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129,764 skills indexed with the new KISS metadata standard.

Showing 24 of 129,764Categories: Openclaw, Cursor-rules, Writing & Content, General, Coding & Debugging, Creative, Education
General
PromptBeginner5 minmarkdown

3. Maintain a natural

conversational tone—keep it light.

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General
PromptBeginner5 minmarkdown

· Capture key constraints (budget

seating

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General
PromptBeginner5 minmarkdown

Car Buying Intake Interview

# ==========================================================

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General
PromptBeginner5 minmarkdown

- When helpful

use ML language (correlation

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General
PromptBeginner5 minmarkdown

- Isolate anomalies and outliers confidently

and attribute them to network mechanics where causally plausible.

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General
PromptBeginner5 minmarkdown

- Keep the tone concise

analytical

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Creative
PromptBeginner5 minmarkdown

- Provide specific

technically grounded creative recommendations that account for format constraints per network.

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General
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- Highlight early signals the model would treat as predictors per network (CTR → IPM deterioration on ALN

CPI drift patterns on Mintegral

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Creative
PromptBeginner5 minmarkdown

- Always analyze creatives at two levels: within each network

and across all four networks simultaneously.

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General
PromptBeginner5 minmarkdown

- Format-specific opportunities (e.g.

an endcard mechanic untested on ALN

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Creative
PromptBeginner5 minmarkdown

**Promising Creative(s):** Identify early positive signals and specify which variations — pacing edits

hook recuts

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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.

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Education
PromptBeginner5 minmarkdown

**Worst Creative(s):** Explain which patterns predict failure

and flag whether the failure is universal or network-localized.

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General
PromptBeginner5 minmarkdown

- Which are candidates for format adaptation (e.g.

recut for Google's asset ingestion

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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?

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General
PromptBeginner5 minmarkdown

- State the performance delta (e.g.

top 1 on ALN

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Education
PromptBeginner5 minmarkdown

- High Spend / Poor Results: Explain the inefficiency pattern and the likely network-specific ML reason (e.g.

ALN AXON fallback behavior

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Education
PromptBeginner5 minmarkdown

- Highest CPI: Explain which signals

specific to this network

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General
PromptBeginner5 minmarkdown

- 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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Education
PromptBeginner5 minmarkdown

- Top Creative by Spend: Explain why this network's algo is favoring it

and whether scaling is amplifying or compressing efficiency.

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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

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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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