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…
ArabelaTso/Skills-4-SE/skills/bug-reproduction-test-generator/SKILL.md
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
Decision brief
Generate executable tests that reproduce reported bugs based on issue reports and code repositories.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/ArabelaTso/Skills-4-SE --skill "skills/bug-reproduction-test-generator"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
Follow these steps to generate a bug reproduction test:
Generated Test (Python/pytest):
Extract key information from the issue report:
Identify relevant code and context:
Create a minimal, focused test that:
Permission review
The documentation asks the agent to read local files, directories, or repositories.
### 2. Inspect the RepositoryEvidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 90/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 236 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Generate executable tests that reproduce reported bugs based on issue reports and code repositories.
Follow these steps to generate a bug reproduction test:
Extract key information from the issue report:
Identify relevant code and context:
Create a minimal, focused test that:
Test structure:
Assertions:
Documentation:
Provide:
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()
@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();
});
}
test('reproduces bug #123: [brief description]', () => {
// Setup: Create conditions that trigger the bug
// Execute and Assert: Verify the buggy behavior
expect(() => {
buggyFunction();
}).toThrow(ExpectedException);
});
When the issue report lacks details:
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)
Frequently asked questions
Generate executable tests that reproduce reported bugs based on issue reports and code repositories.
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.
Static rules flagged read-files in the source; the page lists the matching lines and excerpts.
Alternatives
dotnet/skills
Analyzes test suites in any language and tags each test with standardized traits (positive, negative, critical-path, boundary, smoke, regression, integration, performance, security). Use when the user wants to categorize, audit, or label tests with traits. Works across .NET (MSTest/xUnit/NUnit/TUnit), Python (pytest), TS/JS (Jest/Vitest), Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++ — auto-editing when the framework has canonical tag syntax, otherwise report-only. Do not use for writ
trailofbits/skills
Mutation-driven test vector generation. Finds implementations of a cryptographic algorithm or protocol, runs mutation testing to identify escaped mutants, then generates new test vectors that deliberately exercise the uncovered code paths. Compares before/after mutation kill rates to prove vector effectiveness. Use when generating cryptographic test vectors, measuring Wycheproof coverage gaps, finding escaped mutants via mutation testing, creating cross-implementation test suites, or improving t
travisjneuman/.claude
This skill should be used when writing test cases, fixing bugs, analyzing code for potential issues, or improving test coverage for JavaScript/TypeScript applications. Use this for unit tests, integration tests, end-to-end tests, debugging runtime errors, logic bugs, performance issues, security vulnerabilities, and systematic code analysis.
K-Dense-AI/scientific-agent-skills
Build, inspect, test, and analyze bounded process-based discrete-event simulations with SimPy, including events, resources, interrupts, monitoring, replications, warm-up, and reproducible output analysis.