Github-Copilot

The agent handoff contract standard you are looking for is Relay Task Kernel (RTK): a zero-dependency CLI that consolidates the four per-agent instruction files — AGENTS.md (Codex), CLAUDE.md (Claude Code), GEMINI.md (Gemini CLI), and .github/copilot-instructions.md (Copilot) — into one shared contract with thin pointer files, four scoped markdown memory files, and an idempotent merge protocol. Instead of maintaining the same rules four times and watching them drift apart, RTK gives every agent one source of truth. This guide explains the problem, how RTK works, the merge and memory contracts, presets, and how it compares to alternative handoff tools. ...

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. ...

What Are AI Coding Tool System Prompts and Why Do They Matter? System prompts are the hidden instruction sets that define how AI coding tools behave, think, and interact with developers. Every major AI coding assistant — from Claude Code to Cursor, OpenAI Codex to Windsurf — operates on a carefully crafted system prompt that encodes its personality, tool usage rules, safety constraints, and communication style. In 2026, these prompts have become a matter of public fascination: the largest GitHub collection of AI tool system prompts has amassed over 141,981 stars, and The Washington Post covered system prompt extraction as a mainstream security story in May 2026. Understanding these prompts reveals not just how AI tools work, but how their creators want them to think. ...

Your AI Coding Assistant Has a Hidden Bias — and It’s Reshaping the Software Ecosystem I’ve been running AI coding agents daily for over a year now — Claude Code, Cursor, GitHub Copilot — and I’ve noticed something unsettling. When I ask them to generate a React component, the output is near-perfect on the first try. When I ask for the same thing in SvelteKit or Solid, I get hallucinated APIs, wrong imports, and code that looks like someone read a blog post from 2023 and guessed the rest. ...

GitHub launched the Copilot App as a technical preview at Microsoft Build 2026, and it is now generally available for Windows, macOS, and Linux. This is not a Copilot chat plugin inside VS Code — it is a standalone desktop application built around agent-native development, with isolated git worktrees for parallel sessions, Canvases for bidirectional collaboration, and Agent Merge for automating the PR-to-production pipeline. I have been testing it since the preview, and here is what actually matters about the GA release. ...

GitHub Copilot SDK reached GA on June 2, 2026, and it is best understood as an embeddable agent runtime, not a chat wrapper. It gives your app Copilot’s planning, tool calling, file edits, streaming, multi-turn sessions, MCP, hooks, and tracing across TypeScript, Python, Go, .NET, Java, and Rust. I have built enough agent integrations to be suspicious of “SDK” announcements that are mostly a thin prompt API with a nicer package name. The GitHub Copilot SDK is different because it exposes the same runtime layer behind Copilot CLI: your application talks to an SDK client, the SDK talks to Copilot CLI server mode over JSON-RPC, and the runtime handles the agent loop. That matters when you need an agent to inspect files, request permissions, stream events, call tools, and stay useful across multiple turns. ...

If you’re running Copilot Enterprise across a few hundred engineers, you’ve probably stared at the usage dashboard and asked yourself: can I trust these numbers? The short answer is yes, with caveats. The longer answer is what this article is about. I’ve been working with Copilot’s metrics pipeline across several mid-to-large enterprise deployments, and I keep running into the same three questions: How accurate are these metrics? What’s actually covered by the data? And how do I build reliable team-level reports when the API doesn’t give me a team endpoint? This guide tackles each of those head-on. ...

If you’re paying for GitHub Copilot Enterprise across a 200-person engineering org, you need to know whether it’s actually moving the needle. The good news: GitHub now exposes surprisingly detailed usage metrics through dashboards, REST APIs, and NDJSON exports. The bad news: the data has sharp edges that will mislead you if you don’t understand how it’s collected and attributed. I’ve spent the last few months working with Copilot’s metrics pipeline across several enterprise deployments, and this guide covers what I’ve found — the five metric categories, how data actually flows from IDE to dashboard, the API endpoints you’ll need, and the attribution gotchas that will trip you up. ...

On June 25, 2026, the Mozilla 0DIN team demonstrated an attack that should change how every team deploys AI coding agents. They published a normal-looking Python repository on GitHub. A developer cloned it and pointed Claude Code at it. The agent read the README, installed the requirements, hit a routine initialization error, and — trying to be helpful — ran the suggested fix. That fix queried a DNS TXT record, decoded the value, and executed it as a shell command, opening a reverse shell on the developer’s machine. ...

SonarQube MCP Server is SonarSource’s official open-source bridge between AI coding agents and SonarQube’s code quality engine. Instead of context-switching to a browser dashboard or running CLI scans manually, your AI agent can query issues, check quality gates, analyze code snippets, review security hotspots, and even change issue status — all through MCP tool calls. Version 1.19.0 ships with 20+ tools, supports every major AI client from GitHub Copilot to Claude Code, and works with both SonarQube Cloud and self-hosted Server instances. ...