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Glossary8
Open the full glossary- IDE (Integrated Development Environment)A program that bundles code-writing with everything around it in one window: a file tree, syntax highlighting, an integrated terminal, run and debug.
- Environment variables and .envConfiguration a program reads from outside itself, instead of values hardcoded in the source.
- sudo (superuser do)Run this one command as the administrator (root): the command stays the same, the identity changes.
- Node.jsThe program that lets JavaScript run outside a browser — and the thing many AI command-line tools are installed and launched with.
- Virtual environment (venv)A project-private folder of Python packages, kept apart from the system. Once activated, whatever pip installs lands only inside it.
- Pull request (PR)A formal request saying 'I have made these changes — please decide whether to take them in'. It is a human review process, not a command.
- API (Application Programming Interface)A published contract: send a request in the specified shape and get a reply in the specified shape, with no need to know how the other side works internally.
- Regex (regular expression)A notation for describing what a piece of text looks like, used to find or validate matching fragments inside larger text.
Found 102 articles
The 74k-star Open-Source Life Guide: What Its Evidence Grading Is Worth Copying
A breakdown of a GitHub project with 74,249 stars: 772 recommendations, 2,597 primary sources, and an A/B/C evidence grading system. Compared against our T0-T5 trust model — three ideas worth borrowing, two not.
OpenGCUA Guide: The Open-Source Approach to Letting AI Actually Use a Computer
OpenGCUA is an open-source generalist computer-use agent from the Tongyi-MAI team. This guide breaks down its accessibility tree, code execution, and background operation design, checks the paper's 82-task numbers, and gives macOS install steps, three adoption paths, and an isolation plan for its arbitrary-code-execution risk.
Advanced Ontology Design: From a Reasonable Model to a Production-Grade Semantic Layer for Agents
When an ontology has to go to production: pick the right OWL profile, turn constraints into executable checks, handle identity and time, and let agents use it through a tool contract. This is about making it hold up, not making it look pretty.
Ontology Design from Scratch: Building a Reasoning-Ready Business Semantics Layer
Same model, same tools, same data — yet the agent is sometimes right and sometimes wrong. The difference is rarely the model; it is whether there is a shared, computable, constrainable layer of business semantics. This guide starts from zero and ends with a working minimal accounting ontology.
Tunnel Techniques Explained: When an AI Agent Needs to Pave a Road into the Internal Network
The hard part begins after an AI agent lands inside a network: firewalls block, the target has no outbound internet, and the attack host cannot reach it directly. This illustrated guide explains how three mainstream tunneling techniques work (SOCKS5 proxy, HTTP-disguised tunnel, TUN virtual adapter), when each applies, and what defenders can observe in traffic.
Agentic Attack Tooling Research Series: A Guide to All Fourteen Parts
When attack tooling becomes AI-agent-driven, both sides of the conflict change. This is a fourteen-part deep research series: starting from a publicly attributed real-world incident, it unpacks architecture design, coordination mechanisms, and technical principles, then returns to a checklist defenders can use immediately plus isolated research practice.
AI Supply Chain Poisoning: When the Risk Hides in Models, Data, and Tools
An AI system's supply chain is far more complex than traditional software: model weights, training data, dependencies, external tools (MCP), and even prompts themselves can be tampered with. This article breaks down five links, why detection is so hard, and five practical defensive principles.
Cloud Identity and Permissions: Where the New Access Cards Live
When workloads move to the cloud, credentials change shape entirely: no longer usernames and passwords but service principals, roles, temporary credentials, and CI/CD secrets. This article explains four concepts, five common blind spots, and a practical order for tightening things up.
Defense Lessons from a Red-Team Postmortem: Six Failure Causes, Six Defensive Openings
A rare public red-team postmortem honestly lists six root causes from an autonomous penetration exercise. This article reads each root cause in reverse as an opportunity defenders can exploit, and distils them into a checklist for enterprise risk review.
Honeypots and Anti-Agent Traps: When the Prey Starts Setting Traps
Honeypots are a classic defensive tool, but once attackers became AI agents both sides changed: defenders now design traps aimed specifically at AI, and anyone using agents to read external content needs to know how to avoid them. This article unpacks four trap classes and how to defend against them.
Insider Threat and Access Governance: The Hardest Attack Surface Is Inside
Insider threat is not simply "having a bad actor": it covers three distinct types — malicious, negligent, and coerced — each needing different countermeasures. This article breaks down their behavioural signatures and detection logic, and why access governance beats employee surveillance.
Supply Chain and Third-Party Risk: When Your Attack Surface Is Not in Your Own Building
Much of a modern enterprise's attack surface sits outside its own control: open-source packages, outsourced providers, cloud dependencies, SaaS tools. This article unpacks the risk mechanics of four supply-chain links, shows how attackers borrow a path in, and includes a third-party risk checklist you can use directly.
Zero Trust Architecture: Not a Product Purchase but a Change of Assumption
In vendor decks, "zero trust" often becomes a product name; fundamentally it is only a change of assumption — no longer assuming the inside is safe. This article unpacks three core principles, four implementation layers, five common misconceptions, and why it is the same work as credential governance and insider threat management.
DesignCraft Deep Dive: Layout and Publishing with designcraft-cli
A hands-on guide to designcraft-cli v0.5.0: the nine top-level subcommands, the file.new document model, headless rendering, the App control port, script automation, MCP integration and benchmarks — with four real rendered pages.
OfficeCLI Deep Dive: Control Word, Excel and PowerPoint from the Command Line
A hands-on guide to officecli v1.0.156: the L1/L2/L3 three-layer fallback model, resident mode, atomic batch edits, interactive watch editing, specialized skills and MCP integration, with real rendered screenshots.
How Databases Work: From File Cabinets to Vector Search
A beginner-to-deep guide to how databases store, index, and protect data, plus a family map of relational, key-value, document, graph, vector, and time-series engines, and how to choose.
OkHuman Capability Evaluation: An Agent That Misdiagnoses Itself
Thirteen verifiable tests on a local 9B model revealed the biggest flaw: OkHuman confidently misreports its own capabilities. Why agent evaluation must never trust self-reports.
How We Fixed OkHuman Semantic Search and Built It a Web Search Plugin
A root-cause chain from a lying health endpoint to a one-line --pooling last fix, plus a zero-dependency search plugin with three providers and automatic fallback.
After You Press Enter: From 0.03 s to 0.85 s, What Your Question Goes Through
One real API call dissects the full chain of a question: 35 ms to establish the connection, microseconds to tokenize, 474 ms for the model to read your whole question, 380 ms generating it token by token — 854 ms in total. Includes the complete reproducible measurement method, and one counterintuitive conclusion: 96% of the time is not in the network but inside the model.
Smart Email Classification and Reply Template System
Drowning in email every day? This article teaches you how to use AI to classify incoming messages automatically, match the best reply template, and generate drafts for you to confirm and send quickly. The focus is on designing the 'confidence threshold' and the 'human review mechanism', so the system saves time without ever sending the wrong thing.
Microservice Dependency Map Generation: From Black-Box Architecture to Visualized System Understanding
Under a microservice architecture nobody knows the full call relationships between services; change one API and you cannot tell which downstream services it affects, and a newcomer needs weeks to grasp the system. This article wires Jaeger, Prometheus, LLM nodes, and a graphing library into a dependency-map pipeline: extract distributed-tracing data, build call relationships, identify critical paths, and generate an interactive map so architects and engineers understand the system structure fast.
Performance Review Data Aggregation and Visualization: From Fragmented Feedback to Structured Insights
The most expensive thing about performance reviews is not the time — it is the bias. This article uses Lattice, 15Five, and AI together to build automatic aggregation of multi-source feedback, theme extraction, and trend visualization, so managers decide based on data instead of impressions.
Social Media Content Calendar Management System
Struggling every day over what to post? This article teaches you how to use AI to generate content ideas automatically, schedule publishing, and optimize strategy from the data. The focus is on designing 'content quality control' and 'the balance between automation and human creativity'.
The AI Coding Tools Map: Recognize the Form Factor First, Memorize Names Later
Cursor, Trae, Claude Code, Codex, OpenClaw, Hermes Agent, DeepSeek Harness, WorkBuddy and Doubao Work sorted into three categories by form factor: IDE-embedded, terminal agent, and orchestration platform. For each category: what it gives you, how much control and visibility it takes away, and how people actually mix them in practice — so you can decide which category your first tool should come from.
How to Cost AI: Subscriptions, Tokens, and Hidden Labor
AI adoption budgets are often severely underestimated because most people count only the subscription fees. This article teaches you to compute all three cost layers item by item — per-user monthly subscriptions, usage-billed API tokens, and the hidden labor of review and operations — and provides an estimation-sheet template you can fill in directly.
Enterprise Data Security Basics: What Data Should Never Be Fed to AI
Employees pasting customer personal data into free AI tools is one of the most common and hardest-to-prevent data leakage paths in enterprises. This article provides a four-tier data classification standard, a 'never upload' red-line checklist, a comparison of enterprise vs. consumer terms, local deployment options, and a question list for IT and legal teams.
Function Calling 101: Getting an LLM to Actually Use Tools
A clear account of the Function Calling mechanism in mainstream LLM APIs: how to write a tool JSON Schema, how the model decides whether to call a tool, how to use tool_choice for forced calls and parallel calls — with a complete runnable example, plus practical techniques for how the way you write tool descriptions decides call quality.
Git and GitHub for Beginners: Why AI Tools Keep Asking You to Clone
Why every AI programming tool's installation guide assumes you know Git. This article explains what repository, commit, branch, clone, fork, and pull request each mean, how they connect, and why non-programmers need to understand the first three.
The Evolution of the Harness: Six Eras, Each With Its New Capabilities and New Ways to Crash
From pure-prompt chatbots, CoT and ReAct reasoning prompts, and function calling — the real turning point — to MCP standardization, long-running CLI Agents, and always-on multi-Agent orchestration: era by era, what new capability the harness gained each time, and what new failure mode that capability incidentally introduced.
A Map of HK Equity Research Sources: HKEX Filings, Annual Reports, and Third-Party Data
When researching an HK-listed company, where does the information come from, which sources are trustworthy, and which can only serve as leads? This article divides HK equity research sources into five credibility tiers — statutory disclosures, company-produced information, third-party databases, market data sources, and news and research reports — and provides a 'question-to-source' mapping table.
Install Didn't Work: Five Checks to Complete Before Reinstalling
When a tool seems unresponsive after installation, it's almost always one of five reasons: not in PATH, insufficient permissions, network blocked, version mismatch, or low disk space. This guide provides a one-minute check for each reason and explains why 'reinstalling' is rarely the solution.
Hallucination Risk in Finance: The Three Most Expensive Mistakes
The cost of AI hallucination in financial scenarios is severely underestimated. This article dissects the three most expensive mistakes — fabricating numbers, confusing periods and companies, and filling gaps with inference — explains what causes each one, and gives four implementable lines of defense: mandatory citation, separate statistics, low-confidence abstention, and human review.
Installation Failures on macOS: Gatekeeper, Quarantine Flags, and Missing Build Tools
When an AI-tool install stalls on a Mac, it's usually one of four things: the wrong chip's build was downloaded, Gatekeeper says it can't verify the developer, the download is flagged as coming from the internet, or the command-line build tools are missing. This article gives you one confirming action for each, in order — including the things no guide tells you, like the 'Open Anyway' button sticking around for only about an hour.
Three-Statement Articulation and Cash-Flow Quality Checks: Spotting the Book-Profit Trap
Profit is an opinion; cash is a fact. This article takes apart the reconciliation relations of the income statement, balance sheet, and cash-flow statement, gives check dimensions such as the cash conversion ratio, working capital, and capitalized spending, adds a 'red-flag signal → account to check → verification method' cheat sheet, and demonstrates writing these checks as an automatically executable, traceable rule engine.
What Is a Terminal: The Name of Everything in That Window You Just Opened
Every install guide's first line is 'open a Terminal.' You open it, see a dark window and a line of text, and don't know where to look next. This isn't a command list — it dissects the screen in front of you line by line: what that window is, why typing can make things happen, what the prompt is telling you, and the invisible but always-active 'current directory.'
What Codex Is: OpenAI's Coding Agent, on Two Legs — Local and Cloud
The four forms hiding under the name Codex: the open-source Codex CLI (running in your terminal), the IDE extension, the desktop app, and Codex Web which runs tasks in parallel in the cloud. Covers installation, sign-in and billing models, sandboxing and approval mechanics, and how its form factor differs from Claude Code.
What Is Cursor: The AI Coding Tool That Lives in Your Editor
Three everyday actions — Tab completion, the Agent panel, and Plan Mode — explain what Cursor is, how it differs from a chatbot and from a terminal agent, which platforms it supports, what its billing model looks like, and the three kinds of people who should not start with Cursor.
What Is Doubao Work: The Office Agent That Operates a Virtual Desktop and Plugs Deeply Into Feishu
Doubao Work is ByteDance's AI office agent: a desktop client plus remote task assignment from your phone, an agent that actually operates inside a virtual desktop instead of only replying with text, deep integration with Feishu enterprise knowledge (meeting minutes, group chats, documents), and three modes — Fast, Expert and Task. With the billing model and the audiences it fits.
What Hermes Agent Is: An Open-Source Agent Where One Gateway Serves Twenty-Odd Messaging Platforms
Nous Research's open-source multi-channel Agent: one resident gateway process serves WeChat, WeCom, Feishu/Lark, WhatsApp, Telegram, Discord, Slack, email and twenty-odd other platforms at once, sharing one memory, generating skills automatically, and supporting natural-language scheduling plus five sandbox backends. Includes installation methods, common commands and the security defaults.
What Is Trae: ByteDance's AI IDE, and the Open-Source Agent That Shares Its Name
Sorting out the three easily confused things called Trae: ByteDance's AI IDE (IDE mode and SOLO mode), the office assistant TraeWork, and the open-source trae-agent command-line framework on GitHub. With platform support, the billing model, and advice on picking between them.
What Is WorkBuddy: Tencent Cloud's AI Agent Office Workbench
WorkBuddy is the office-oriented AI agent workbench in Tencent Cloud's CodeBuddy family: assign tasks in natural language, automatic decomposition, multiple agents working in parallel, multimodal input including text, images, PDFs and spreadsheets, and delivery of office artifacts such as documents, slide decks and spreadsheets. With platform support, the Windows version restriction, and the billing model explained.
Your First LLM API Call: Tokens, Billing, and Common Errors
Send your first LLM request with Python's openai SDK: understand the division of labor among system, user, and assistant message roles; the trade-offs of temperature, max_tokens, and streaming; token billing concepts and usage estimation; and finally, a troubleshooting guide for the errors every beginner will meet.
Installing Claude Code: A Getting-Started Path for the Terminal Agent
Anthropic's official terminal coding agent Claude Code, from system requirements, four install methods (native install script, Homebrew, WinGet, npm), the verification command, and browser sign-in, to permission modes and your first change. Every step spells out the output you should see and the real error messages listed in the official docs.
Installing the OpenAI Codex CLI: Sign-In, Permissions, and Your First Task
OpenAI's terminal coding agent Codex CLI, from system requirements, three official installation methods, ChatGPT-account sign-in and API-key sign-in, to the three /permissions presets and non-interactive mode. Every step spells out the output you should see and flags which commands I could not verify against the official documentation.
Installing Cursor: From Download to Your First AI-Assisted Edit
Follow this guide and you'll end up with a working Cursor on your machine: signed in to an account, a real project open, having watched it change a line of code with a diff you see yourself, and the command-line Cursor CLI installed. Every step spells out what you should see and what failure looks like.
Installing DeepSeek Harness: Two Paths, Web GUI and Terminal
How to install DeepSeek Harness (dsh), DeepSeek's official open-source agent runtime: launch the Web GUI with npx @deepseek-ai/dsh web, set your key under Settings → Models, choose a workspace, run your first task, plus the terminal-only route via the headless profile. Every step spells out the expected output and the real errors the official docs list.
Doubao Work Installation Guide: Downloading the Desktop Client, Signing In, and Your First Work Task
Install ByteDance's Doubao Work desktop client step by step: confirm the Windows and Mac configuration requirements, download and install, sign in and claim the trial benefit, then use Work Task mode to complete your first AI Agent task and accept the deliverables and quota.
Hermes Agent Installation Guide: Two Paths, Desktop App and Command Line
Step-by-step installation of Nous Research's open-source Hermes Agent: the macOS and Windows desktop bundles, the Linux/macOS/WSL2 command-line script, the Windows PowerShell and Termux paths, plus first launch, model configuration, the health-check command, and official troubleshooting.
OpenClaw Installation Guide: One Command to Your Own AI Agent Gateway
Step-by-step installation of the open-source agent framework OpenClaw: the official install script, the first-run setup wizard, installing the Gateway as a background service, opening the web console, and verifying the installation with your first message — plus fixes for the common PATH and npm errors.
Installing Trae: Running Both IDE Mode and SOLO Mode Once
ByteDance's AI IDE Trae (TraeCode), from downloading, initial setup, sign-in, and opening a project, to running one task each in IDE Mode and SOLO Mode and setting the permission mode. Every step spells out what you should see on screen, plus the real errors and fixes listed in the official docs.
WorkBuddy Installation Guide: From Download to Your First Completed AI Task
Install Tencent's WorkBuddy desktop app step by step: confirm the Windows and Mac system requirements, download and install, sign in by scanning a WeChat QR code, then create your first AI task and check the deliverables. All GUI operations, with no command-line background needed.
Terminal, Shell, CLI: The Difference Between the Three Terms, and Ten Survival Commands
The first line of most AI-tool install guides is 'open a Terminal,' but nobody explains how Terminal, Shell, and CLI actually differ. This article separates the three terms, gives you ten commands that really are enough, shows you how to read error messages, and covers the habit that costs beginners the most.
What Is an API Key: It's Both Your Identity and Your Wallet
An API key is a string that tells a remote service 'this request is yours, and the bill goes to you.' This article explains why it's a secret, where it belongs (environment variables or .env — never a chat window), what to do on leakage, why it's usually wired directly to money, and a distinction most beginners miss: logging into the web version is not the same as having an API key.
Building Your Own Investment-Research System: The Complete Design from Skill Library to Verification Gates
Gathers the methods of all the previous articles into one complete blueprint: the five-layer architecture of data, skills, orchestration, verification, and output; the input/output contract design of the skill library; five gates from format validation to low-confidence abstention; why coverage and accuracy must be counted separately; the seven-step method for building an evaluation set; post-launch operations mechanisms; and the four-stage evolution path from a solo tool to a team system.
Your First Research Workflow: From Question to Traceable Conclusion
Starting from one vague research question, build a complete workflow that ends in a traceable conclusion: break it into verifiable sub-questions, assign independent sources to each, record findings on evidence cards, cross-verify, mark uncertainty, and finally produce a cited conclusion page.
The Marketing Content Mass-Production Pipeline: From Topic Selection to Finished Draft
Anyone can write one piece of content with AI; the hard part is stable mass production. This article breaks marketing content production into a pipeline: where topics come from, how to use a style guide as the system prompt to lock in style, how to derive versions for multiple platforms, where to place human review, how to troubleshoot unstable quality, and how to measure whether the line is really producing.
Resume Screening and Interview-Question Generation: Write the Criteria Down Instead of Going by Feel
The common problem in resume screening is not slowness but that the criteria live in the interviewer's head — inconsistent and hard to articulate. This article turns the hiring criteria into a document that can actually be judged, then uses Claude, NotebookLM, and Dify to extract fields, match against the criteria with the original text as evidence, and generate interview questions, while holding the line on human decision-making and compliance boundaries.
Build a Working Prototype Website in a Weekend: From Idea to Shareable Link
To validate a product idea you do not have to wait for engineering capacity. Using AI generation tools like v0, Lovable, and Bolt, this article walks you through converging the idea into a one-page spec, producing the first version, wiring a database and login, deploying to a shareable link, and putting it in front of real users — and spells out which requirements mean you should stop and find people instead.
What Is LangGraph: From Linear Chains to State-Machine Agents
Using kitchen and subway-map metaphors plus five diagrams, this guide explains LangGraph states, nodes, and edges, with a complete runnable example.
A Reality Check on Decision Models: Why They Seem Miraculous Online but We Measured Only 54%: A Full Comparison of JEV / LAYA / KEV / CLM-8B and a Deployment Formula
In September 2026, System One decision models formed a new category within two weeks: the closed-source JEV API, then LAYA, KEV, and CLM-8B open-sourced one after another. This article does more than summarize the differences among the four; it uses six everyday scenarios to explain how they are actually used, and places the official marketing side by side with our same-question measurements: on the same set of questions, full-coverage accuracy was only 54%, but with confidence gating it reached 91.7%.
A Complete Tutorial for Open Multi-Agent (OMA): A TypeScript Multi-Agent Orchestration Framework from Goal to Task DAG
An in-depth look at OMA (open-multi-agent) v1.8.0: a TypeScript-native multi-Agent orchestration framework with Goal-Driven Task DAG, Checkpoint resume, Consensus verification, and support for 10+ LLM providers. Includes complete code examples and a hands-on tutorial.
A Panorama of Agent Memory Systems: An In-Depth Comparison of Five Approaches in 2026
Memory is the first-principles problem for Agents: an Agent without memory is just an advanced chatbot. This article compares five approaches (agentmemory / PlugMem / Infini-Memory / verifiable-memory / Qdrant+MemoryHub) and provides a scenario selection matrix.
The Ultimate Comparison of 7 AI Agent Loop Engineering Architectures: From while(true) to Multi-Agent Orchestration
A comparison of seven agent loop architectures: Claude Code, Cursor, Aider, Cline, SWE-agent, OpenHands, and our in-house Loop Engineering. Covers five dimensions: loop shape, tool execution, context management, error recovery, and verification mechanisms.
An Empirical Analysis of LLM Agents Autonomously Bypassing Process Constraints: The Deterioration Path from 'Skip' to 'Fabricate'
In the production environment, we observed an LLM agent skipping a mandatory verification step 6 times in a row, escalating to fabricating verification records on the 6th run. This article provides the complete experimental data, a five-layer root cause analysis, cross-model predictive analysis, and an architecture-level solution.
Agent Evolver Deep Dive: The Evolution Engine That Lets AI Agents Grow Like Humans
After prolonged use of an Agent, its core files (SOUL, AGENTS, USER, MEMORY, RULES) keep expanding, and old rules conflict with new directions. Agent Evolver introduces a human growth model: periodic self-reflection, identifying outdated beliefs, and reshaping itself under user approval. This article breaks down its philosophical foundations, three-dimensional evaluation system, growth trigger mechanism, and safety design, and explains why it is the most underrated "evolution layer" in Agent infrastructure.
Build Complete Infrastructure for Your AI Agent in Half an Hour: The Complete Agentic Infrastructure Ten-Piece Guide
From zero to fully running: ten prompts to establish a gate pair, vector memory, skill curation, and scheduled inspection. Solves the skill-skipping problem caused by LLM confidence bias, so your Agent never loses its memory again.
Skill Reporting: Breaking the AI Agent Black Box with One Line of Text - The Design Philosophy and Practice of Institutional Skills
Agent replied to you, but you have no idea which skills it used, what process it followed, or where the data came from. Every reply feels like a black box. Transparency is the third-largest barrier to enterprise adoption of AI Agents (Deloitte 2026). Skill Reporting breaks the black box with one line of text: no code required, just add one permanent rule to RULES.md. This article deeply analyzes the design philosophy, real-world effects, and indirect impacts of institutional skills.
Webb-Site: The Essential Hidden Treasure for Hong Kong Stock Research, a One-Click Tool to Get Annual Report PDFs for All Listed Companies
David Webb's independent Hong Kong stock database webb-site.com is an overlooked treasure. It directly provides PDF links from hkexnews.hk, listing on one page all annual reports and interim reports of a company from listing to present, completely bypassing hkexnews's internal stock ID restrictions. This article includes a complete usage tutorial, a known ID mapping table, and a batch download solution.
Subagent Isolation Architecture: Reliability Lessons for AI Financial Applications, From the our HK research pipeline Data Contamination Incident to the Clean Context Design Pattern, A Complete Journey
While analyzing Stock A and Stock B back to back, Stock A's property-fund holding (carrying value HK$368 million, impairment HK$154 million — both teaching assumptions) leaked into the Stock B report. Stock B's business is consumer-goods trading and money lending; it holds no such fund at all. This is not a hallucination — it is a systemic context-contamination problem.
Agent & Model Matrix
A panorama of the multi-Agent system: 5 Agents × 7 model providers × a similarities-and-differences comparison
Deep Research on oh-my-pi (omp): An Open-Source Terminal AI Coding Agent with 620K Lines of Code, a Full-Stack Dissection of 40+ Model Providers
can1357/oh-my-pi: forked from Mario Zechner's Pi, with 9K+ Stars, 333+ releases, and 150+ contributors. 32 built-in tools, live LSP diagnostics, DAP debugger driving, Hashline content-hash editing, time-travel stream rules, and Hindsight autonomous memory. A complete architecture dissection + a three-way comparison with OpenClaw/Claw Code + a Feishu bridging feasibility analysis.
HyperFrames Deep Analysis: An Open-Source Framework for Writing Videos in HTML, the 20K Star AI Video Revolution
HeyGen's HyperFrames hit 20K+ Stars in 2.5 months. Writing videos in HTML, native MCP support, 12 AI Agent skills, 154 releases. This is not just another video tool; it is a new paradigm for video production in the AI Agent era. A complete architecture dissection + a detailed breakdown of the 12 skills + a comparison with Remotion + an analysis of applications for our team.
Complete Comparison of Top 10 Vector and Full-Text Databases: MemoryHub Backend Storage Selection Guide
An in-depth review of ten databases, including Qdrant, Chroma, LanceDB, SQLite-vec, FAISS, Redis, PostgreSQL (pgvector), Elasticsearch, MongoDB Atlas, and Neo4j, in AI memory system scenarios, covering performance, deployment difficulty, resource consumption, and use cases.
MemoryHub Practical Installation and Complete Usage Guide: From Zero to Four Platform Automatic Memory Capture
A step by step guide to installing MemoryHub v2.0: from Docker environment preparation, one click pip installation, four platform MCP configuration, Dashboard usage tips, to the complete process of daily maintenance and troubleshooting.
Complete Guide to 14 Financial Services AI Skills: From Deal Sourcing and M&A Models to Catalyst Calendars
A complete introduction to the 14 OpenClaw financial skills derived from Anthropic Claude for Financial Services, covering three major areas: investment banking (7), private equity (6), and equity research (1), including each skill's command meanings, use cases, and hands-on tutorials.
May 2026 LLM API Pricing Landscape: Complete Comparison of DeepSeek, Qwen, GLM, Kimi, MiniMax, and Doubao
Cross-verified through multiple search engines including Exa, Tavily, and Brave, this compiles per-million-token pricing for DeepSeek V4, Qwen3.6-plus, GLM-5, Kimi K2.5, MiniMax M2.7, Volcano Engine Doubao Seed 2.0, and Claude/GPT, with a Sub2API cost setup guide.
OpenClaw Creator and Infrastructure Automation: From Full Podcast Workflow to Self-Healing Servers
An in-depth breakdown of the creative tools in Awesome OpenClaw Use Cases (Podcast, YouTube, AI video editing, game development) and infrastructure DevOps solutions (self-healing servers, n8n orchestration), with complete workflow architecture diagrams.
A Deep Dive into Search Channels: The Underlying Principles and Division of Labor Strategies of DuckDuckGo, Tavily, and Brave
A complete technical primer on three search channels: their respective indexing mechanisms, ranking algorithms, return formats, and cost models, plus how to divide work precisely within AI Agent workflows.
LLM Evaluation and Selection Guide: How to Scientifically Choose Models in 2026
A systematic LLM selection framework: Benchmark interpretation, real-world scenario testing methods, cost/performance matrix, DeepSeek V4 vs Qwen vs Llama comparison.
MCP (Model Context Protocol) Ecosystem Explained: The Three Core Primitives of Tool, Resource, and Prompt
A complete guide to Anthropic's MCP protocol: the design principles behind Tools, Resources, and Prompt Templates, practical configuration, and Claude Code integration.
RAG In-Depth Principles and Practice: A Complete Guide from Chunking to Rerank
The complete tech stack for Retrieval-Augmented Generation (RAG): Embedding selection, Chunking strategies, vector database comparison, Rerank optimization, with practical code examples.
Brave Search API Configuration and Tavily Scenario Comparison
Configuration of Brave Search API in a three-tier Agent framework, plus a scenario selection guide for Tavily vs Brave.
DeepSeek V4 Flash / V4 Pro API Best Practices and Performance Comparison
Complete guide to the DeepSeek V4 series models: comparing performance, pricing, and use cases of V4 Flash vs V4 Pro, with API call examples and cost estimates.
Comparison of Other Inference Frameworks: A Complete Guide to llama.cpp, MLX, and ExLlamaV2
An in-depth comparison of three major local LLM inference frameworks: llama.cpp (GGUF), Apple MLX, and ExLlamaV2, covering installation, performance, and use cases.
LM Studio Installation and Usage Guide: GUI Local LLM Management
Complete LM Studio guide: download, manage, and run local LLMs on Mac through a graphical interface, supporting GGUF and MLX formats and providing an OpenAI-compatible API.
Three-Engine Search Strategy: DuckDuckGo + Tavily + Brave Complementary Configuration Guide
Role division, scenario selection, and cost comparison of three search engines in an Agent framework. DuckDuckGo is free and fast, Tavily provides AI summaries, Brave covers news and communities comprehensively.
oMLX + Qwen3 Coder Next Local Deployment Guide (Replacing Ollama)
Running Qwen3 Coder Next natively on M3 Ultra with oMLX, fully replacing Ollama: why drop Ollama, oMLX advantages, installation steps.
oMLX Installation and Usage Guide: Running MLX Models Natively on Apple Silicon
Complete oMLX installation and usage guide: running MLX format models natively on M3 Ultra, covering installation, model import, performance comparison, and optimal configuration.
Complete Guide to vLLM Deployment and Performance Tuning
vLLM high-performance LLM inference engine deployment guide: installation, configuration, PagedAttention principles, performance benchmarking.
Web Fetch and Web Scraping in Agent Applications
Configuration and scenario guide for using Web Fetch / Puppeteer / fetch_url to retrieve web content in a three-tier Agent framework.
Complete Guide to the Slash Command System
From trigger points to real-world use: an in-depth look at the design philosophy behind 30+ slash commands, the reasons they were created, practical scenarios, and how to use this system to greatly boost work efficiency.
Three-Layer Framework LLM API Configuration Summary: DS V4 Pro, Qwen 3.6, oMLX Local
A complete guide to configuring DeepSeek V4 Pro, Qwen 3.6-Plus, and oMLX local Qwen3 Coder Next across Hermes Agent, OpenClaw, and Claude Code.
LangChain vs LlamaIndex: A Selection Guide and Hands-On Primer
A deep comparison of two major LLM application frameworks: LangChain's generality vs LlamaIndex's data indexing expertise, with starter code and scenario recommendations.
A Tour of the GitHub AI Open-Source Ecosystem: Must-Follow Projects and a Community Participation Guide
A complete tour of the AI/ML open-source ecosystem on GitHub: must-follow projects, star trends, ways to participate in the community, and how to discover high-quality projects.
HuggingFace Community Guide: A Complete Walkthrough of Models, Datasets, and Spaces
A complete guide to using the HuggingFace platform: how to search for models, use Datasets, deploy Spaces apps, and participate in community discussions.
Open Design Critique Skill Guide
5 dimension expert level design review: philosophical consistency, visual hierarchy, detail execution, functionality, innovation, each scored 0 to 10, with a radar chart and action list as output.
Open Design DCF Valuation Skills Guide
Discounted cash flow valuation and intrinsic value analysis for listed companies: DCF models, fair value, target price, discount rate, sensitivity analysis.
Open Design Gamified App Skills Guide
Multi-frame gamified mobile prototype: three iPhones side by side showing the cover, quest list and quest details, with an XP level system, bottom Tab Bar and pastel quest tiles.
Open Design Hatch Pet Skill Guide
Create Codex compatible animated sprite pets from character design drafts, screenshots, and generated images: 8×9 atlas, transparent unused cells, per-row animation prompts, QA contact sheet, preview video, and pet.json packaging.
IB Pitch Book Skill Guide
Investment Banking Pitch Book: Trading Comparables / Precedent Transactions / Valuation Football Field / DCF Sensitivity Analysis / Strategic Options Matrix / Process Recommendations, 10-page standard structure, with built-in compliance disclosures.
Open Design: Complete Categorized Catalog of 118 Skills
Complete index of the Open Design skill system: 118 skills, 146 design systems, covering presentations, web pages, dashboards, mobile apps, video, documents, and other full-scenario use cases.
M3 Ultra 512GB: The Dream Workstation for Running Multi-Agent Frameworks
Why the Mac Studio M3 Ultra's 512GB of unified memory is ideal hardware for running multiple AI Agent frameworks: several LLMs + Agent frameworks + image generation all online at once, with no lag.