Build an AI agent harness in Rust, from a minimal loop to tools, subagents, memory, teams, worktrees, MCP, and type...
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 57/100. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Claude Code
Model
Claude
Fastest way to find out if learn-claude-code-rs 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/wulawulu/learn-claude-code-rs ~/.claude/agents/learn-claude-code-rsRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/learn-claude-code-rsNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ agents/ │ └─ learn-claude-code-rs/ ← installs here └─ settings.json
Build an AI agent harness in Rust, from a minimal loop to tools, subagents, memory, teams, worktrees, MCP, and typed tool routing.
Source: GitHub repository
Source check: August 29, 2026
Upstream commit: August 29, 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.