Agent-Skills

Benjamin-Plus is a JetBrains-published, MIT-licensed token-efficiency skill for coding agents that measurably cuts cost per task by up to 18% and total tokens by up to 22% without detectable quality loss. In this 2026 review we walk through the independent paired A/B results, the five habits it teaches, the decisive finding that you must inject it rather than install it, and a practical adoption checklist for Claude Code, Codex, and Cursor. ...

Every team can get an AI coding agent to write code once; almost nobody gets the same result twice. A software factory agent skill fixes exactly that: it packages a repeatable agents-plus-code workflow into one Claude skill you stamp into any repository, with the control plane living in deterministic Python rather than in a prompt. By the end of this guide you will know how to build your own repeatable workflow, where the human still makes decisions, and the real statistics behind the skills movement. ...

Film studio agent skills are installable AI workflows that condense the entire production pipeline behind a $2M AI feature film into seven ordered stages, from script breakdown to locked, generation-ready shot prompts. They solve the core problem of AI video — that models have no memory between generations — by using locked references, asset passports, and written gates that refuse to let inconsistent work through. The result is a reproducible pipeline that ran a 110-minute film in four weeks for roughly $2M, about 50x faster than a traditional indie production. ...

ARC-Skill is a lightweight agent skill that lets an unmodified Claude Code agent finish all 25 ARC-AGI-3 games and all 183 levels at a perfect 100.00 RHAE score, using just 7,645 actions versus a median human’s 17,135. It works by enforcing a single rule: before the agent presses any button, it must write down exactly what that press will do to the grid, and the harness refuses to act until a prediction is recorded and graded. This article explains how that one rule unlocks frontier-level performance, how ARC-Skill compares to heavier harness systems, and what it teaches about agentic skill engineering. ...

GitHub Copilot code review has reached a major milestone with the general availability of agent skills and MCP (Model Context Protocol) server support, announced on July 29, 2026. These features transform Copilot code review from a static analysis tool into an extensible platform that understands your team’s coding standards, integrates with your existing toolchain, and delivers context-aware feedback on every pull request. What’s New — Agent Skills and MCP Go GA On July 29, 2026, GitHub announced that agent skills and MCP server support for Copilot code review are now generally available for all Copilot Pro, Pro+, Business, and Enterprise users. This marks the culmination of a public preview that began on June 2, 2026, and represents GitHub’s most significant investment in code review intelligence to date. ...

Introduction — Why Source-Backed Research Matters for AI Agents A product deep research agent skill is a reusable capability that equips AI coding agents like Claude Code, Cursor, and Windsurf to autonomously gather, verify, and synthesize information about products, companies, and markets from real sources — producing structured, citation-backed output instead of hallucinated summaries. Without source-backed research, AI agents cannot be trusted for production-grade competitive analysis, due diligence, or market intelligence, because they default to generating plausible-sounding but unverifiable claims. This guide explains how to build such a skill from the ground up. ...

If you’ve been using AI coding agents for more than a few months, you’ve hit the same wall I have: every new project needs the same setup — linting rules, test conventions, deployment scripts, API patterns — and you end up repeating yourself in prompts or pasting the same instructions into every new session. Agent skills are the fix, and in 2026 every major platform has shipped their own version. But they’re not all the same, and picking the wrong one for your team costs real time. ...

If your coding agents can’t see your artifact repository, they’re flying blind. They’ll guess dependency versions, hallucinate package names, and suggest upgrades that don’t exist. But giving an AI agent direct access to Artifactory is a bad idea — one prompt injection and your entire binary repository is an attack surface. JFrog solves this with two complementary paths: JFrog Skills (open-source agent skills) and the JFrog MCP Server (remote SaaS MCP server). Both give agents safe, governed access to artifact context, but they work differently and suit different use cases. Here is how both work, when to use each, and how to set them up without compromising security. ...

If you’re using AI coding agents in 2026, you’ve probably hit the wall where your agent needs the same workflow — review a PR, run a specific test pattern, deploy to staging — and you end up pasting the same instructions every time. VoltAgent’s awesome-agent-skills repository solves that. It’s a curated collection of 1,000+ reusable agent skills compatible with Claude Code, OpenAI Codex, Cursor, Gemini CLI, and more. With 27,286 stars and 2,922 forks as of July 2026, it’s the largest community-driven skills directory in the ecosystem. Here’s how to use it, how to evaluate skill quality, and how to contribute your own. ...

Agent Skills supply chain security means treating every SKILL.md, referenced file, script, and marketplace update as executable influence over your AI agent. In practice, skills are closer to npm packages or CI actions than documentation, because a small metadata change can redirect planning, tool use, file access, and data movement. Why did Agent Skills become a supply chain problem in 2026? I’ve found that teams adopt Agent Skills for the same reason they adopted package managers: reuse beats rebuilding every workflow by hand. A skill can package conventions for code review, deployment, incident response, design handoff, or data analysis. The format is intentionally lightweight, which is exactly why it spreads quickly across tools such as Claude Code, OpenAI Codex, Cursor, GitHub Copilot, Gemini CLI, VS Code, Windsurf, and OpenClaw-style marketplaces. ...