Local, LLM-free memory for AI agents. A single offline Rust binary — deterministic and auditable — that learns from u...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Still active enough to matter. Good candidate for a fast stack test instead of a long evaluation loop.
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 85/100. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Universal
Model
Claude
Fastest way to find out if shodh-memory 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/varun29ankuS/shodh-memory ~/.claude/agents/shodh-memoryRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/shodh-memoryNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ agents/ │ └─ shodh-memory/ ← installs here └─ settings.json
Local, LLM-free memory for AI agents. A single offline Rust binary — deterministic and auditable — that learns from use, forgets the irrelevant, and strengthens what matters. No cloud, no API keys.
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: July 15, 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.