Claude Code

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. ...

Anthropic is quietly A/B testing reduced default effort levels in Claude Code, and the change does not make the coding agent dumber — it makes it less proactive. Effort controls how much autonomous work Claude performs per turn (reading files, running tests, double-checking its own output) before responding or asking for context. When the default drops, you get faster, cheaper turns that skip deep investigation, which is fine for scoped tasks but can silently degrade complex multi-file refactors. ...

Open-source memory for coding agents synced over SSH lets you carry your AI assistant’s context, preferences, and project knowledge across every machine you work on — without a cloud service. The most portable approach is a git-backed markdown store: symlink your agent’s memory files, push and pull over SSH, and let auto-sync hooks handle the rest. This guide walks through the three proven methods and how to pick the right one. ...

Heimdall is an open-source, CPU-only knowledge layer that gives AI coding agents a verified, self-healing memory across every repository you work in. Instead of returning plausible-but-unverified matches, every search result carries a trust verdict — STRONG, WEAK, REBUILT, or STALE — re-checked against your live filesystem at query time. It indexes with tree-sitter and local embeddings, spends zero tokens on memory maintenance, and re-anchors moved files automatically. What is Heimdall and why does it exist? Heimdall is a trust-verified knowledge layer built specifically for AI coding agents. It was released on Hacker News on August 22, 2026, and is published on npm as @ariantdeva/heimdall at version 0.2.1. The project’s core claim is simple: most agent memory tools return results that look right but have not been checked against the actual state of your codebase. Heimdall exists to close that gap. ...

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. ...

If you have ever run more than three AI coding agents side by side, you know the pain: terminal tabs stop scaling, output scrolls past, and you cannot tell which agent is doing what. A growing wave of 2026 tools answers by turning your agent fleet into a walkable pixel-art office, where each Claude Code or Copilot CLI process gets a desk, an NPC-like chat bubble, and a live terminal you can peek over. This review explains how these tools work, why they emerged, and whether running your agents in an office is genuinely useful or just a pretty dashboard. ...

The n8n Governance Kit is a one-click way to deploy a governed n8n instance into your own Railway account and operate it safely with Claude Code. It provisions n8n with zero-secret handling, ships native MCP and Claude skills, and enforces agent-based governance so production workflows stay reliable. This guide explains the architecture, the deploy flow, and how to operate it. What Is an n8n Governance Kit and Why You Need One in 2026 An n8n governance kit is a packaged set of rules, skills, and deployment tooling that lets you run n8n in production without letting automation quality slip. Provisioning n8n is a commodity in 2026 — any developer can spin up an instance. The real product is keeping a non-technical user’s workflows from breaking once they are live. ...

What is Kontext CLI? Kontext CLI is an open-source credential broker and runtime security tool built specifically for AI coding agents. It intercepts every tool call made by agents like Claude Code, Codex, and Claude Cowork, brokers short-lived credentials at request time, and enforces security policies before any action reaches your infrastructure. Unlike traditional secrets managers that just store credentials, Kontext actively controls how and when agents use them. What is a Credential Broker for AI Agents? A credential broker is a security layer that sits between an AI coding agent and the services it needs to access. Instead of giving the agent a long-lived API key or database password, the broker issues short-lived, scoped credentials on demand for each individual tool call. The agent never holds the actual secret — it receives a temporary token valid only for the specific operation it needs to perform. ...

Ponytail Improved is an AI agent skill that teaches coding agents to think like the laziest senior developer on your team — the one who writes the minimum viable solution, reuses existing code, and delivers faster with fewer bugs. By enforcing a six-rung laziness ladder before any code is written, Ponytail reduces AI-generated code by 54% on average while keeping 100% of safety guards intact, making your agent cheaper, faster, and more reliable. ...

Introduction — The Rise of Kotlin-Specific AI Coding Benchmarks For years, AI coding benchmarks have been dominated by Python and TypeScript. SWE-bench, HumanEval, and MBPP all lean heavily on these languages, leaving Kotlin developers wondering how well AI agents actually handle JVM-based code, Android development, and Kotlin-specific idioms. In July 2026, JetBrains changed that by releasing the official Kotlin Benchmark for AI Coding Agents — a rigorous, open-source evaluation framework built on Multi-SWE-bench infrastructure that measures how well AI coding agents resolve real-world Kotlin software engineering tasks. ...