audit-compliance
Compliance and performance specialist. Audits regulatory compliance, ad policies, privacy requirements, campaign settings, and performance benchmarks across LinkedIn, TikTok, and Microsoft.
$ npx -y skills add naveedharri/benai-skills --agent claude-codeShips with benai-skills. Installing the plugin gets this agent.
How it fires
How this agent gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
Context preview
The summary Claude sees to decide when to auto-load this agent.
Compliance and performance specialist. Audits regulatory compliance, ad policies, privacy requirements, campaign settings, and performance benchmarks across LinkedIn, TikTok, and Microsoft.
Expert automation skills for Claude Code, organized by department.
Repo: naveedharri/benai-skills
Other agents on benai-skills.
- audit-budget
Budget and bidding specialist. Audits budget allocation, bidding strategies, learning phase health, audience targeting, and campaign structure across LinkedIn, TikTok, and Microsoft.
Open agent - audit-creative
Creative quality specialist. Audits ad creative across LinkedIn, TikTok, and Microsoft for format diversity, fatigue signals, platform-native content, and spec compliance.
Open agent - audit-google
Google Ads audit specialist. Analyzes conversion tracking, wasted spend, account structure, keywords, Quality Score, ad assets, PMax, bidding, and settings.
Open agent - audit-meta
Meta Ads audit specialist. Analyzes Pixel/CAPI health, EMQ scores, creative diversity and fatigue, account structure, learning phase, audience targeting, and Advantage+ campaigns.
Open agent - audit-tracking
Conversion tracking specialist. Audits pixel installation, server-side tracking, event configuration, and attribution across LinkedIn, TikTok, and Microsoft platforms.
Open agent - autoresearch-eval-agent
Eval Agent for AutoResearch. Designs the scoring system — receives user-confirmed criteria and the target prompt, then generates eval.py + test_cases.json (deterministic mode) or rubric.md + test_cases.json (AI judge mode). The main agent never sees the eval artifacts in detail.
Open agent