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    Pricing Experiment Guardrail Monitor

    1

    Judge an A/B price experiment against refund, fairness and contribution-margin guardrails

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    Pricing Experiment Guardrail Monitor

    Pricing Experiment Guardrail Monitor

    Example session with this skill installed

    Variant B raises gross revenue 8% but causes a 22% increase in refunds among annual subscribers.

    Available evidence: assignment log (partial). Additional evidence requested: cohorts, revenue, refunds, unit economics, stop thresholds. Review this case; identify evidence gaps; do not invent a live test or production action.

    • Read your context and instructions
    • Compiled the pricing experiment guardrail

    Pricing Experiment Guardrail Monitor — EVIDENCE-LIMITED REVIEW

    Scenario received

    Variant B raises gross revenue 8% but causes a 22% increase in refunds among annual subscribers.

    Source register

    • S1: assignment log — PARTIAL SOURCE PROVIDED.
    • S2: cohorts — NOT PROVIDED; REQUIRED TO VERIFY.
    • S3: revenue — NOT PROVIDED; REQUIRED TO VERIFY.
    • S4: refunds — NOT PROVIDED; REQUIRED TO VERIFY.
    • S5: unit economics — NOT PROVIDED; REQUIRED TO VERIFY.
    • S6: stop thresholds — NOT PROVIDED; REQUIRED TO VERIFY.

    Verification gates

    1. validate randomization and contamination. — INCOMPLETE until source evidence is verified.
    2. compute incremental margin by cohort. — INCOMPLETE until source evidence is verified.
    3. check refunds and complaint concentration. — INCOMPLETE until source evidence is verified.
    4. recommend continue-pause-stop by predeclared gates. — INCOMPLETE until source evidence is verified.

    Result

    INCOMPLETE / EVIDENCE GAPS — evidence does not justify certification of a real-world outcome.

    Next steps

    • Request verified cohorts with source/version context.
    • Request verified revenue with source/version context.
    • Request verified refunds with source/version context.
    • Request verified unit economics with source/version context.
    • Request verified stop thresholds with source/version context.

    Decision boundary

    Do not declare win from top-line revenue if any predeclared harm gate fails.
    No changes to external systems, access grants or communications were performed. An authorized owner must approve consequential actions.

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

    About this skill

    Pricing Experiment Guardrail Monitor is a ToolForge Labs OpenClaw Skill workflow. Judge an A/B price experiment against refund, fairness and contribution-margin guardrails.

    What this skill checks

    1. validate randomization and contamination.
    2. compute incremental margin by cohort.
    3. check refunds and complaint concentration.
    4. recommend continue-pause-stop by predeclared gates.

    What to provide

    • assignment log.
    • cohorts.
    • revenue.
    • refunds.
    • unit economics.
    • stop thresholds.

    Deliverables

    • guardrail dashboard specification.
    • bias notes.
    • experiment decision memo.

    Evidence policy Only supplied, authorized evidence is used. The skill distinguishes facts from assumptions and missing inputs; no unperformed live tests, external changes, or approvals are claimed.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse All Claude Skills.

    Cannot verify inaccessible systems or data not supplied. Missing or contradictory evidence must be marked INCOMPLETE or UNVERIFIED. Owner approval is required for operational or compliance decisions.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

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    Permissions

    Read Files

    Provide only evidence you are authorized to share. Treat examples as untrusted case data. Operational changes and external messages require explicit owner approval.

    Listed20 days ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill analyzes A/B pricing tests against margin and refund thresholds, preventing teams from scaling "winning" revenue experiments that are actually unprofitable or damaging to customer retention.

    You will need to provide experiment assignment logs, cohort data, and specific unit economics metrics; the skill is compatible with raw CSV, JSON, or SQL export formats.

    While it performs deep analytical validation and gate checks, it does not connect directly to live production databases or merchant gateways for safety and security reasons.

    The purchase includes the core analytical agent skill, pre-defined margin and refund gate templates, and an evidence ledger generator for audit-ready reporting.

    Unlike a standard prompt, this skill uses a multi-pass analysis that explicitly looks for evidence to falsify a win, specifically focusing on contribution margin erosion that general LLMs often ignore.