Is LoopCraft free to use?

Yes. LoopCraft offers a free tier for designing and exporting AI agent loop patterns. A Pro plan is available for advanced features.

What is Loop Engineering?

Loop Engineering is designing the control flow for AI agents: how they plan actions, observe results, and iterate. LoopCraft includes 11 pre-built patterns based on research from Anthropic, OpenAI, and others — including ReAct, Plan-Execute, Evaluator-Optimizer, Multi-Agent, and more. Design loops visually and export to LangGraph, OpenAI Agents SDK, AutoGen, or CrewAI.

Which frameworks can I export to?

LoopCraft exports to LangGraph (Python), OpenAI Agents SDK (TypeScript), AutoGen (Python), and CrewAI (Python). Each export produces working code you can run directly in your project.

Do I need to write code?

No. LoopCraft is a visual builder — you design loop patterns with a drag-and-drop interface and configure nodes without writing code. Code export to LangGraph, OpenAI SDK, AutoGen, and CrewAI is generated automatically and is optional.

What loop patterns are supported?

LoopCraft supports 11 agent loop patterns: ReAct (think-act-observe cycle), Prompt Chaining (sequential steps with quality gates), Routing (classify and direct inputs), Parallel Sectioning (independent subtasks in parallel), Parallel Voting (multiple runs for confidence), Orchestrator-Workers (dynamic task decomposition), Evaluator-Optimizer (generate-evaluate loop), Plan-and-Execute (plan then execute with replanning), ReWOO (variable passing between tasks), LLM Compiler (DAG-based parallel execution, 3.6x speedup), and Multi-Agent (collaborative agents with roles).

Token Budget Planning for Agent Loops: A Practical Framework

Estimate token cost per node, multiply by expected retry count, add a 30% buffer for edge cases, and set a hard circuit-breaker limit at the loop level. Review the estimate before export, not after the first production bill. The reason this order matters is that token spend in an agent loop is multiplicative, not additive. A node that looks cheap in isolation can dominate the bill once retries, branching, and accumulated context enter the picture. Planning the budget at design time, while the graph is still editable, is dramatically cheaper than discovering the overrun from a usage dashboard at the end of the month. Most budget surprises trace back to a few recurring patterns: the silent retry that resends the full accumulated context on every failure, context snowball where each node re-reads a growing shared state, and the unbounded planner that expands its own scratchpad without a cap. Each is invisible on a happy-path diagram, which is why a per-node estimate that ignores retry counts consistently understates real spend. A practical four-step framework: estimate each node's steady-state cost (system prompt plus typical input plus expected output, priced against your configured model), multiply by expected execution count including retries, add roughly 30% buffer, then wire the per-loop total into a circuit breaker that aborts cleanly when spend crosses the threshold. As of 2026-07-25, LoopCraft export previews show a per-node token cost estimate beside the timeout and retry labels introduced on 2026-07-20, so you can read the realistic retry-adjusted cost without leaving the canvas. Allocate budget unevenly on purpose. Reserve about half for the highest-cost reasoning node, split a third across tool interactions (truncating large tool outputs before they re-enter context), and hold the rest plus your buffer as headroom. If a single node shows more than about 60% of total cost in the export preview, split it, cache it, or move it to a cheaper model tier. Enforce the estimate at runtime with a loop-level circuit breaker and per-node logging so you can compare actual spend against the design-time number. LoopCraft keeps the loop in a visual editor, so you can iterate, re-check the per-node estimates, and re-export to LangGraph, AutoGen, CrewAI, or the OpenAI Agents SDK without rewriting code. Export targets and loop behavior are unchanged; the new part is cost visibility before you commit. Feedback: sapsap@qq.com. LoopCraft: https://getloopcraft.com