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    AI Bug Report & Reproduction Assistant

    1

    Transforms messy bug descriptions and logs into structured, reproduction-ready QA reports and test cases.

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    AI Bug Report & Reproduction Assistant

    AI Bug Report & Reproduction Assistant

    Example session with this skill installed

    A user says the checkout page hangs when they try to use a discount code 'SAVE20' on Chrome. They sent a screenshot of a 400 error in the console. Help me write a report.

    • Read your context and instructions
    • Compiled the ai bug report
    • Generated the document

    The reported issue has been converted into a structured bug report. Missing environment details and specific API request fields have been flagged for follow-up.

    Checkout — Page hangs after applying discount code — Chrome

    Summary

    The checkout page becomes unresponsive when a user attempts to apply a specific discount code ('SAVE20'), accompanied by a 400 Bad Request error in the console.

    Affected Area

    Checkout / Coupon System

    Environment

    • Application: Web Storefront
    • Browser: Chrome
    • Version / build: Not provided
    • Operating system: Not provided
    • Device: Not provided

    Preconditions

    1. User must have items in the cart.
    2. User must be on the Checkout page.

    Steps to Reproduce

    1. Navigate to the checkout page with items in the cart.
    2. Enter the discount code 'SAVE20' into the coupon field.
    3. Click the 'Apply' button.
    4. Observe the page state and console output.

    Expected Behavior

    The system should validate the code, apply the discount to the total, or display a clear validation error if the code is invalid. The page should remain interactive.

    Actual Behavior

    The checkout page hangs (becomes unresponsive) and a 400 Bad Request error is logged to the browser console.

    Reproducibility

    Unknown (Frequency not specified by user).

    Severity Suggestion

    High

    Reason

    Blocks the primary revenue-generating workflow (checkout) for users attempting to use discounts.

    Evidence

    • Screenshot: Provided (shows 400 error).
    • Logs: Not provided.
    • Console error: 400 Bad Request.

    Missing Information

    • What was the specific API endpoint that returned the 400 error?
    • Was the user logged in or a guest?
    • Does this happen with other discount codes or only 'SAVE20'?

    QA Verification

    TC-001 — Verify Discount Code Application

    Objective: Confirm checkout remains responsive during coupon validation.
    Steps:

    1. Add items to cart.
    2. Apply code 'SAVE20'.
    3. Verify total updates and UI is interactive.
      Expected Result: Discount applied and UI remains active.

    Developer Investigation Notes

    • Inspect the network tab to see the payload sent to the /apply-coupon (or equivalent) endpoint.
    • Check if the 400 error is due to a malformed request body or an unhandled validation exception on the backend.

    Next steps

    1. Request the full API response body from the user or support logs.
    2. Test the 'SAVE20' code in the staging environment.
    3. Check Sentry/Datadog for 400 errors on the checkout endpoint.

    ai-bug-report-reproduction-assistant.pdf

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

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

    What you get

    Standardize bug reporting across support and engineering teams.Identify missing technical evidence in user-submitted complaints.Generate regression test cases automatically from bug descriptions.Triage bulk issue logs to find duplicates and assess severity.

    About this skill

    The problem

    Vague bug reports like "the button is broken" or raw support logs waste hours of engineering time. Developers often lack the exact reproduction steps, environment details, or console errors needed to start a fix.

    What it does

    • Converts conversational complaints and raw logs into structured, developer-ready markdown bug reports.
    • Extracts atomic, step-by-step reproduction paths from messy user descriptions.
    • Identifies critical missing information, such as browser versions or specific API payloads, before the ticket reaches dev.
    • Generates focused QA test cases and regression scenarios to ensure the fix stays fixed.
    • Suggests severity based on impact factors like data integrity and workflow blocks.

    Why this beats prompting it yourself

    This skill enforces a strict separation between observed facts and technical hypotheses, preventing "hallucinated" root causes. It follows a specific QA framework that ensures consistency across your entire issue tracker, which is difficult to maintain with simple prompts.

    Use cases

    • Converting messy Slack or Discord bug reports into GitHub or Jira tickets.
    • Analyzing raw API error responses to build technical reproduction steps.
    • Creating regression test suites for manual QA teams after a bug is identified.
    • Triage of bulk support tickets to identify duplicates and prioritize based on impact.

    Known limitations

    Cannot access live production environments or verify if a bug is truly fixed. It relies entirely on provided text, logs, and images.

    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

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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    Verified clean 10 days ago

    • Passed all security checks, Safe to install

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