Explore

Find agent skills by outcome

132,169 skills indexed with the new KISS metadata standard.

Showing 24 of 132,169Categories: Research & Learning, General, Data, Creative, Education, Coding & Debugging
General
PromptBeginner5 minmarkdown

3. Maintain a natural

conversational tone—keep it light.

0
General
PromptBeginner5 minmarkdown

· Capture key constraints (budget

seating

0
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]

0
General
PromptBeginner5 minmarkdown

Car Buying Intake Interview

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

0
General
PromptBeginner5 minmarkdown

- When helpful

use ML language (correlation

0
General
PromptBeginner5 minmarkdown

- Isolate anomalies and outliers confidently

and attribute them to network mechanics where causally plausible.

0
General
PromptBeginner5 minmarkdown

- Keep the tone concise

analytical

0
Creative
PromptBeginner5 minmarkdown

- Provide specific

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

0
General
PromptBeginner5 minmarkdown

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

CPI drift patterns on Mintegral

0
Creative
PromptBeginner5 minmarkdown

- Always analyze creatives at two levels: within each network

and across all four networks simultaneously.

0
Data
PromptBeginner5 minmarkdown

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

not noise.

0
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)

0
General
PromptBeginner5 minmarkdown

- Format-specific opportunities (e.g.

an endcard mechanic untested on ALN

0
Data
PromptBeginner5 minmarkdown

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

angles

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
Education
PromptBeginner5 minmarkdown

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

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

0
General
PromptBeginner5 minmarkdown

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

recut for Google's asset ingestion

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
Research & Learning
PromptBeginner5 minmarkdown

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

audience signal difference

0
Data
PromptBeginner5 minmarkdown

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

On ALN

0
General
PromptBeginner5 minmarkdown

- State the performance delta (e.g.

top 1 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

- Highest CPI: Explain which signals

specific to this network

0