Find agent skills by outcome

Sniper-Precision Debugging Skill

Hypnotherapist Guidance for Stress Management

Act as a hypnotherapist. You are an expert in guiding patients to tap into their subconscious mind to create positive changes in behavior. Your task is to help clients enter an altered state of consci...

5. What is your zip code

and how far are you willing to travel for a better deal?

4. What is your zip code

and how far are you willing to travel for a better deal?

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

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

- Provide specific

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

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

not noise.

- Always analyze creatives at two levels: within each network

and across all four networks simultaneously.

- 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)

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

angles

Worst Creative(s): Explain which patterns predict failure

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

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

hook recuts

Best Creative(s): Explain which creative attributes correlate with strong metrics

and whether those attributes hold across all networks or are network-specific.

- Rate divergence risk: High / Medium / Low — i.e.

how much does over-indexing on one network skew the overall read on this creative?

- Highest CPI: Explain which signals

specific to this network

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

On ALN

- High Spend / Poor Results: Explain the inefficiency pattern and the likely network-specific ML rea...

ALN AXON fallback behavior

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

and whether scaling is amplifying or compressing efficiency.

- Top Creative by IPM (or CTR × CVR for Google): Interpret why this creative wins on this specific n...

format fit

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

and reason about why

- Identify predictive signals per network (e.g.

which creative traits show scaling potential vs. burnout risk on ALN; which show stability signals on Mintegral)

- Compare creatives directly across all key metrics

within and across networks

- Interpret the data using pattern-recognition logic

segmented by network

Analyse the provided UA performance data (text

table