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Agent skill

Bug Reproduction Test Generator

by ArabelaTso in ArabelaTso/Skills-4-SE

Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories.

Apache-2.0Auto-check passedTesting & QA

Install Bug Reproduction Test Generator

skills CLI
$ npx skills add ArabelaTso/Skills-4-SE --skill bug-reproduction-test-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ArabelaTso/Skills-4-SE bug-reproduction-test-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ArabelaTso/Skills-4-SE.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bug-reproduction-test-generator .claude/skills/bug-reproduction-test-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bug-reproduction-test-generator
GitHub stars
253
Token cost
~1.8k tokens
SKILL.md length
501 words
Files
1
Skills in repo
170
Repo updated
First seen
Licence
Apache-2.0

At a glance

Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories.

  • Works in 4 steps: Analyze the Issue Report → Inspect the Repository → Generate the Reproduction Test → …
  • Create a test that reproduces a bug described in an issue report
  • SKILL.md covers Workflow, Example Workflow, Constraints and Handling Underspecified Issues, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Bug Reproduction Test Generator is an agent skill from ArabelaTso/Skills-4-SE. 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 triggers the reported bug.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering Unit testing, Debugging and Test generation. The repository describes itself as: A curated list of 180+ useful Claude Skills for Software Engineering and resources for customizing AI for SE workflows. The licence is Apache-2.0.

When your agent uses it

  • Create a test that reproduces a bug described in an issue report
  • Generate failing tests from bug descriptions
  • Validate bug reports by creating reproducible test cases
  • Convert issue reports into executable regression tests

Example prompts

  • “/bug-reproduction-test-generator”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Analyze the Issue Report
  2. Inspect the Repository
  3. Generate the Reproduction Test
  4. Output Format

What it can do on your machine

Read from SKILL.md and the folder at commit 4f38503. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python, markdown, java and javascript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bug Reproduction Test Generator loads about 1.8k tokens when it runs. Until then it costs about 138 tokens; SKILL.md has 501 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~138
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ArabelaTso/Skills-4-SE at commit 4f38503, republished under its Apache-2.0 licence (© ArabelaTso). 501 words, ~1,769 tokens.

Download SKILL.mdSave it as .claude/skills/bug-reproduction-test-generator/SKILL.md (or your agent's skills folder).
name
bug-reproduction-test-generator
description
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 triggers the reported bug.

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
Show full SKILL.md (203 more words)Show less

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):

python
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:

markdown
## 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:

python
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)
java
@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)
javascript
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:

python
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

© ArabelaTso, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

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

Open the folder on GitHubat commit 4f38503

Compare with similar skills

Bug Reproduction Test Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Bug Reproduction Test Generator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Bug Reproduction Test Generator this skillArabelaTso/Skills-4-SE253—~1.8kAutomated safety check: PassApache-2.0
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Atmos Testscloudposse/atmos1.4k—~1.9kAutomated safety check: PassApache-2.0
Exploratory Testtobihagemann/turbo409—~2kAutomated safety check: PassMIT
Exploratory Testtobihagemann/turbo409—~2kAutomated safety check: PassMIT
Frappe Testing UnitImpertio-Studio/Frappe_Claude_Skill_Package188—~3kAutomated safety check: PassMIT

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Categories

Questions about Bug Reproduction Test Generator

What does Bug Reproduction Test Generator do?

Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories. Bug Reproduction Test Generator is an agent skill from ArabelaTso/Skills-4-SE. Automatically generates executable tests that reproduce reported bugs from issue reports and code repositories.

When should I use Bug Reproduction Test Generator?

Bug Reproduction Test Generator fits situations like: create a test that reproduces a bug described in an issue report; generate failing tests from bug descriptions; validate bug reports by creating reproducible test cases; convert issue reports into executable regression tests.

How do I install Bug Reproduction Test Generator in Claude Code?

Run `npx skills add ArabelaTso/Skills-4-SE --skill bug-reproduction-test-generator -a claude-code`. Or copy the skill folder (skills/bug-reproduction-test-generator in ArabelaTso/Skills-4-SE) into .claude/skills/bug-reproduction-test-generator in your project. Claude Code loads it when a task matches its description.

How do I install Bug Reproduction Test Generator in Codex?

Run `npx skills add ArabelaTso/Skills-4-SE --skill bug-reproduction-test-generator -a codex`. Or copy the skill folder (skills/bug-reproduction-test-generator in ArabelaTso/Skills-4-SE) into .agents/skills/bug-reproduction-test-generator in your project. Codex loads it when a task matches its description.

Can I use Bug Reproduction Test Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ArabelaTso/Skills-4-SE --skill bug-reproduction-test-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bug-reproduction-test-generator, .gemini/skills/bug-reproduction-test-generator, .github/skills/bug-reproduction-test-generator and .opencode/skills/bug-reproduction-test-generator in your project.

What does Bug Reproduction Test Generator need to run?

SKILL.md names no scripts, command-line tools or credentials: Bug Reproduction Test Generator is instructions for the agent only. Our summary lists: Python 3.

Does Bug Reproduction Test Generator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bug Reproduction Test Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bug Reproduction Test Generator use?

Bug Reproduction Test Generator is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bug Reproduction Test Generator use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bug Reproduction Test Generator?

Skills that share tags, products or a category with Bug Reproduction Test Generator: Offload (imbue-ai/offload, 125 stars), Atmos Tests (cloudposse/atmos, 1.4k stars), Exploratory Test (tobihagemann/turbo, 409 stars) and Exploratory Test (tobihagemann/turbo, 409 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bug Reproduction Test Generator?

ArabelaTso (a GitHub user) maintains it in ArabelaTso/Skills-4-SE, which has 253 GitHub stars. The repository holds 170 skills in this directory. The repository was last updated on August 21, 2026.

Source: ArabelaTso/Skills-4-SE on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.