LLM-native static vulnerability detection. An LLM reads your source like a human auditor, point it at any local f...
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 100/100. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Multiple
Model
Claude
Fastest way to find out if argo 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/gigioneggiando/argo ~/.claude/agents/argoRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/argoNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ agents/ │ └─ argo/ ← installs here └─ settings.json
LLM-native static vulnerability detection. An LLM reads your source like a human auditor, point it at any local folder or repo and get a reviewable vuln report. Auto-enriched prompts, adversarial validation, opt-in fix-verify. Runs on Claude Code / Codex / local OSS. Bug-bounty triage is one mode. Detection-only, read-only.
Source: GitHub repository
Source check: August 14, 2026
Upstream commit: August 14, 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.