naveedharri/benai-skills
13 subagents
Subagent
audit-budgetBudget and bidding specialist. Audits budget allocation, bidding strategies, learning phase health, audience targeting, and campaign structure across LinkedIn, TikTok, and Microsoft.audit-complianceCompliance and performance specialist. Audits regulatory compliance, ad policies, privacy requirements, campaign settings, and performance benchmarks across LinkedIn, TikTok, and Microsoft.audit-creativeCreative quality specialist. Audits ad creative across LinkedIn, TikTok, and Microsoft for format diversity, fatigue signals, platform-native content, and spec compliance.audit-googleGoogle Ads audit specialist. Analyzes conversion tracking, wasted spend, account structure, keywords, Quality Score, ad assets, PMax, bidding, and settings.audit-metaMeta Ads audit specialist. Analyzes Pixel/CAPI health, EMQ scores, creative diversity and fatigue, account structure, learning phase, audience targeting, and Advantage+ campaigns.audit-trackingConversion tracking specialist. Audits pixel installation, server-side tracking, event configuration, and attribution across LinkedIn, TikTok, and Microsoft platforms.autoresearch-eval-agentEval 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_caseautoresearch-judgeJudge Agent for AutoResearch. Scores outputs against a locked rubric for quality assessment. Operates with fresh context every iteration — knows NOTHING about iteration count, prompt changes, or optimautoresearch-test-runnerTest Runner Agent for AutoResearch. Executes the prompt/skill for real using all available tools (web search, APIs, file access). Operates with fresh context — knows NOTHING about eval criteria, assericebreaker-writerUse this sub-agent to write hyper-personalized cold email icebreakers for a batch of B2B leads. Spawn one instance per batch of 5 leads. Each instance receives full lead data (including intelligence alead-qualifierUse this sub-agent to qualify a batch of B2B leads against an ICP definition. Spawn one instance per batch of 10 leads. Each instance receives a JSON batch of leads, the full ICP definition, and qualilead-researcherUse this sub-agent to conduct deep web research on a batch of B2B leads. Spawn one instance per batch of 5 leads. Each instance researches each lead's company, role, and public presence, then produceslinkedin-scraperUse this sub-agent to orchestrate LinkedIn scraping for all qualified leads via Apify actors. Only ONE instance should be spawned per pipeline run. It handles triggering both Apify actors (posts + pro