skills/llm-gate/SKILL.md
LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.
npx skillsauth add rohitg00/pro-workflow llm-gateInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use Claude Code's type: "prompt" hooks to create intelligent quality gates that use AI to verify operations.
Use when:
Claude Code supports hooks with type: "prompt" that run a small LLM (Haiku by default) to verify conditions:
{
"PreToolUse": [{
"matcher": "Bash",
"hooks": [{
"type": "prompt",
"if": "Bash(git commit*)",
"prompt": "Check if this git commit follows conventional commit format (<type>(<scope>): <summary>). The commit command is: $ARGUMENTS. Return {\"ok\": true} if valid, {\"ok\": false, \"reason\": \"...\"} if not.",
"model": "haiku",
"timeout": 15
}]
}]
}
The hook:
$ARGUMENTS with the JSON hook input{"ok": true} or {"ok": false, "reason": "..."}{
"type": "prompt",
"if": "Bash(git commit*)",
"prompt": "Verify this git commit follows conventional commits: type(scope): summary. Types: feat,fix,refactor,test,docs,chore,perf,ci. Summary under 72 chars. Input: $ARGUMENTS",
"model": "haiku"
}
{
"type": "prompt",
"if": "Bash(rm *)",
"prompt": "Check if this rm command is safe. Flag if it uses -rf on important directories (src/, node_modules/, .git/). Input: $ARGUMENTS",
"model": "haiku"
}
{
"type": "prompt",
"matcher": "Write",
"prompt": "Check if this file write contains hardcoded API keys, secrets, passwords, or tokens. Input: $ARGUMENTS. Return ok:false if secrets found.",
"model": "haiku"
}
For complex verification, use type: "agent" (runs a full agent):
{
"type": "agent",
"if": "Bash(git push*)",
"prompt": "Review all staged changes for security issues before pushing. Check for: hardcoded secrets, SQL injection, XSS vulnerabilities, exposed internal URLs.",
"model": "haiku",
"timeout": 60
}
if condition to avoid running on every tool calldevops
SkillOpt-flavored offline training loop for any SKILL.md. Treats accumulated learn-rule corrections as training trajectories, proposes bounded patches via an optimizer LLM, gates each candidate against a held-out validation set built from the user's own past corrections, and ships only candidates that demonstrably improve the score. Inspired by Microsoft SkillOpt's ReflACT pipeline (rollout → reflect → aggregate → select → update → evaluate) adapted to pro-workflow's SQLite store. Use when a skill has accumulated 8+ learn-rule rows and the user wants the skill itself to get better, not just longer.
tools
Prevent destructive operations using Claude Code hooks. Three modes — cautious (warn on dangerous commands), lockdown (restrict edits to one directory), and clear (remove restrictions). Uses PreToolUse matchers for Bash, Edit, and Write.
development
Complete AI coding workflow system. Orchestration patterns, 18 hook events, 5 agents, cross-agent support, reference guides, and searchable learnings. Works with Claude Code, Cursor, and 32+ agents.
data-ai
Analyze permission denial patterns and generate optimized alwaysAllow and alwaysDeny rules. Use when permission prompts are slowing you down or after sessions with many denials.