RUC DataLab released SkillAdam, an open-source tool (MIT license, Python 3.10+) that automatically improves AI agent SKILL.md files. It tests a skill on relevant tasks, learns from results and prior revision feedback, and applies only changes that pass evaluation. It ships as integrations for Codex, Claude Code, Cursor Agent, and GitHub Copilot, letting developers optimize skills inside their existing agent.
The open-source quiron skill, installable via the skills CLI for coding agents like Claude Code, Codex and Cursor, rewrites AI-generated prose to remove machine-writing tells and then measures the result against human writing baselines. It requires no API key and runs on the agent's existing model.
The open-source quiron skill, installable via the skills CLI for coding agents like Claude Code, Codex and Cursor, rewrites AI-generated prose to remove machine-writing tells and then measures the result against human writing baselines. It requires no API key and runs on the agent's existing model.
A developer using Claude Code and Codex asks whether to add GitHub Copilot Pro, given IT restrictions limiting them to the Copilot extension in VS Code. They seek advice on plan value and its relation to the agents window, as they work as a data engineer on Fabric.
A developer using Claude Code and Codex asks whether to add GitHub Copilot Pro, given IT restrictions limiting them to the Copilot extension in VS Code. They seek advice on plan value and its relation to the agents window, as they work as a data engineer on Fabric.
UsageDeck is an open-source desktop dashboard for tracking AI usage across 13 providers, including Claude Code, Codex, and Cursor. It runs locally, reuses existing credentials, and offers quota alerts and pacing. It solves the problem of monitoring usage and costs for developers using multiple AI tools.
UsageDeck is an open-source desktop dashboard for tracking AI usage across 13 providers, including Claude Code, Codex, and Cursor. It runs locally, reuses existing credentials, and offers quota alerts and pacing. It solves the problem of monitoring usage and costs for developers using multiple AI tools.
Multiple Reddit threads in late August and early September 2026 describe code review breaking down as developers use Cursor, Claude Code, Codex, and Copilot to generate large features fast. One team merged 214 PRs in a month with the poster properly reading about 12, and another calls agent diffs of 20-40 files unreviewable despite green tests. Teams are debating which AI first-pass tools (CodeRabbit, Copilot review, Claude as a second model) add real value versus noise.
Multiple Reddit threads in late August and early September 2026 describe code review breaking down as developers use Cursor, Claude Code, Codex, and Copilot to generate large features fast. One team merged 214 PRs in a month with the poster properly reading about 12, and another calls agent diffs of 20-40 files unreviewable despite green tests. Teams are debating which AI first-pass tools (CodeRabbit, Copilot review, Claude as a second model) add real value versus noise.
A YouTube talk by Paul Bakaus presents Impeccable, a design skill that runs on top of coding harnesses like Claude Code, Copilot, Cursor, and Codex. Instead of automating design, it loads vocabulary like 'bolder' and 'quieter' with project-specific meaning so developers steer AI-generated design iteratively. Bakaus argues one-shot design fails because good design is context-rich and opinion-laden, and he rejects building an automatic mode.
A YouTube talk by Paul Bakaus presents Impeccable, a design skill that runs on top of coding harnesses like Claude Code, Copilot, Cursor, and Codex. Instead of automating design, it loads vocabulary like 'bolder' and 'quieter' with project-specific meaning so developers steer AI-generated design iteratively. Bakaus argues one-shot design fails because good design is context-rich and opinion-laden, and he rejects building an automatic mode.