AI tool comparison
CodeBurn vs Google ADK
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
CodeBurn
Token cost analytics and waste finder for AI coding tools
75%
Panel ship
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Community
Paid
Entry
CodeBurn is an open-source terminal dashboard that tracks and analyzes your token spend across Claude Code, OpenAI Codex, Cursor, OpenCode, and GitHub Copilot. It classifies coding sessions into 13 activity types — architecture, debugging, refactoring, code review, and more — and shows you exactly where your tokens are going. The standout feature is the optimizer: CodeBurn identifies wasteful patterns in your workflow — like repeatedly re-reading the same files, bloated context files, or MCP servers that are loaded but never used — and suggests concrete changes with estimated savings. It also tracks one-shot success rates per task type, helping you understand where AI is genuinely saving time vs. where you're fighting the tool. A macOS menu bar widget shows live token spend as you work, with a daily budget alert. Built by indie developer AgentSeal and shared as a Show HN, it picked up 80 upvotes and significant interest from developers who didn't realize how much they were spending on context re-reads alone. Open source under MIT license.
Developer Tools
Google ADK
Build multi-agent AI pipelines with Google's open framework
75%
Panel ship
—
Community
Free
Entry
Google's Agent Development Kit (ADK) is an open-source Python framework for building, evaluating, and deploying multi-agent AI systems. It gives developers the orchestration primitives needed to connect multiple AI agents into pipelines, workflows, and hierarchies — so one agent can spawn others, delegate tasks, share context, and coordinate on complex goals. Released alongside Gemini CLI in April 2026, it already has 8,200+ GitHub stars. ADK is model-agnostic but optimized for Gemini. It integrates natively with Google Cloud services including Vertex AI and Cloud Run, making it a natural fit for teams already in the Google ecosystem. Developers can define agent graphs in Python, add tool-calling capabilities, configure memory and state management, and deploy the result as a containerized service or serverless function. The framework enters a competitive space against LangGraph, AutoGen, and CrewAI — but Google's infrastructure integration and the free Gemini CLI tier make ADK a compelling choice for teams that want a managed path from prototype to production without managing their own orchestration infrastructure.
Reviewer scorecard
“I ran this on a week of Claude Code sessions and immediately found I was spending 30% of my tokens re-reading the same five config files. The menu bar widget is the killer feature — seeing the cost counter tick up while you work changes your behavior instantly. Instant install for anyone serious about AI coding.”
“If you're already on Google Cloud, ADK is the cleanest path to multi-agent production systems right now. The Python API is intuitive, the Vertex AI integration removes a lot of DevOps overhead, and 8,200 stars in a few weeks means the community is already finding it useful.”
“The 13 activity categories feel arbitrary and require calibration. More importantly, this is fundamentally a symptom-treating tool — the real fix is better context management built into the AI tools themselves. And if you're on a flat-rate API plan, cost tracking is largely irrelevant.”
“LangGraph has a year head-start, a larger ecosystem, and works with every model provider. ADK is arguably just a Google-flavored re-skin with better GCP hooks. Unless you're already committed to Google Cloud, the switching cost isn't worth it yet.”
“Observability for AI token usage is an entire category about to explode. As agentic workflows scale from individual developers to teams and enterprises, understanding where tokens go becomes as important as understanding where CPU cycles go. CodeBurn is early but directionally correct.”
“Multi-agent orchestration is the infrastructure layer that will define how AI systems are built for the next decade. Google open-sourcing ADK while giving away Gemini access for free is a land-grab for developer mindshare — and it's working.”
“Even for non-coding creative work — writing, research, brainstorming — understanding which prompting patterns are wasteful vs. effective is valuable. The one-shot success rate tracking by task type is a genuinely novel idea I haven't seen anywhere else.”
“For content teams building automated pipelines — research agents feeding writing agents feeding publishing agents — ADK provides the connective tissue without requiring a backend engineer to wire it all together. The visual graph debugging alone is worth the switch from manual chaining.”
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