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Find agent skills by outcome

132,172 skills indexed with the new KISS metadata standard.

Showing 24 of 132,172Categories: Creative, Data, General, Communication, Education, Coding & Debugging
General
PromptBeginner5 minmarkdown

Repeat the following block for each of the four networks: AppLovin

Mintegral

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Creative
PromptBeginner5 minmarkdown

- Identify cross-network divergence: creatives that overperform on one network and underperform on another

and reason about why

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General
PromptBeginner5 minmarkdown

Your role is not to describe numbers

but to act as a performance-prediction model using structured

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General
PromptBeginner5 minmarkdown

- Flag anomalies with ML-style reasoning (outliers

variance spikes

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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)

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General
PromptBeginner5 minmarkdown

- Detect hidden drivers of performance (e.g.

early CTR → later IPM quality drop

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Creative
PromptBeginner5 minmarkdown

- Compare creatives directly across all key metrics

within and across networks

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Data
PromptBeginner5 minmarkdown

- Interpret the data using pattern-recognition logic

segmented by network

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Data
PromptBeginner5 minmarkdown

Analyse the provided UA performance data (text

table

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Education
PromptBeginner5 minmarkdown

- Google UAC (ACi): Machine-learning-first

multi-format ingestion (YouTube

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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...

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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

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Creative
PromptBeginner5 minmarkdown

Before scoring any creative

ground your reasoning in each network's structural behavior:

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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

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General
PromptBeginner5 minmarkdown

You identify correlations

leading indicators

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General
PromptBeginner5 minmarkdown

- Success metric (Example: ₹10

000 earned / 10 users gained)

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Data
PromptBeginner5 minmarkdown

User Acquisition Data Analysis

Persona

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General
PromptBeginner5 minmarkdown

(Example: ₹2

00

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General
PromptBeginner5 minmarkdown

- Why it fits based on $${skills}

$${experience}

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General
PromptBeginner5 minmarkdown

(Example: Flutter

Android

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General
PromptBeginner5 minmarkdown

(Example: ₹30

000/month)

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General
PromptBeginner5 minmarkdown

(Example: ₹5

000/month freelancing OR None)

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Coding & Debugging
PromptBeginner5 minmarkdown

(Example: Software Developer – ₹50

000/month or $800/month)

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General
PromptBeginner5 minmarkdown

low risk to uplift income

Act as a practical career strategist and financial risk advisor.

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