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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Find agent skills by outcome
13,989 skills indexed with the new KISS metadata standard.
Showing 24 of 13,989Categories: Data, Cursor-rules, Creative
Data
PromptBeginner5 minmarkdownQuality: 24
User Acquisition Data Analysis
Persona
1
Data
PromptBeginner5 minmarkdownQuality: 24
- Failure scenarios (invalid input
missing data
1
Creative
PromptBeginner5 minmarkdownQuality: 26
Vibe Coding with Commands and Skills
Act as a Vibe Coding Expert with built-in /commands and skills. You are proficient in leveraging AI models for coding and UX/UI design tasks, using a variety of tools and frameworks to streamline the...
3
Data
PromptBeginner5 minmarkdownQuality: 26
- Flag when data volume per network is insufficient to draw high-confidence conclusions
and adjust confidence language accordingly.,FALSE,TEXT,[email protected]
1
Creative
PromptBeginner5 minmarkdownQuality: 26
- Provide specific
technically grounded creative recommendations that account for format constraints per network.
0
Creative
PromptBeginner5 minmarkdownQuality: 26
- Always analyze creatives at two levels: within each network
and across all four networks simultaneously.
0
Data
PromptBeginner5 minmarkdownQuality: 22
- Never flatten cross-network data into a single average — divergence is signal
not noise.
1
Data
PromptBeginner5 minmarkdownQuality: 26
- Predictive creative mechanics the data hints at (e.g.
a mechanic that lifts CTR on Google but hasn't been tested on ALN's playable format)
0
Data
PromptBeginner5 minmarkdownQuality: 22
Use ML-pattern inference across all four network datasets to suggest what themes
angles
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Creative
PromptBeginner5 minmarkdownQuality: 26
**Promising Creative(s):** Identify early positive signals and specify which variations — pacing edits
hook recuts
0
Creative
PromptBeginner5 minmarkdownQuality: 26
- 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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Data
PromptBeginner5 minmarkdownQuality: 22
One concise pattern extracted strictly from this network's data — e.g.
On ALN
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Creative
PromptBeginner5 minmarkdownQuality: 26
- 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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Creative
PromptBeginner5 minmarkdownQuality: 26
- 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: 26
- Identify predictive signals per network (e.g.
which creative traits show scaling potential vs. burnout risk on ALN; which show stability signals on Mintegral)
0
Creative
PromptBeginner5 minmarkdownQuality: 22
- Compare creatives directly across all key metrics
within and across networks
0
Data
PromptBeginner5 minmarkdownQuality: 22
- Interpret the data using pattern-recognition logic
segmented by network
0
Data
PromptBeginner5 minmarkdownQuality: 22
Analyse the provided UA performance data (text
table
0
Creative
PromptBeginner5 minmarkdownQuality: 26
- 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...
0
Creative
PromptBeginner5 minmarkdownQuality: 22
Before scoring any creative
ground your reasoning in each network's structural behavior:
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Data
PromptBeginner5 minmarkdownQuality: 26
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
0
Data
PromptBeginner5 minmarkdownQuality: 22
User Acquisition Data Analysis
Persona
1
Data
PromptBeginner5 minmarkdownQuality: 22
- Failure scenarios (invalid input
missing data
0