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ArabelaTso/Skills-4-SE/skills/bug-reproduction-test-generator/SKILL.md

bug-reproduction-test-generator

Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories. Use when users need to: (1) Create a test that reproduces a bug described in an issue report, (2) Generate failing tests from bug descriptions, stack traces, or error messages, (3) Validate bug reports by creating reproducible test cases, (4) Convert issue reports into executable regression tests. Takes a repository and issue report as input and produces test code that reliably trigger

Source repository stars
236
Declared platforms
0
Static risk flags
1
Last source update
2026-08-21
Source checked
2026-08-25

Decision brief

What it does: where it fits

Generate executable tests that reproduce reported bugs based on issue reports and code repositories.

Best for

  • Use when users need to: (1) Create a test that reproduces a bug described in an issue report, (2) Generate failing tests from bug descriptions, stack traces, or error messages, (3) Validate bug reports by creating repro…

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/ArabelaTso/Skills-4-SE --skill "skills/bug-reproduction-test-generator"
Safe inspection promptEditorial

Inspect the Agent Skill "bug-reproduction-test-generator" from https://github.com/ArabelaTso/Skills-4-SE/blob/4f38503747e0617504bce5329283ef837d375c09/skills/bug-reproduction-test-generator/SKILL.md at commit 4f38503747e0617504bce5329283ef837d375c09. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Workflow

    Follow these steps to generate a bug reproduction test:

    Symptoms: What goes wrong? (incorrect output, exception, crash, assertion failure, unexpected behavior)Affected components: Which modules, classes, or functions are involved?Triggering conditions: What inputs, states, or sequences trigger the bug?
  2. 02

    Example Workflow

    Generated Test (Python/pytest):

    Generated Test (Python/pytest):
  3. 03

    1. Analyze the Issue Report

    Extract key information from the issue report:

    Symptoms: What goes wrong? (incorrect output, exception, crash, assertion failure, unexpected behavior)Affected components: Which modules, classes, or functions are involved?Triggering conditions: What inputs, states, or sequences trigger the bug?
  4. 04

    2. Inspect the Repository

    Identify relevant code and context:

    Locate the affected components mentioned in the issueFind entry points (public APIs, main functions, test fixtures)Understand dependencies and required setup
  5. 05

    3. Generate the Reproduction Test

    Create a minimal, focused test that:

    Uses the repository's existing test framework and conventionsSets up minimal preconditions needed to trigger the bugExecutes the code path that triggers the bug

Permission review

Static risk signals and limitations

Reads files

low · line 19

The documentation asks the agent to read local files, directories, or repositories.

### 2. Inspect the Repository

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score90/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars236SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
ArabelaTso/Skills-4-SE
Skill path
skills/bug-reproduction-test-generator/SKILL.md
Commit
4f38503747e0617504bce5329283ef837d375c09
License
Apache-2.0
Collected
2026-08-25
Default branch
main
View the original SKILL.md

Bug Reproduction Test Generator

Generate executable tests that reproduce reported bugs based on issue reports and code repositories.

Workflow

Follow these steps to generate a bug reproduction test:

1. Analyze the Issue Report

Extract key information from the issue report:

  • Symptoms: What goes wrong? (incorrect output, exception, crash, assertion failure, unexpected behavior)
  • Affected components: Which modules, classes, or functions are involved?
  • Triggering conditions: What inputs, states, or sequences trigger the bug?
  • Stack traces: If provided, identify the call chain and failure point
  • Expected vs. actual behavior: What should happen vs. what actually happens?

2. Inspect the Repository

Identify relevant code and context:

  • Locate the affected components mentioned in the issue
  • Find entry points (public APIs, main functions, test fixtures)
  • Understand dependencies and required setup
  • Identify the test framework used (pytest, unittest, JUnit, Jest, etc.)
  • Check existing test patterns for consistency

3. Generate the Reproduction Test

Create a minimal, focused test that:

Test structure:

  • Uses the repository's existing test framework and conventions
  • Sets up minimal preconditions needed to trigger the bug
  • Executes the code path that triggers the bug
  • Asserts the symptom described in the issue report

Assertions:

  • For exceptions: Assert the exception type and message match the report
  • For incorrect output: Assert actual output matches the reported incorrect behavior
  • For crashes: Assert the crash occurs at the expected point
  • For assertion failures: Reproduce the failing assertion

Documentation:

  • Add inline comments explaining the reproduction logic
  • Reference the issue number/URL in the test name or docstring
  • Document any assumptions made due to underspecified details

4. Output Format

Provide:

  1. Executable test code in the appropriate language and framework
  2. Inline comments explaining how the test reproduces the bug
  3. Markdown summary including:
    • How the test reproduces the issue
    • Which symptoms it validates
    • Any assumptions made
    • Instructions for running the test

Example Workflow

Issue Report:

Title: Division by zero in calculate_average()
Description: When calling calculate_average([]) with an empty list,
the function crashes with ZeroDivisionError instead of returning 0.

Stack trace:
  File "stats.py", line 15, in calculate_average
    return sum(values) / len(values)
ZeroDivisionError: division by zero

Generated Test (Python/pytest):

import pytest
from stats import calculate_average

def test_calculate_average_empty_list_reproduction():
    """
    Reproduces bug: calculate_average([]) raises ZeroDivisionError
    Issue: #123

    Expected: Should return 0 for empty list
    Actual: Raises ZeroDivisionError
    """
    # Trigger the bug with empty list input
    with pytest.raises(ZeroDivisionError):
        result = calculate_average([])

    # This test currently passes (reproduces the bug)
    # After fix, change to: assert calculate_average([]) == 0

Summary:

## Bug Reproduction Test

**Issue**: Division by zero in calculate_average()

**How it reproduces the bug:**
- Calls `calculate_average([])` with an empty list
- Asserts that ZeroDivisionError is raised (the buggy behavior)

**Symptoms validated:**
- Exception type: ZeroDivisionError
- Location: stats.py line 15

**Assumptions:**
- The function should return 0 for empty lists (common convention)

**Running the test:**
```bash
pytest test_stats.py::test_calculate_average_empty_list_reproduction

After the bug is fixed: Replace the pytest.raises assertion with:

assert calculate_average([]) == 0

## Language-Specific Patterns

### Python (pytest/unittest)

```python
import pytest

def test_bug_reproduction_issue_123():
    """Reproduces bug #123: [brief description]"""
    # Setup: Create conditions that trigger the bug

    # Execute: Run the code that exhibits the bug

    # Assert: Verify the buggy behavior occurs
    with pytest.raises(ExpectedException):
        buggy_function()

Java (JUnit)

@Test
public void testBugReproduction_Issue123() {
    // Reproduces bug #123: [brief description]

    // Setup: Create conditions that trigger the bug

    // Execute and Assert: Verify the buggy behavior
    assertThrows(ExpectedException.class, () -> {
        buggyMethod();
    });
}

JavaScript (Jest)

test('reproduces bug #123: [brief description]', () => {
  // Setup: Create conditions that trigger the bug

  // Execute and Assert: Verify the buggy behavior
  expect(() => {
    buggyFunction();
  }).toThrow(ExpectedException);
});

Constraints

  • Do not modify production code - Only create test code
  • Do not assume fixes - Test the buggy behavior, not the expected correct behavior (unless explicitly stated in the issue)
  • Document assumptions - If the issue is underspecified, state assumptions clearly
  • Prefer minimal tests - Focus on isolating the bug, avoid unnecessary setup
  • Match existing patterns - Follow the repository's test conventions and style

Handling Underspecified Issues

When the issue report lacks details:

  1. State assumptions explicitly in test comments
  2. Document what's unclear in the summary
  3. Provide multiple test variants if multiple interpretations are possible
  4. Ask clarifying questions if critical information is missing

Example:

def test_bug_reproduction_issue_456():
    """
    Reproduces bug #456: Null pointer exception in processData()

    ASSUMPTION: The bug occurs when input is null (not specified in issue)
    ASSUMPTION: Using default configuration (not specified in issue)
    """
    # Test with null input (assumed trigger)
    with pytest.raises(NullPointerException):
        processData(None)

Tips for Effective Reproduction Tests

  1. Start simple - Begin with the most direct path to trigger the bug
  2. Isolate the bug - Remove unrelated setup and assertions
  3. Make it deterministic - Avoid flaky conditions (timing, randomness)
  4. Reference the issue - Include issue number in test name and comments
  5. Verify it fails - Run the test to confirm it reproduces the bug
  6. Plan for the fix - Comment on how the test should change after the bug is fixed

Frequently asked questions

What to verify before installation and use

What does the bug-reproduction-test-generator source document cover?

Generate executable tests that reproduce reported bugs based on issue reports and code repositories.

How do I install bug-reproduction-test-generator?

The source record exposes this install command: npx skills add https://github.com/ArabelaTso/Skills-4-SE --skill "skills/bug-reproduction-test-generator". Inspect the command and pinned source before running it.

Which permission-related actions were detected?

Static rules flagged read-files in the source; the page lists the matching lines and excerpts.

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