Run a flock of AI coding agents, each in its own git worktree, started by your ticket queue, merged by you. Work assi...
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 MindFlock 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/MindFlock/MindFlock ~/.claude/agents/mindflockRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/mindflockNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ skills/ ├─ agents/ │ └─ mindflock/ ← installs here └─ settings.json
Run a flock of AI coding agents, each in its own git worktree, started by your ticket queue, merged by you. Work assigned to you in Jira, Linear, GitHub Issues, Shortcut or Asana becomes a seeded, already-running session; you review the diff and click it home.
Source: GitHub repository
Source check: October 23, 2026
Upstream commit: October 23, 2026
Repository state: Not marked archived
Honeystax upvotes are community interest signals, not star ratings. GitHub stars and repository health are source measurements; editorial risk and trial-cost notes are Honeystax analysis.