AI tool comparison
Craft Agents vs Litmus
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Craft Agents
Open-source desktop app for multi-session Claude agents with MCP & APIs
75%
Panel ship
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Community
Free
Entry
Craft Agents OSS is an open-source desktop application built on Anthropic's Claude Agent SDK, offering a polished GUI for managing multiple AI agent sessions simultaneously. Built by Luki Labs and released under Apache 2.0, it fills the gap between raw API access and the full Claude.ai web interface — giving developers and power users a native desktop experience with serious capability depth. The app supports three permission modes that make it genuinely useful for real work: Explore (read-only, safe for exploring codebases), Ask to Edit (approval-based, for supervised automation), and Auto (unrestricted, for trusted workflows). It connects to MCP servers, REST APIs from Google, Slack, and Microsoft, and local filesystems, with real-time streaming responses and full tool call visualization. A multi-session workflow with Todo → In Progress → Needs Review → Done status tracking makes it feel more like a project management system than a chat interface. Built on Electron + React with encrypted credential storage and a headless server mode, Craft Agents is architecturally serious. It's available as a one-line installer for macOS, Linux, and Windows. With the Claude Agent SDK gaining traction, this is the first polished desktop client that treats agents as long-running workflows rather than single-turn conversations.
Developer Tools
Litmus
Unit tests for AI — find the cheapest model that passes your prompts
75%
Panel ship
—
Community
Free
Entry
Litmus is an open-source testing framework for AI prompts — the missing unit test layer between "it worked once" and "it works reliably across models." You define test cases (prompt + expected behavior assertions), run them against multiple models simultaneously, and Litmus reports which models pass and — crucially — projects the cost difference at scale. The goal: find the cheapest model that meets your quality bar. The workflow is intentionally simple: litmus init to scaffold a test suite, write YAML test cases describing prompt inputs and assertions, then litmus run to execute against your chosen model roster. Results show pass/fail per model, inference latency, and a cost-at-scale projection (e.g., "using claude-haiku instead of opus would cost 94% less at 1M requests/day with 97.3% pass rate"). This directly addresses one of the most expensive habits in AI development: defaulting to the most capable (and most costly) model for every task. Litmus launched fresh with 74 GitHub stars in its first hours, suggesting real demand. It integrates with the Anthropic, OpenAI, and Google APIs and supports custom model endpoints for local testing.
Reviewer scorecard
“The three permission modes — Explore, Ask to Edit, Auto — is the right model for how I actually use agents. I want read-only exploration when I'm learning a codebase and auto mode when I'm in flow. That plus MCP server support makes this my new default agent UI.”
“Every production AI team needs this and most are doing it manually with spreadsheets. The cost projection feature alone is worth shipping — I've watched teams spend 10x more than necessary on inference because they never systematically tested cheaper models. This is the tooling that makes responsible model selection practical.”
“Electron desktop apps for AI agents have a graveyard of predecessors — most people end up in the terminal or the browser anyway. The Claude-only model dependency is also a real limitation; when Anthropic changes their SDK or pricing, the whole platform needs to adapt.”
“The fundamental challenge with prompt testing is that assertions are hard to write well — defining 'correct' AI behavior is often subjective and context-dependent. New project with 74 stars means no battle-testing, no community-contributed assertion patterns, and no guarantee the test framework won't produce false confidence. Wait for v1.0 with real-world case studies.”
“Agent session management as a first-class concept is where the whole category is heading. Craft Agents is early proof that the IDE model — multi-session, persistent, project-aware — is the right UX paradigm for AI agents, not the chat-box model we inherited from GPT-3 days.”
“Litmus represents the maturation of AI development as a discipline — the shift from 'does it work?' to 'does it work reliably, cheaply, and measurably?' This is how software engineering grew up in the 2000s, and AI is following the same path. Tools like this will be table stakes in 18 months.”
“File attachments with automatic format conversion plus the Slack/Google API integrations mean I can finally have agents that work across my whole toolkit, not just the terminal. The one-line installer is the detail that will make this actually get adopted.”
“Brand voice consistency is one of the hardest problems in AI-assisted content creation. Litmus-style testing against creative prompts — does this output match our tone guidelines? — is something agencies and marketing teams desperately need. The model cost comparison feature makes budget conversations with clients much cleaner.”
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