Ad & Creative Manager

    1

    Analyze Etsy and Meta/TikTok ads with seller-provided unit economics, optional user-chosen thresholds, and structured creative test hypotheses.

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    Ad & Creative Manager

    Example session with this skill installed

    My net revenue per acquired order is $50 and my non-ad variable costs are $31. I want $5 profit per order. Actual ad spend was $210 and 12 acquired orders were attributed using my chosen method. Frequency is 2.8. Calculate break-even, target, and realized CAC, then draft one curiosity-led video test. Do not use a default CAC percentage or claim that frequency proves creative fatigue.

    • Read your context and instructions
    • Compiled the ad & creative

    Data check

    All monetary inputs use the same currency. Actual spend is provided and acquired orders are a positive whole number, so realized CAC can be calculated. Attribution quality is user-supplied and is not independently verified.

    MetricCalculationResult
    Break-even CAC$50 − $31$19.00
    Target CAC$50 − $31 − $5$14.00
    Realized CAC$210 ÷ 12$17.50

    Decision: DOES_NOT_MEET_USER_TARGET. Realized CAC is below the calculated break-even CAC but above your $14 target CAC. This is not an automatic pause instruction. Frequency 2.8 is context only and does not by itself prove creative fatigue.

    Creative hypothesis: curiosity-led product demonstration

    SegmentDraftPurpose
    0–3s“I expected the usual result—then this detail changed the test.”Open a curiosity gap without an unverifiable promise.
    3–10sShow the customer problem using the product in a realistic setting.Make the use case clear.
    10–22sDemonstrate one verifiable feature and the related benefit.Provide evidence rather than hype.
    22–28sAdd an authentic review only if permission and source records exist.Optional social proof.
    28–30s“See the details and decide if it fits your needs.”Low-pressure CTA.

    Next steps

    1. Verify attribution, net revenue, and cost inputs before changing spend.
    2. Test this draft against one control while keeping audience, offer, and landing page stable.
    3. Choose the test budget, duration, and success threshold yourself.
    4. Recalculate after the agreed observation window; do not infer causal lift from a single metric.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Calculate break-even and target CAC from seller-provided revenue, non-ad costs, and target profit.Calculate realized CAC only when valid actual spend and acquired-order data are provided.Compare results with an optional user-chosen threshold and explain the decision state.Generate structured creative hypotheses, video-script drafts, and controlled test plans without a performance guarantee.

    About this skill

    The problem

    Ad decisions can become unreliable when campaign metrics are compared with generic percentages instead of the seller’s own unit economics. Creative performance also varies by product, audience, offer, channel, and measurement quality.

    What it does

    • Calculates break-even CAC and target CAC from the revenue, non-ad variable costs, and target profit you provide.
    • Calculates realized CAC only when actual ad spend and a positive whole-number count of acquired orders are available.
    • Compares results with an optional threshold you explicitly choose; it does not apply a default spend-to-sales ratio, CAC percentage, budget, data window, or cart-value rule.
    • Creates structured creative hypotheses, video-script drafts, and test plans for Etsy, Meta, or TikTok without claiming that a hook or script will improve performance.

    Decision framework

    The workflow keeps break-even CAC, target CAC, realized CAC, and any user-chosen threshold separate. Missing or inconsistent inputs produce a cannot-calculate result instead of a forced pause or scale recommendation.

    Use cases

    • Comparing realized CAC with a seller-defined target profit.
    • Documenting why an ad set meets or misses a user-chosen threshold.
    • Creating alternative hooks and shot lists as test hypotheses.
    • Preparing a controlled creative-test plan with success criteria chosen by the user.

    Known limitations

    Outputs depend on the accuracy and completeness of the data supplied. The skill does not access live ad accounts, attribute sales, predict conversion, guarantee ROAS, or determine causation from frequency or CAC alone. Platform rules and performance patterns change; verify current requirements and use controlled tests before changing spend.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

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    Recently published to Agensi

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    • Passed all security checks, Safe to install

    Listed22 days ago
    Updated8 days ago

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