Orchestrate-Live

Monitor all your AI coding CLI agents in one place. OrchestrateLive tracks speed, token usage, context windows, and execution errors. Stop staring at text logs—start orchestrating.

Comment

OrchestrateLive

📌 The Problem

  • Who experiences this problem? Modern software engineers, AI developers, and technical builders orchestrating multi-agent systems and AI coding CLI tools (such as Claude Code, Cursor, Kilo CLI, and custom agents).
  • What is the problem? As software development shifts from manual coding to orchestrating autonomous AI CLI agents, developers face severe terminal chaos. Running multiple agents concurrently floods screens with dense, raw, wall-of-text terminal logs.
  • Why does it matter? Developers suffer cognitive fatigue from constantly babysitting text streams to check whether an agent has stalled, thrown an error, or completed its run. Without real-time visibility into generation speed, token consumption, and context saturation, workflows become slow, unpredictable, and expensive.
  • Existing limitations & gaps: Current terminal environments offer zero visual lifecycle feedback or ambient progress cues. Existing monitoring platforms require intrusive SDKs or cloud services that pollute local repositories and risk exposing proprietary code to external servers.

💡 The Solution

OrchestrateLive is a lightweight, zero-dependency, local-first observability command center that transforms raw AI CLI outputs into an interactive visual dashboard with ambient audio telemetry.

  • Unified Multi-Agent Monitoring: Aggregates parallel agent runs into a single dashboard, allowing developers to switch between a bird's-eye view and focused, single-agent inspection tabs.
  • Visual Lifecycle Tracking: Translates text streams into a dynamic visual flowchart mapping live execution states: Thought ➜ Planning ➜ Reading ➜ Writing ➜ Terminal ➜ MCP ➜ Done
  • Real-Time Telemetry & Token Metrics: Displays immediate metrics on pipeline latency, generation speed (tokens/sec), token usage (input/output), and context window limits.
  • Synthesized Ambient Audio: Uses native Web Audio oscillators to generate programmatic audio cues for agent milestones, eliminating the need to constantly monitor the screen.
  • One-Click Diagnostic Filters: Isolates runtime errors, MCP tool invocations, and agent planning decisions instantly from the live feed.
  • 100% Local & Privacy-Preserving: Runs standalone outside the developer's project directory via local storage and WebSockets, ensuring zero repository pollution and zero cloud exposure.

🛠️ Development & Process

  • Frontend Architecture: Built using native Vanilla HTML5, CSS3 (featuring a dark-mode glassmorphic interface and hardware-accelerated telemetry wave animations), and native JavaScript to ensure instantaneous rendering without framework overhead.
  • Ambient Audio Engine: Developed a sound synthesizer entirely via the browser's native Web Audio API, generating clean sound cues without bundling external audio assets.
  • Local Backend Broker: Implemented a lightweight Node.js and Express server with a high-throughput WebSocket (ws) layer to process and broadcast agent telemetry at sub-millisecond latency.
  • Decoupled Session Watcher: Built a local workspace listener that automatically discovers active CLI agent sessions without requiring any SDK, package, or configuration file inside the user's active codebase.

⚠️ Challenges & Iterations

  • Burst Token & Speed Computation: AI agents generate output in sudden bursts rather than continuous streams. Calibrating real-time token counts, context percentages, and generation speed without dropping packets or spiking CPU usage required extensive tuning.
  • Parallel Stream Synchronization: Multiplexing several concurrent agent streams to the UI caused race conditions and out-of-order logs. This was resolved by designing an event-driven serialization handler to sequence updates smoothly.
  • Capturing High-Frequency Actions: Balancing continuous file-reading, bash execution, and tool-call logging without imposing latency on the agent's primary task required fine-tuned event batching.

🏆 Accomplishments & Value Delivered

  • Unified Multi-Agent Integration: Seamlessly consolidated disparate AI coding CLI tools into a single command center with dynamic tab switching.
  • Zero Repo Clutter: Built a fully decoupled architecture that runs in a standalone folder with a single command (node server.js), requiring no dependencies or config files in the user's active codebase.
  • Instant Error & Step Isolation: Transformed chaotic terminal logs into an actionable, filterable activity feed for one-click debugging.
  • Ultra-Lightweight Footprint: Avoided heavy libraries and complex build pipelines, allowing the dashboard to run smoothly with minimal CPU and RAM usage.

🔮 What's Next for OrchestrateLive

  • Dedicated IDE Sidebar Extension: Embedding the live telemetry feed directly into VS Code and Cursor sidebars.
  • Smart Budget & Token Alerts: Threshold alerts to warn developers before an agent exceeds token or context limits.
  • Direct Agent Interventions: Pause, steer, and terminate controls from the UI when loops or failures are detected.
  • Session Export & Replay: One-click exports of agent timelines to benchmark agent performance and share debugging traces.
Share this project:

Updates