pldpld

We've been building voice agents across Retell, VAPI, LiveKit, and Bland, and the testing story is... rough. Every platform has its own config format, there's no shared way to define what "correct" looks like, and most teams end up doing manual QA by literally calling their agent and listening. So we built voicetest.

voicetest is an open source (Apache 2.0) test harness that works across voice AI platforms. You import your agent graph from any supported platform (or define one from scratch), write test scenarios with expected behaviors, and voicetest simulates conversations and evaluates them with LLM judges that score each turn 0.0-1.0 with written reasoning. It also ships global compliance evaluators for things like HIPAA, PCI-DSS, and brand voice consistency. The core abstraction is an AgentGraph IR that normalizes across platform formats, so you can convert between Retell, VAPI, LiveKit, and Bland configs and test them all the same way.

Quick start:

``` uv tool install voicetest voicetest demo --serve ```

That gives you a web UI at localhost with a sample agent, test cases, and evaluation results you can poke at. There's also a CLI, a TUI, and a REST API. It integrates into CI/CD with GitHub Actions, uses DuckDB for persistence, and includes a Docker Compose dev environment with LiveKit, Whisper STT, and Kokoro TTS. If you have a Claude Code subscription, voicetest can pass through to it instead of requiring separate API keys for evaluation.

GitHub: https://github.com/voicetestdev/voicetest Docs: https://voicetest.dev API reference: https://voicetest.dev/api/

I built wt to manage the coordination overhead of running multiple AI coding agents (Claude Code, Codex, etc.) concurrently on the same repository.

The problem: I'd spin up 3-4 agents working on different features simultaneously, then conflict on files, and resolving those conflicts burns agent context. Git worktrees solve the isolation problem but the native CLI is verbose, lacks primitives for managing multiple sessions, and I'd have to manage persistence (folders to store the trees) separately.

wt wraps git worktree in an interface designed for this workflow:

  wt new feature/auth    # creates worktree + spawns subshell
  (wt:feature/auth) $ claude
  exit
  git merge feature/auth

Also integrates with tmux to coordinate agent sessions—wt session watch shows which agents are actively processing vs idle by monitoring pane output buffers.

There's a /do skill for Claude Code that implements issue-driven workflows: /do gh 123 fetches the GitHub issue, creates a worktree with a branch derived from the issue, and populates the agent context with the description.

Written in Rust. Binaries for macOS/Linux.

https://github.com/pld/wt

Blog post with more detail: https://peet.ldee.org/general/2026/01/26/wt-git-worktree-orc...