Data
PromptBeginner5 minmarkdown
Use ML-pattern inference across all four network datasets to suggest what themes
angles
0
Explore
Find agent skills by outcome
24,072 skills indexed with the new KISS metadata standard.
Showing 24 of 24,072Categories: Data, Education, Communication, Openclaw, Coding & Debugging, Creative
Education
PromptBeginner5 minmarkdown
**Worst Creative(s):** Explain which patterns predict failure
and flag whether the failure is universal or network-localized.
0
Creative
PromptBeginner5 minmarkdown
**Promising Creative(s):** Identify early positive signals and specify which variations — pacing edits
hook recuts
0
Education
PromptBeginner5 minmarkdown
**Best Creative(s):** Explain which creative attributes correlate with strong metrics
and whether those attributes hold across all networks or are network-specific.
0
Creative
PromptBeginner5 minmarkdown
- Rate divergence risk: High / Medium / Low — i.e.
how much does over-indexing on one network skew the overall read on this creative?
0
Education
PromptBeginner5 minmarkdown
- Highest CPI: Explain which signals
specific to this network
0
Data
PromptBeginner5 minmarkdown
One concise pattern extracted strictly from this network's data — e.g.
On ALN
0
Education
PromptBeginner5 minmarkdown
- High Spend / Poor Results: Explain the inefficiency pattern and the likely network-specific ML reason (e.g.
ALN AXON fallback behavior
0
Education
PromptBeginner5 minmarkdown
- Top Creative by Spend: Explain why this network's algo is favoring it
and whether scaling is amplifying or compressing efficiency.
0
Creative
PromptBeginner5 minmarkdown
- Top Creative by IPM (or CTR × CVR for Google): Interpret why this creative wins on this specific network. Reference network auction behavior
format fit
0
Creative
PromptBeginner5 minmarkdown
- Identify cross-network divergence: creatives that overperform on one network and underperform on another
and reason about why
0
Creative
PromptBeginner5 minmarkdown
- 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 minmarkdown
- Compare creatives directly across all key metrics
within and across networks
0
Data
PromptBeginner5 minmarkdown
- Interpret the data using pattern-recognition logic
segmented by network
0
Data
PromptBeginner5 minmarkdown
Analyse the provided UA performance data (text
table
0
Education
PromptBeginner5 minmarkdown
- Google UAC (ACi): Machine-learning-first
multi-format ingestion (YouTube
0
Creative
PromptBeginner5 minmarkdown
- 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
Education
PromptBeginner5 minmarkdown
- AppLovin (ALN): Operates on a closed DSP with a proprietary ML bidding stack (AXON). Heavy on playable and interactive end-cards. IPM is the primary optimization signal; CTR is secondary. Algo learns fast but punishes creative fatigue aggressively. Look for: steep IPM decay curves
install clustering by creative batch
0
Creative
PromptBeginner5 minmarkdown
Before scoring any creative
ground your reasoning in each network's structural behavior:
0
Data
PromptBeginner5 minmarkdown
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 minmarkdown
User Acquisition Data Analysis
Persona
0
Coding & Debugging
PromptBeginner5 minmarkdown
(Example: Software Developer – ₹50
000/month or $800/month)
0
Coding & Debugging
PromptBeginner5 minmarkdown
Provide a real flow diagram based on the given feature and code
showing:
0
Data
PromptBeginner5 minmarkdown
- Failure scenarios (invalid input
missing data
0