LLM Agent Skill // v1.0 // Community Edition
An LLM Agent Skill that embeds expert YARA knowledge into your AI assistant.
Get professional rule reviews, performance optimization, and quality checks.
Paste a rule. Get instant feedback on naming, atoms, condition logic, metadata.
"Review this YARA rule and suggest improvements"
Before deploying. All 60+ quality checks applied automatically.
"Assess the quality of this rule I found online"
Slow scans? Identifies unanchored regex, short atoms, expensive calculations.
"This rule causes performance issues, why?"
Logic errors, performance, style via embedded yaraQA
Atom selection, regex anchoring, condition ordering
MAL/HKTL/SUSP/EXPL naming conventions
$x*, $s*, $a*, $fp* string naming pattern
63 total checks and guidelines from embedded knowledge:
LOGIC_ERRORS (11)
PERFORMANCE (16)
STYLE & CONVENTION (30)
FORMATTING (6)
User input detected. Analyzing...
// CATASTROPHIC PERFORMANCE
rule Big_Numbers0 {
strings:
$c0 = /[0-9a-fA-F]{20}/ fullword
condition:
$c0
}
// LOGIC ERROR
rule HKTL_Mimikatz {
strings:
$x1 = "\LsaDump.pdb" fullword
condition:
$x1
}
Add to your LLM agent's context:
OPTION_1: Clone and Copy (Recommended)
# Clone the repository
git clone https://github.com/YARAHQ/yara-rule-skill.git
# Copy to your agent's skills folder
cp -r yara-rule-skill ~/.openclaw/skills/
OPTION_2: Package as .skill File
# Clone the repository
git clone https://github.com/YARAHQ/yara-rule-skill.git
cd yara-rule-skill
# Package the skill
python3 scripts/package_skill.py .
# Install the packaged skill
cp yara-rule-skill.skill ~/.openclaw/skills/
Ready. Start conversation about YARA rules.