Lightweight, local-first Python DAG workflow compiler and execution engine with human-in-the-loop checkpoints for CLI...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Fresh repo activity plus visible builder pull. This is the kind of tool people test before it turns obvious.
Copy the install, test the workflow, then decide if it earns a permanent slot.
Reasonable to try, but it will take more than a quick skim to get real signal.
GitHub health unknown. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Universal
Model
Multiple
Fastest way to find out if lightflow belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
git clone https://github.com/google/lightflow ~/.claude/agents/lightflowRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/lightflowNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ skills/ ├─ agents/ │ └─ lightflow/ ← installs here └─ settings.json
Lightweight, local-first Python DAG workflow compiler and execution engine with human-in-the-loop checkpoints for CLI and AI-agent workflows.
Source: GitHub repository
Source check: October 17, 2026
Upstream commit: October 16, 2026
Repository state: Not marked archived
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