No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ash-project · Agent Tool · ★ 223
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is usage_rules safe to install? View the security audit →
SPDX-License-Identifier: MIT -- UsageRules UsageRules is a config-driven dev tool for Elixir projects that manages your AGENTS.md file and agent skills from dependencies. It: Gathers and consolidates files (or files from a directory) from your dependencies into an (or any file) Generates agent skills ( files) from dependency usage rules Provides built-in usage rules for Elixir and OTP Includes a powerful documentation search task via Quickstart Installation If you have igniter installed: Or add
| Stars | 223 |
| Forks | 40 |
| Language | Elixir |
| Category | Agent Tool |
| Quality Score | 68.688848598926/100 |
| Open Issues | 2 |
| Last Updated | 2026-10-02 |
| Created | 2025-05-23 |
| Est. Tokens | ~19k |
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usage_rules is A tool for synchronizing LLM rules files with your dependencies.. It is categorized as a Agent Tool with 223 GitHub stars.
usage_rules is primarily written in Elixir.
You can find installation instructions and usage details in the usage_rules GitHub repository at github.com/ash-project/usage_rules. The project has 223 stars and 40 forks, indicating an active community.
The top alternatives to usage_rules on Agent Skills Hub include awesome-android-agent-skills, synalinks-skills, agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: