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    📒 Qualified Demand Ledger

    1

    Classify launch, outreach, checkout, payment, usage, and review-time evidence without counting views, deployments, sent messages, or owner tests as demand.

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    See it in action

    You say

    A directory impression, an owner verification payment, an external buyer question with direct attribution, a verified settlement, and a recurring use event two days later for the same opaque actor and product.

    Your agent does

    Exposure and owner activity remain outside demand and revenue. The buyer question counts as qualified demand, the settlement counts in its own currency, and eligible later use counts as retention with stable findings and receipts.

    What you get

    Audit whether a launch report mislabeled impressions or directory exposure as demandSeparate owner-controlled checkout and payment verification from external buyer behavior and revenueReconcile attributed clicks, buyer questions, checkout openings, installs, settlements, commissions, and recurring useProduce a stable receipt before an agent claims a commercial experiment worked

    About this skill

    Qualified Demand Ledger turns a normalized local JSON event set into a deterministic commercial-evidence receipt. It separates exposure, operations, candidate signals, qualified demand, validated review-time reduction, external revenue, retention, and excluded evidence. Weak attribution stays a candidate. External revenue requires amount, currency, and transaction evidence. Recurring use requires an eligible external non-owner baseline for the same opaque actor and product at least 24 hours earlier. Duplicate evidence and out-of-window events are excluded. The bundled Python helper runs offline with the standard library and writes reviewable JSON and Markdown reports with stable findings and SHA-256 receipts. It does not retrieve analytics, contact buyers, convert currencies, authenticate source references, or claim that a clean ledger proves demand, profitability, or product-market fit.

    demand-evidence
    traction-audit
    commercial-ledger
    launch-analytics
    revenue-evidence
    agent-operations

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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