Afrexai Mcp Engineering
MCP Engineering — Complete Model Context Protocol System
Review ads and campaign setup for policy compliance on Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install danyangliu-sandwichlab/ad-compliance-reviewerExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Detect compliance risks and provide concrete compliant rewrites before publishing.
Use this skill when the user asks to:
Typical trigger keywords:
Required:
Optional:
Return an execution-ready result with:
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# Ads Compliance Review ## Purpose Detect compliance risks and provide concrete compliant rewrites before publishing. ## When To Trigger Use this skill when the user asks to: - run ads or execute advertising campaigns with clear operational next steps - grow revenue or profit, improve roas, reduce cpa, or optimize budget and bidding - analyze market, traffic, conversion funnel, and campaign performance signals - apply this specific capability: policy screening, violation detection, compliant rewrite Typical trigger keywords: - ads, advertising, campaign, growth, strategy - revenue, profit, roi, roas, cpa - budget, bidding, traffic, conversion, funnel - meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp ## Input Contract Required: - business_goal: primary objective (sales, leads, traffic, awareness, retention) - scope: campaign range, market, timeline, and platform scope - context: URL, account context, historical performance, or request text Optional: - kpi_targets: target cpa, roas, revenue, roi, ltv, cvr - constraints: budget, policy, brand rules, timeline, resource limits - platform_preference: preferred channels and priority - baseline_metrics: existing benchmark metrics ## Output Contract Return an execution-ready result with: 1. Intent Summary (goal, KPI, scope) 2. Findings (key observations and assumptions) 3. Action Plan (prioritized next steps) 4. Risks and Guardrails (what can break and what to monitor) 5. Handoff Payload (structured fields for downstream skills) ## Workflow 1. Normalize request and confirm objective. 2. Validate available inputs and list missing critical data. 3. Analyze according to this skill focus: policy screening, violation detection, compliant rewrite. 4. Generate prioritized actions tied to KPI impact. 5. Add platform-specific notes and constraints. 6. Emit a compact handoff payload for execution. ## Decision Rules - If KPI is missing, infer likely primary KPI from goal and mark assumption explicitly. - If d...
MCP Engineering — Complete Model Context Protocol System
Incident Postmortem Generator
Complete SEO content creation system for AI agents. Research keywords, analyze competitors, write optimized articles, and track rankings — all through natural conversation. No APIs required.
Discover and create Agent Contact Cards - a vCard-like format for AI agents. Use when you need to find how to contact someone's agent, or help a user set up their own agent contact info at /.well-known/agent-ca...