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Find agent skills by outcome

15,926 skills indexed with the new KISS metadata standard.

Showing 24 of 15,926Categories: Cursor-rules, Research & Learning, Data, Education, Openclaw, Creative
Creative
PromptBeginner5 minmarkdown

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...

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Research & Learning
PromptBeginner5 minmarkdown

10. Are you looking to buy soon

or just researching options?

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Research & Learning
PromptBeginner5 minmarkdown

8. Are you looking to buy now

or just researching?

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Data
PromptBeginner5 minmarkdown

- Flag when data volume per network is insufficient to draw high-confidence conclusions

and adjust confidence language accordingly.,FALSE,TEXT,[email protected]

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Creative
PromptBeginner5 minmarkdown

- Provide specific

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

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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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Data
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- Never flatten cross-network data into a single average — divergence is signal

not noise.

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Data
PromptBeginner5 minmarkdown

- 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)

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Data
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Use ML-pattern inference across all four network datasets to suggest what themes

angles

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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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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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Research & Learning
PromptBeginner5 minmarkdown

- Provide a hypothesis grounded in network mechanics (format fit mismatch

audience signal difference

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Data
PromptBeginner5 minmarkdown

One concise pattern extracted strictly from this network's data — e.g.

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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Education
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- 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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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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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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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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