Creative
PromptBeginner5 minmarkdownQuality: 28
- Rate divergence risk: High / Medium / Low — i.e.
how much does over-indexing on one network skew the overall read on this creative?
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Find agent skills by outcome
138,404 skills indexed with the new KISS metadata standard.
Showing 24 of 138,404Categories: General, Creative, Coding & Debugging, Cursor-rules, Data
Data
PromptBeginner5 minmarkdownQuality: 24
One concise pattern extracted strictly from this network's data — e.g.
On ALN
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General
PromptBeginner5 minmarkdownQuality: 24
- State the performance delta (e.g.
top 1 on ALN
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General
PromptBeginner5 minmarkdownQuality: 28
- Lowest IPM (or weakest CTR × CVR): Identify root-cause patterns through the lens of this network's audience and format behavior (e.g.
weak hook on a skip-heavy rewarded placement
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Creative
PromptBeginner5 minmarkdownQuality: 28
- Top Creative by IPM (or CTR × CVR for Google): Interpret why this creative wins on this specific network. Reference network auction behavior
format fit
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General
PromptBeginner5 minmarkdownQuality: 24
Repeat the following block for each of the four networks: AppLovin
Mintegral
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General
PromptBeginner5 minmarkdownQuality: 24
- Flag anomalies with ML-style reasoning (outliers
variance spikes
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General
PromptBeginner5 minmarkdownQuality: 28
Your role is not to describe numbers
but to act as a performance-prediction model using structured
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Creative
PromptBeginner5 minmarkdownQuality: 28
- Identify cross-network divergence: creatives that overperform on one network and underperform on another
and reason about why
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Creative
PromptBeginner5 minmarkdownQuality: 24
- Compare creatives directly across all key metrics
within and across networks
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Creative
PromptBeginner5 minmarkdownQuality: 28
- Identify predictive signals per network (e.g.
which creative traits show scaling potential vs. burnout risk on ALN; which show stability signals on Mintegral)
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General
PromptBeginner5 minmarkdownQuality: 24
- Detect hidden drivers of performance (e.g.
early CTR → later IPM quality drop
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Data
PromptBeginner5 minmarkdownQuality: 24
- Interpret the data using pattern-recognition logic
segmented by network
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Data
PromptBeginner5 minmarkdownQuality: 24
Analyse the provided UA performance data (text
table
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Creative
PromptBeginner5 minmarkdownQuality: 28
- Mintegral: SDK-based
rewarded and interstitial heavy. Audience quality can vary significantly by geo and supply path. CPI tends to be volatile early; stabilizes at scale. Creative fatigue patterns differ from ALN — longer...
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Data
PromptBeginner5 minmarkdownQuality: 28
You think like a UA analyst and like a model trained to detect patterns in noisy data. You understand that each network has a distinct auction mechanic
creative format bias
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Creative
PromptBeginner5 minmarkdownQuality: 24
Before scoring any creative
ground your reasoning in each network's structural behavior:
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General
PromptBeginner5 minmarkdownQuality: 24
You identify correlations
leading indicators
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General
PromptBeginner5 minmarkdownQuality: 28
- Success metric (Example: ₹10
000 earned / 10 users gained)
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Data
PromptBeginner5 minmarkdownQuality: 24
User Acquisition Data Analysis
Persona
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General
PromptBeginner5 minmarkdownQuality: 28
(Example: ₹2
00
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General
PromptBeginner5 minmarkdownQuality: 24
- Why it fits based on $${skills}
$${experience}
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General
PromptBeginner5 minmarkdownQuality: 28
(Example: Flutter
Android
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General
PromptBeginner5 minmarkdownQuality: 28
(Example: ₹30
000/month)
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