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Ads monitor

Skill AgriciDaniel/claude-ads/skills/ads-monitor

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

Install
npx -y skills add AgriciDaniel/claude-ads --skill ads-monitor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.1 KB, 165 tokens by cl100k_base, as published. Nobody here has run it

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.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most marketing audience skills give in 165 tokens

Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07

  • Apply Poppins font to headingsin 41 of 690, across 6 files
  • Apply Lora font to body textin 41 of 690, across 6 files
  • Use Arial fallback for headingsin 39 of 690, across 4 files
  • Use Georgia fallback for body textin 39 of 690, across 4 files
  • Maintain text hierarchy and formattingin 39 of 690, across 4 files
  • Use accent colors for non-text shapesin 38 of 690, across 3 files
  • Use RGB values for precise color matchingin 38 of 690, across 3 files
  • Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
  • Read product marketing context file before asking questions, starting, or auditingin 35 of 690, across 23 files
  • Use active voice instead of passive voicein 26 of 690, across 10 files
  • Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
  • Prioritize clarity over clevernessin 22 of 690, across 8 files

Said here and by no other author read

  • load normalized snapshots
  • separate expected changes from unexplained anomalies
  • evaluate campaign delivery and health metrics
  • return observations and confidence levels
  • persist a versioned monitoring bundle

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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