by asklokesh · Codex Skill · ★ 1.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Featured in: Open-Source Vibe Coding Tools
bun install -g loki-mode
git clone https://github.com/asklokesh/loki-mode.git && cd loki-modeTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
One of 14 tools we ran end to end on the same task for our Open-Source Vibe Coding Tools page (2026-10-27).
Result: one-sentence page: 4 of 4 checks · family ledger: 8 of 8 · opens by double-click · stopped to ask 2 times · 10.8 + 11.0 min, 1.4× the usage of no tool
| Stars | 1,120 |
| Forks | 206 |
| Language | Shell |
| Category | Codex Skill |
| Quality Score | 66/100 |
| Open Issues | 189 |
| Last Updated | 2026-11-06 |
| Created | 2025-12-26 |
| Platforms | claude-code, cli, codex |
| Est. Tokens | ~15k |
Loki Mode Build the future, faster. Describe what you want. Get production-ready code. Website Purple Lab Web UI How it works: Drop a spec -- a PRD, GitHub issue, OpenAPI/JSON/YAML, or one-line brief. Loki Mode classifies complexity (), assembles an agent team from 41 specialized types across 8 swarms, and runs autonomous RARV cycles (Reason - Act - Reflect - Verify, see ) with 11 quality gates...
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: