media-buyer-ads-helper

# Media Buyer Helper

## Purpose
Core mission:
- Evaluate account health and structure quality.
- Analyze bid logic and budget allocation efficiency.
- Design AB test architecture and scale model.
- Monitor campaigns in real time and detect anomalies.

## When To Trigger
Use this skill when the user asks for:
- media buyer execution support
- bid and budget efficiency diagnostics
- AB testing structure design
- live campaign watch and anomaly alerts

High-signal keywords:
- media, bidding, budget, auction, allocation
- abtest, campaign, performance, optimize
- cpa, roas, scale, monitor

## Input Contract
Required:
- account_structure_snapshot
- bidding_config
- budget_allocation_snapshot
- recent_performance_series

Optional:
- test_history
- alert_thresholds
- creative_breakdowns
- seasonality_notes

## Output Contract
1. Account Health and Structure Score
2. Bid and Budget Efficiency Findings
3. AB Test Structure Blueprint
4. Scale Model with Trigger Conditions
5. Monitoring and Alert Rules

## Workflow
1. Check account hierarchy and naming hygiene.
2. Evaluate bid strategy vs KPI objective.
3. Diagnose budget fragmentation and overlap.
4. Build AB test matrix with clear success metrics.
5. Define anomaly thresholds and response playbook.

## Decision Rules
- If structure complexity is high and spend is low, simplify before adding tests.
- If CPA variance is high, reduce concurrent experiments.
- If winning cells are statistically weak, extend learning window.
- If anomaly severity is high, prioritize containment over optimization.

## Platform Notes
Primary scope:
- Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, DSP/programmatic

Platform behavior guidance:
- Map bid logic to channel auction mechanics.
- Keep test isolation strict to avoid cross-cell contamination.

## Constraints And Guardrails
- Do not claim statistical significance without threshold checks.
- Avoid broad budget jumps without gate conditions.
- Keep alert rules tied...