---
name: Paid Media Monitor
slug: paid-media-monitor
category: Data
description: Paid Media Monitor monitors paid-ad account pacing, delivery, performance, creative fatigue, tracking, policy, and data quality across supported platforms. Use it for daily or weekly checks, anomaly review, budget pacing, post-launch verification, or campaign monitoring.
github: "https://github.com/AgriciDaniel/claude-ads/tree/main/skills/ads-monitor"
language: Python
stars: 8064
forks: 1200
install: "npx degit https://github.com/AgriciDaniel/claude-ads/tree/main/skills/ads-monitor ~/.claude/skills/ads-monitor"
installs_to: ~/.claude/skills/ads-monitor
source_path: skills/ads-monitor/SKILL.md
collection_size: 25
category_size: 668
collection_url: "https://dirskills.com/collections/AgriciDaniel/claude-ads"
added: 2026-08-15T06:51:13.717Z
last_synced: 2026-08-15T06:51:13.717Z
canonical_url: "https://dirskills.com/skills/paid-media-monitor"
---

# Paid Media Monitor

Paid Media Monitor monitors paid-ad account pacing, delivery, performance, creative fatigue, tracking, policy, and data quality across supported platforms. Use it for daily or weekly checks, anomaly review, budget pacing, post-launch verification, or campaign monitoring.

**Install:**

```bash
npx degit https://github.com/AgriciDaniel/claude-ads/tree/main/skills/ads-monitor ~/.claude/skills/ads-monitor
```

## README

# Paid Media Monitoring

1. Load two or more normalized snapshots with compatible account, timezone,
   currency, metric, and attribution definitions.
2. Validate data freshness and finalization windows before comparing periods.
3. Separate expected learning, seasonality, reporting latency, and planned changes
   from unexplained anomalies.
4. Evaluate pacing, delivery, conversion quality, unit economics, creative fatigue,
   tracking health, policy status, and changed account objects.
5. Return observations, confidence, likely causes, required investigation, and
   decision thresholds. Do not mutate the account.
6. Persist a versioned monitoring bundle and link detected failures to regression
   or follow-up tasks.

Do not alert on percentage changes with trivial denominators or incomparable
windows. State when evidence cannot distinguish noise from a material change.