The article deeply compares shift‑left testing with traditional testing across five dimensions—goal orientation, participants, timing, technical means, and quality metrics—showing how early defect prevention, cross‑functional collaboration, embedded quality checkpoints, automation, and measurable outcomes can dramatically reduce defects and accelerate delivery.
The report analyzes recent global data on Agentic AI in the workplace, highlighting rapid adoption forecasts, job impact numbers, practical implementation steps, successful case studies across finance, healthcare, and manufacturing, and the governance risks that could derail projects.
Claude Code Game Studios is a virtual game‑studio framework that assembles 49 AI agents, 72 slash commands, and 12 automation hooks to automate the entire game‑development pipeline—from concept brainstorming to release—cutting a typical two‑week design phase down to 2‑3 days and supporting Unity, Unreal, and Godot.
This guide breaks down Claude Code’s 50‑plus commands into three logical categories, highlights the top ten daily‑use commands with concrete examples and code snippets, and walks through advanced tricks, shortcut keys, hidden options, and a full‑day automation workflow to dramatically boost developer productivity.
This article introduces Claude Code, an agentic command‑line AI coding assistant, explains its core features, walks through installation via Node.js, demonstrates a full Markdown editor project using Vue3, and details built‑in commands that streamline development tasks.
Learn how to design, write, test, and deploy reusable Claude Skills—custom instruction sets that automate document processing, code review, content creation, and data handling—by defining goals, crafting SKILL.md, adding scripts, creating trigger phrases, and measuring performance with concrete examples.
Amid widespread claims that AI will replace programmers, the article argues that current AI demos are limited to simple apps, while real software engineering requires deep problem definition, architecture design, and operational judgment—skills AI cannot replicate, making programmers' cognitive expertise more valuable than ever.
The article presents a Claude AI Skill that automatically creates detailed, color‑coded architecture diagrams as standalone HTML files, explains its design system, shows installation options via manual zip or Skills Hub, and demonstrates fast generation and iterative editing through simple prompts.
Learn how to turn daily repetitive Claude Code prompts into reusable Skills by identifying repeatable workflows, extracting five key Skill traits, applying a four‑step creation process, and iterating through observation, refinement, structuring, validation, and continuous improvement, illustrated with a real code‑review case study.
The author argues that traditional coding is dying as AI-powered tools such as Cursor enable non‑technical users to build and deploy functional software, highlighting faster development cycles, lower costs, and a shift in power dynamics that could reshape the future of programming.
The article analyzes Anthropic’s Co‑work, showing how the new AI collaboration system moves beyond answering questions to actively managing emails, calendars, documents, and Slack, turning fragmented digital tools into a unified workflow that lets knowledge workers treat AI as a true partner rather than a simple query engine.
An AI Agent is a large‑model system that can perceive its environment, plan steps, invoke tools, and remember past interactions to autonomously achieve user‑specified goals, distinguishing it from simple chatbots that only answer questions.
Hermes Agent, an open‑source, self‑evolving AI agent framework from Nous Research, tackles the major pain points of current AI tools—memory loss, static skills, limited deployment, and fragmented ecosystems—by offering autonomous learning loops, three‑layer persistent memory, a self‑optimising skill system, and seamless multi‑platform integration.
This practical guide compares Hermes Agent and OpenClaw across user skill levels, privacy requirements, and automation goals, offering step‑by‑step installation tips, scenario‑specific recommendations, and a decision matrix to help you choose the most suitable open‑source AI agent.
This comprehensive guide explains why MySQL backup is essential, defines RPO/RTO, compares logical and physical tools, provides ready‑to‑run scripts for full, incremental, binlog, encryption and compression backups, details step‑by‑step recovery procedures, troubleshooting tips and monitoring recommendations for reliable database protection.
This guide shows how to create a smart water‑drinking tracker that sends hourly reminders via a WeChat bot, stores daily intake, generates reports, and can be customized or deployed to GitHub, using OpenClaw’s cron and scripting features.
This guide explains how Claude Code’s probabilistic nature can lead to missed actions and shows how deterministic Claude Code Hooks—command, HTTP, prompt, and agent types—provide reliable pre‑, post‑, and permission‑stage controls, with detailed configuration examples, troubleshooting tips, and CI/CD integration.
The article analyzes how AI agents can write code yet remain uncontrollable, examines the shortcomings of prompt engineering and simple loops, and proposes Harness Engineering—a structured, constraint‑driven, feedback‑rich environment that turns software development into a stable, closed‑loop control system.
This guide introduces the Architecture Diagram Generator skill for Spring Boot 3, explains how to install it via OpenCode and Claude Code, lists its visual features and color scheme, and demonstrates generating various architecture diagrams such as web applications, AWS serverless stacks, and microservice systems.
This comprehensive guide walks you through what the OpenAI Codex desktop app is, how to install it on macOS and Windows, configure models, language, project standards, and unlock advanced features like multi‑agent parallel programming, code review, skill integrations, and automation for a seamless AI‑powered coding experience.
The article analyzes why AI agents lose context during multi‑session web‑app development, outlines common failure patterns, and proposes a practical harness that records progress, uses Git commits, and enforces fine‑grained feature lists and end‑to‑end testing to keep development on track.
The article analyzes how the 2026 OpenClaw breakout—an AI agent that can execute tasks on a computer—signals a quiet AI revolution that transforms product managers from chat‑based advisors to autonomous executors, reshapes their daily workflows, and forces a three‑layer shift in skills and strategy.
This article walks through Karpathy’s open‑source Autoresearch system, explaining its core design principles, file layout, and workflow, and then demonstrates practical AI‑agent applications for code optimization, bug fixing, and article writing, complete with setup commands, code snippets, and example experiment logs.
Learn how to create and use a Python @extract_value decorator that automatically pulls specific fields from API responses, stores them in a global context, and lets subsequent test steps access these values without manual extraction, complete with step-by-step code examples and common pitfalls.
Discover six powerful Claude Code and Codex Skills—code review, security guidance, commit commands, up‑to‑date documentation, frontend design, and document handling—that streamline code review, Git workflows, security checks, UI creation, and file processing, dramatically boosting developer productivity.
This article details how a SaaS platform transformed its AWS multi‑account management from manual, toil‑heavy processes to a fully automated, self‑healing system that now handles over 6,000 accounts with just three engineers, achieving sub‑5‑minute provisioning, 99.8% compliance, and massive cost savings.
This article walks you through what Claude Code skills are, how they work, the four skill types, the exact file format, a step‑by‑step process for building your first skill, best‑practice design principles, testing methods, and ongoing maintenance, enabling you to automate repetitive AI tasks efficiently.
This article explains what Agent Skills are, why a curated skill library is valuable, and reviews eight actively maintained GitHub repositories—detailing their structure, core capabilities, integration points, and practical usage examples for building production‑grade AI agents.
The article explains how HiClaw’s Worker templates turn ad‑hoc multi‑agent tasks into repeatable, stable processes by encapsulating skills, constraints, and SOPs, enabling easier reuse, versioning, and distribution across teams and private markets.
This article extracts the core methodology of Anthropic's skill‑creator tool and presents seven practical design guidelines—progressive three‑layer loading, aggressive description writing, explaining the why, test‑driven development, avoiding over‑fitting, delegating repetitive work to scripts, and domain‑specific reference splitting—to help developers craft LLM‑driven skills that are both efficient and generalizable.
Superpowers is an open‑source workflow system that equips AI coding agents like Claude Code, Codex, and OpenCode with composable skills, decision‑flow diagrams, and test‑driven development to automate best‑practice software engineering from brainstorming to code review.
The article dissects twelve concrete harness design patterns uncovered in the leaked Claude Code source, organized into four categories—memory & context, workflow & orchestration, tools & permissions, and automation—detailing their use cases, trade‑offs, and implementation costs for building production‑grade AI agents.
Codex CLI, OpenAI’s command‑line programming assistant, lets developers generate, explain, debug, and refactor code directly from the terminal; this guide walks through prerequisite Node.js setup, multi‑platform installation methods, authentication options, core commands, advanced parameters, configuration files, MCP integration, practical use‑cases, and troubleshooting tips.
The article analyzes how AI is fundamentally reshaping agile development across strategic, product, and personal dimensions, urging organizations to treat AI adoption as a cultural challenge, developers to focus on rapid problem discovery and validation, and individuals to evolve from prompt users to autonomous AI agents.
The asm (agent‑skill‑manager) tool unifies the management of AI coding‑assistant skills by providing a global view, one‑click GitHub installation, built‑in security scanning, a complete local development workflow, and support for over 17 assistants through both TUI and CLI interfaces.
In a rapidly growing data‑driven environment, Kuaishou’s Life Services Data Center tackled exploding demand and limited manpower by replacing traditional siloed data‑warehouse practices with AI‑driven intelligent review, DQC, and chatbot solutions, achieving up to 11.34% productivity gains and dramatically improving data quality.
This article details a practical experiment that uses the Kuikly App Builder skill to let an AI agent automatically create, compile, and deploy multi‑platform mobile apps, highlighting the workflow, results, current limitations, and broader implications for future AI‑driven development tools.
The article warns that the high‑privilege OpenClaw AI agent can cause data loss, credential theft, and unexpected charges, then provides a step‑by‑step guide to fully remove it, revoke API keys, and follow best practices to keep the tool from becoming a security liability.
This guide explains how to integrate Anthropic's Claude Code AI assistant into IntelliJ IDEA, covering installation, configuration, and immersive coding workflows that enable natural‑language code generation, project‑wide understanding, smart debugging, automated refactoring, and terminal automation for dramatically higher developer productivity.
This article explains how linking the breadth‑focused OpenClaw with the depth‑oriented Hermes Agent creates a dual‑agent workflow that lets an AI assistant not only handle multi‑channel requests but also continuously learn, remember, and improve its responses.
This article examines how AI large models can transform data warehouse development by automating modeling, improving data cleansing and quality auditing, and enabling intelligent operations, while also highlighting five common implementation pitfalls and practical best‑practice recommendations for enterprises seeking cost, efficiency, and quality gains.
This article walks professionals through OpenClaw’s command‑line interface, explaining its role alongside GUI and API, detailing five common use‑cases with exact commands, and illustrating the underlying execution flow from CLI input to component actions, enabling quick debugging, automation, and efficient operations.
The article walks readers through OpenClaw’s complete automation architecture, detailing the roles of Client, Gateway, Hooks, Cron, Heartbeat, Agent, Skills, and Plugins, explaining event flow, execution steps, hook loading, webhook integration, and practical enterprise deployment patterns, while providing concrete examples and configuration snippets.
gstack is an open‑source AI engineering workflow that bundles 23 AI skills into a seven‑stage sprint (Think, Plan, Build, Review, Test, Ship, Reflect), delivering desktop‑class development speed, detailed security, and cross‑model collaboration for solo developers or small teams.
This article details the design and workflow of HiClaw, an AI‑driven, cloud‑native system that intercepts DingTalk crash alerts, isolates analysis in secure containers, and automatically generates actionable reports, dramatically reducing manual investigation time while complying with strict internal security policies.
The article analyzes the unique challenges of evaluating AI products—output uncertainty, subjective criteria, over‑fitting risk, high cost, and vague metrics—compares traditional testing with AI testing, proposes a five‑step evaluation workflow, defines concrete metrics such as pass rate and efficiency gain, and illustrates the process with a real‑world sales‑script generation case study, concluding with five key success factors and future trends.
Claude Managed Agents provide a pre‑built sandbox, orchestration, and session layers that let developers launch production‑grade AI agents in days instead of months, cutting costs, boosting success rates, and delivering real‑world enterprise case studies.
This article explains what Agent Skills are, shows the folder layout and SKILL.md format, introduces the progressive‑disclosure design, provides concrete best‑practice tips, testing and evaluation methods, and demonstrates how to package scripts for reliable AI‑assistant automation.
BCG’s Henderson Institute report reveals that AI will reshape 50‑55% of U.S. jobs within the next 2‑3 years, altering tasks, skill demands and work methods, while only 10‑15% of roles are expected to be fully eliminated.
The open‑source “oh‑my‑claudecode” (OMC) framework lets developers drive Claude Code with natural‑language commands, automatically orchestrating multiple agents to plan, code, test, and deploy projects, eliminating the need to memorize complex Claude Code instructions and dramatically lowering the cognitive load of AI‑assisted programming.
The article analyzes how AI coding agents are moving from answering questions to autonomously handling the entire development workflow, reshaping programmers' roles from manual implementation to defining, orchestrating, and validating tasks.
