Herdr vs Taste Lab: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Herdr and Taste Lab — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
H
Herdr
Ogulcan Celik
Herdr is a terminal-native agent multiplexer — every coding agent at a glance, real terminal views, detach and reattach anywhere without losing sessions.
Key features
- Agent Multiplexer: See every running coding agent at once with real terminal views — blocked, working, or done — instead of wrapped or interpreted output.
- Detach and Reattach Anywhere: Sessions survive restarts and can be reattached from any terminal or over SSH so long-running agents keep working in the background.
- Socket API for Agents: A pure socket API lets agents themselves spawn panes, read output, and wait on each other, with a documented agent-skill.
- Keyboard + Mouse First Class: tmux-style prefix keys plus click, drag, and split — pick whichever interaction fits the moment.
- Plugin Marketplace: Extend panes and workflows with plugins from the herdr.dev plugin marketplace.
- Single Rust Binary: Distributed as one Rust binary (no Electron), installable via curl script, Homebrew, or mise, with a Windows PowerShell beta.
Best for
- Coding Agent Fleet Management: Watch a swarm of Claude, Codex, or Cursor agents in one dashboard while they work on different repos.
- Long-Running Agent Jobs: Kick off multi-hour agent tasks, detach, and reattach from a laptop later to check status without losing progress.
- Remote Development: SSH into a workstation and reattach the exact multiplexer session, so agents keep running on the server between sessions.
- Agent-to-Agent Orchestration: Use the socket API so one agent can spawn sub-agents in new panes and wait on their output.
- Terminal-Centric Workflows: Replace ad-hoc tmux + shell tricks with a purpose-built multiplexer that understands agent lifecycles.
Taste Lab
Sen Lin
Taste Lab is a Claude Code skill that turns any URL into a complete design context: design tokens plus the reasoning and trade-offs behind every choice.
Key features
- Design Map Extraction: Captures every color, font weight, spacing value, radius, and shadow with exact px/hex/ratio citations across 20 measurement categories.
- Taste DNA Inference: Derives four design principles, each with a Trigger, Decision, Reason, Evidence, and Trade-off explaining why each choice was made.
- Four-Agent Pipeline: Runs Extract, Detect Patterns, Infer Taste, and Observer stages, each reading the page through a sharper lens.
- Anti-Slop Quality Gate: A final critic stage runs anti-slop checks and validates JSON before writing output.
- Dual File Output: Writes a {domain}.md and {domain}.json that any AI agent can build from.
Best for
- Cloning Design Systems: Give an AI agent a complete, reasoned design context to rebuild a site's look and feel.
- Design Reviews: Understand the deliberate trade-offs behind a website's visual decisions.
- Agent-Assisted Frontend Work: Feed structured taste files into coding agents so they make the right call on unseen pages.
- Design Token Auditing: Extract and document a site's full token set with cited measurements.