ads-optimization
Skill1 starsChanged 22 days agoMITView on GitHub
Structured optimization engine for Meta and Google Ads - multi-window analysis (today, 3, 7, 14, 30 days), conversion lag, learning status, wasted spend, search terms, creative fatigue, budget constraints, attribution quality, and confidence-graded recommendations (HIGH / MODERATE / EXPERIMENT). Use for "optimize", "what wasted the most spend", "what should we change", "weekly optimization".
1 other project uses a version of this.
Adopted by
Most recently taken up by
- aronhy/marketing-skill-hubtheir own version, first seen Nov 8, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- aronhy/marketing-skill-hub★ 186same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository17 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- llms.txtllms.txt
- ads-auditSkill
- ads-budgetingSkill
- ads-client-onboardingSkill
- ads-communitySkill
- ads-competitor-researchSkill
- ads-coreSkill
- ads-creative-analysisSkill
- ads-landing-pageSkill
- ads-portfolioSkill
- ads-reportingSkill
- ads-strategySkill
- ads-trackingSkill
- google-adsSkill
- meta-adsSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 45
Use adsgm quality to grade evidence when in doubt.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Ads optimization
Workflow: workflows/optimization-cycle.md.
Windows and what each is for
| Window | Use | Never use for |
| Today | anomalies, delivery breaks, runaway spend | performance verdicts |
| Last 3 days | early warning (tracking drop, disapprovals, CPM spike) | pausing or scaling |
| Last 7 days | primary read for active entities (full week cycle) | low-volume accounts' CPA |
| Last 14 days | fatigue trends, small accounts | - |
| Last 30 days | search terms, structure, small-volume verdicts | detecting recent change |
Exclude the last N days from CPA verdicts where N ≈ conversion lag (Google lag buckets; CRM lead-to-qualified time).
Wasted spend ("Show me what wasted the most spend this month")
Rank entities by spend with no or poor results, but only call it waste when:
- Certain waste: irrelevant search terms, spend outside service area, broken URLs/disapproved-then-reapproved ads, duplicate campaigns bidding on the same queries, spend on a tracking-broken period with no leads in CRM either.
- Probable waste: ads/ad sets/keywords with spend ≥ 2-3x target CPA and zero conversions, out of learning, tracking verified (HEURISTIC).
- Not waste: learning ad sets, breakdown segments with higher averages (Meta breakdown effect), upper-funnel campaigns judged on last-click.
Report: top 5-10 by $ with class (certain/probable), evidence, fix, confidence, approval needed.
Recommendation format
[HIGH CONFIDENCE] Add 7 phrase negatives (DIY/jobs) to Kitchen Search
Data: 30d, $166 on 23 terms, 0 conv; no converter blocked
Expected: -$40/week waste
Action: adsgm google plan (add_negative_keywords) -> approval: yes (client in approval mode)Confidence:
- HIGH - large sample, clean tracking, mechanism clear (e.g., irrelevant queries, out-of-area spend).
- MODERATE - directional data; act in small reversible steps, set a read date.
- EXPERIMENT - hypothesis; design a test with one variable (workflows/creative-testing.md).
Use adsgm quality to grade evidence when in doubt. Do not overreact to tiny samples; "no action - insufficient data until <date>" is a valid recommendation.
Order of operations per cycle
- Tracking health and anomalies. 2. Certain waste. 3. Budget constraints on winners. 4. Fatigue/creative. 5. Structure. 6. Tests. Max 3-5 changes per cycle per platform; log each with
adsgm planso cooldowns apply.
Does it work?
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