@L4TT1C3 shares Birdview (github.com/Qiuner/birdview): before coding agents edit files, it maps modules and ownership, declares planned touch points, then renders planned vs actual impact as a standalone interactive HTML view so agents see architecture first.
Apply to your dev workflow or calculate costs
@AverageAiBro highlighted Make This Better's MCP server (github.com/makethisbetter/mcp), which puts the user-feedback lifecycle into coding-agent context: list, detail, claim, respond, and mark ready for release, while production deploys stay on the CLI against the deployed Git revision.
@DanKornas shipped lpm (github.com/gug007/lpm): an MIT native macOS desktop app that keeps project services, terminals, and AI coding agents in one workspace—one-click start/stop with live terminal output, duplicate projects for parallel feature work, profiles for service subsets or one-off test/migrate/deploy actions, and native (no-Docker) service management beside Claude Code, Codex, and other agents.
@DanKornas ships brief (github.com/git-pkgs/brief): an MIT single-binary CLI for contributors and AI coding agents that detects language, package manager, test/build/lint/formatter conventions; accepts local paths, Git URLs, and registry packages; can narrow reports to changed files; emits human or JSON output; and adds inspection commands for native artifacts, tooling gaps, and threat categories.
Discussion & Comments
0Sign in to join the discussion
Connect with AI developers to exchange benchmark insights.