Agent skill

Regression Root Cause Analyzer

by ArabelaTso in ArabelaTso/Skills-4-SE

Locate root causes of failing regression tests by analyzing code changes, error messages, and test dependencies.

Apache-2.0Auto-check passedTesting & QA

Install Regression Root Cause Analyzer

skills CLI
$ npx skills add ArabelaTso/Skills-4-SE --skill regression-root-cause-analyzer -a claude-code

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

GitHub CLI
$ gh skill install ArabelaTso/Skills-4-SE regression-root-cause-analyzer --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/regression-root-cause-analyzer .claude/skills/regression-root-cause-analyzer && 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
regression-root-cause-analyzer
GitHub stars
253
Token cost
~3.4k tokens
SKILL.md length
1,029 words
Files
2 (incl. references)
Skills in repo
150
Repo updated
First seen
Licence
Apache-2.0

At a glance

Locate root causes of failing regression tests by analyzing code changes, error messages, and test dependencies.

  • Works in 6 steps: Gather Initial Information → Analyze Error Messages → Identify Code Changes → …
  • Regression tests start failing after code changes
  • SKILL.md covers Overview, Workflow, Root Cause Analysis: [Test Name] and Alternative Hypotheses, plus 4 more sections
  • Calls git, pytest and pip

What it does

Regression Root Cause Analyzer is an agent skill from ArabelaTso/Skills-4-SE. Locate root causes of failing regression tests by analyzing code changes, error messages, and test dependencies. Use when regression tests start failing after code changes, investigating test failures in CI/CD, debugging flaky tests, or understanding why previously passing tests now fail. Analyzes git diffs, stack traces, test output, and dependency changes to produce structured markdown reports ranking likely causes. Triggers when users ask to find why tests are failing, debug regression failures, investigate…

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/failure-patterns.md`).

It sits in Testing & QA, covering Failing and flaky tests, Root cause analysis and Debugging. It works with Git. 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

  • Regression tests start failing after code changes
  • Investigating test failures in CI/CD
  • Debugging flaky tests
  • Understanding why previously passing tests now fail

Example prompts

  • “/regression-root-cause-analyzer”

Requirements

  • Python 3
  • Node.js

Workflow steps

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

  1. Gather Initial Information
  2. Analyze Error Messages
  3. Identify Code Changes
  4. Investigate Specific Failure Patterns
  5. Generate Root Cause Report
  6. Verify the Root Cause

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

    Shell commands in SKILL.md call:

    • git
    • pytest
    • pip
    • npm

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

  • Network

    No URLs in SKILL.md. Its commands use git, pip and npm, which can reach the network depending on how they are called.

    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

Regression Root Cause Analyzer loads about 3.4k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 148 tokens; SKILL.md has 1,029 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~148
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.2k

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). 1,029 words, ~3,407 tokens.

Download SKILL.mdSave it as .claude/skills/regression-root-cause-analyzer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
regression-root-cause-analyzer
description
Locate root causes of failing regression tests by analyzing code changes, error messages, and test dependencies. Use when regression tests start failing after code changes, investigating test failures in CI/CD, debugging flaky tests, or understanding why previously passing tests now fail. Analyzes git diffs, stack traces, test output, and dependency changes to produce structured markdown reports ranking likely causes. Triggers when users ask to find why tests are failing, debug regression failures, investigate test breakage, or analyze failing test suites.

Regression Root Cause Analyzer

Overview

Systematically investigate failing regression tests to identify root causes by analyzing code changes, error messages, test dependencies, and common failure patterns.

Workflow

1. Gather Initial Information

Collect essential details about the test failure:

Test failure details:

  • Which test(s) are failing?
  • Error message and stack trace
  • When did tests start failing? (commit, PR, date)
  • Do tests fail consistently or intermittently?
  • Do tests fail locally, in CI, or both?

Quick commands to gather info:

bash
# Run the failing test
pytest path/to/test_file.py::test_name -v

# Get recent commits
git log --oneline -10

# Check current branch and status
git status
git branch

# See what changed recently
git log --since="1 week ago" --oneline

# Check for uncommitted changes
git diff
2. Analyze Error Messages

Parse the error message and stack trace for clues. See failure-patterns.md for common patterns.

Error type indicators:

ImportError / ModuleNotFoundError:

ImportError: cannot import name 'UserService' from 'app.services'
  • Likely cause: Module or class renamed/moved
  • Investigation: Check recent commits to app/services/

AttributeError:

AttributeError: 'User' object has no attribute 'email_address'
  • Likely cause: Property renamed or removed
  • Investigation: Check User class definition changes

TypeError (arguments):

TypeError: process_data() got an unexpected keyword argument 'format'
  • Likely cause: Function signature changed
  • Investigation: Find process_data definition and recent changes

AssertionError:

AssertionError: assert 3 == 2
  • Likely cause: Logic change or test data change
  • Investigation: Understand what the assertion checks

KeyError / IndexError:

KeyError: 'status'
  • Likely cause: Data structure changed
  • Investigation: Check response/data format changes
3. Identify Code Changes

Use git to find what changed since tests last passed.

Find When Tests Broke
bash
# If you know the last good commit
git diff <last-good-commit> <current-commit>

# Check specific file changes
git log -p path/to/file.py

# See what changed in last N commits
git log -p -n 5

# Find commits that touched specific function
git log -S "function_name" -p
Analyze Relevant Changes

Priority order for investigation:

  1. Direct changes to tested code - Changes to the file/class being tested
  2. Changes to imported dependencies - Files imported by tested code
  3. Changes to test fixtures/mocks - Test setup code
  4. Changes to test infrastructure - pytest config, test runners
  5. Dependency version changes - requirements.txt, package.json

Commands to find changes:

bash
# What files changed recently?
git diff --name-only HEAD~5..HEAD

# Changes to specific file
git diff HEAD~5..HEAD path/to/file.py

# Changes to test file
git diff HEAD~5..HEAD path/to/test_file.py

# Changes to requirements
git diff HEAD~5..HEAD requirements.txt package.json
4. Investigate Specific Failure Patterns

Match the error to common patterns:

Pattern: API Signature Change

Symptoms:

  • TypeError: missing required argument
  • TypeError: got unexpected keyword argument

Investigation steps:

  1. Find function definition: grep -r "def function_name" .
  2. Check git history: git log -p -S "def function_name"
  3. Compare signatures before/after
  4. Update test calls to match new signature
Pattern: Return Type Change

Symptoms:

  • AttributeError when accessing return value
  • TypeError: 'NoneType' object is not iterable

Investigation steps:

  1. Check function return statements
  2. Look for changes from return [] to return None
  3. Check if error handling changed
  4. Update test to handle new return type
Pattern: Dependency Version Change

Symptoms:

  • Tests fail after pip install or npm install
  • Different behavior in CI vs local

Investigation steps:

  1. Check dependency files: git diff HEAD~5..HEAD requirements.txt
  2. Review changelogs for updated packages
  3. Look for deprecation warnings in test output
  4. Pin to previous version to confirm
Pattern: Test Isolation Issue

Symptoms:

  • Tests pass individually but fail when run together
  • Order-dependent failures

Investigation steps:

  1. Run tests individually: pytest test_file.py::test_one
  2. Run in different orders
  3. Check for shared state (global variables, database, files)
  4. Look for missing cleanup in teardown
5. Generate Root Cause Report

Produce a structured markdown report:

Root Cause Analysis: [Test Name]

Summary
  • Test: test_user_registration
  • Status: Failing since commit abc123
  • Error: TypeError: process_user() got an unexpected keyword argument 'email_format'
Root Cause

The process_user() function signature changed in commit abc123. The parameter email_format was renamed to email_type.

Evidence:

  • Commit abc123 modified app/users.py
  • Function signature before: def process_user(data, email_format="html")
  • Function signature after: def process_user(data, email_type="html")
  • Test still calls: process_user(user_data, email_format="html")
Likelihood: High (95%)

This is the direct cause of the TypeError.

Fix Required

Update test to use new parameter name:

python
# Before
result = process_user(user_data, email_format="html")

# After
result = process_user(user_data, email_type="html")
  • Commit abc123: Renamed email_format to email_type throughout codebase
  • 5 other test files also need updates
Additional Notes

The function behavior is otherwise unchanged. Only the parameter name differs.


Alternative Hypotheses

Hypothesis 2: Test Data Changed

Likelihood: Low (10%)

The test fixture might have changed, but review shows fixtures are unchanged.

Hypothesis 3: Environment Difference

Likelihood: Very Low (5%)

Could be environment-related, but error is consistent locally and in CI.


Reproduction Steps

  1. Checkout commit abc123
  2. Run: pytest tests/test_users.py::test_user_registration
  3. Observe TypeError
Show full SKILL.md (417 more words)Show less

Verification Steps

  1. Apply suggested fix
  2. Run test: pytest tests/test_users.py::test_user_registration
  3. Verify test passes

6. Verify the Root Cause

Before finalizing the analysis:

Test the hypothesis:

  1. Apply the proposed fix
  2. Run the test to confirm it passes
  3. Run related tests to ensure no new breaks

If fix doesn't work:

  1. Review alternative hypotheses
  2. Gather more information
  3. Expand investigation to related areas

Commands to verify:

bash
# Run the specific failing test
pytest path/to/test.py::test_name -v

# Run all related tests
pytest path/to/test.py -v

# Run with verbose output
pytest path/to/test.py::test_name -vv

# Run with print statements visible
pytest path/to/test.py::test_name -s

Investigation Strategies

Strategy 1: Binary Search Through Commits

Find exact commit that broke tests:

bash
# Start bisect
git bisect start

# Mark current (broken) commit
git bisect bad

# Mark last known good commit
git bisect good <commit-hash>

# Git will checkout middle commit
# Run tests, then mark good or bad
pytest tests/

# If tests pass
git bisect good

# If tests fail
git bisect bad

# Repeat until git finds the breaking commit
Strategy 2: Compare Working vs Broken

Diff approach:

bash
# Compare file between commits
git diff <good-commit>:<path> <bad-commit>:<path>

# Show file at specific commit
git show <commit>:path/to/file.py

Checkout approach:

bash
# Temporarily checkout old version
git checkout <good-commit> path/to/file.py

# Run tests
pytest tests/

# Restore current version
git checkout HEAD path/to/file.py
Strategy 3: Isolate the Problem

Minimal reproduction:

  1. Create minimal test case that reproduces failure
  2. Remove unrelated code
  3. Identify exact line causing issue

Example:

python
# Simplified test
def test_minimal_repro():
    # Reproduce just the failing assertion
    result = function_under_test(input)
    assert result == expected  # This fails
Strategy 4: Check Test Dependencies

Fixture issues:

python
# Check what fixtures provide
def test_debug_fixture(sample_user):
    print(f"Fixture data: {sample_user}")
    assert False  # Force test to show output

Mock issues:

python
# Verify mock is called
@patch('module.function')
def test_with_mock(mock_func):
    mock_func.return_value = "test"
    result = code_that_uses_function()
    print(f"Mock called: {mock_func.called}")
    print(f"Call args: {mock_func.call_args}")

Setup/teardown:

python
# Check state before/after
def test_check_state():
    print(f"Before: {get_current_state()}")
    run_test_code()
    print(f"After: {get_current_state()}")

Common Investigation Commands

Git Commands
bash
# Show commits that changed a file
git log --follow path/to/file.py

# Show commits with specific content
git log -S "function_name" --source --all

# Show commits by author
git log --author="AuthorName" --since="1 week ago"

# Show detailed commit
git show <commit-hash>

# Compare branches
git diff main feature-branch
Test Commands
bash
# Run with maximum verbosity
pytest -vv

# Show print statements
pytest -s

# Stop at first failure
pytest -x

# Show local variables on failure
pytest -l

# Run last failed tests
pytest --lf

# Run tests that failed, then all
pytest --ff

# Collect tests without running
pytest --collect-only

# Show slowest tests
pytest --durations=10
Python Debugging
python
# Add breakpoint
import pdb; pdb.set_trace()

# Or in Python 3.7+
breakpoint()

# Print stack trace
import traceback
traceback.print_stack()

# Inspect object
import pprint
pprint.pprint(vars(obj))

Example Workflows

Example 1: Simple Function Signature Change

User request:

"Tests started failing with TypeError about unexpected keyword argument"

Investigation:

  1. Check error message: TypeError: process() got unexpected keyword argument 'format'
  2. Find function: grep -r "def process" .
  3. Check recent changes: git log -p -S "def process"
  4. Find commit that changed parameter name
  5. Verify: Apply fix and run test

Report:

markdown
## Root Cause: Parameter Renamed

Function `process()` parameter `format` renamed to `output_format` in commit abc123.

**Fix**: Update test call from `process(data, format="json")` to `process(data, output_format="json")`

**Likelihood**: High (99%)
Example 2: Flaky Test Investigation

User request:

"Test passes sometimes but fails randomly"

Investigation:

  1. Run test multiple times: for i in {1..10}; do pytest test.py; done
  2. Check for timing issues, race conditions
  3. Look for shared state between tests
  4. Check for external dependencies (network, filesystem)

Report:

markdown
## Root Cause: Race Condition

Test has race condition in async code. The async operation sometimes completes before assertion, sometimes after.

**Evidence**: Test fails ~30% of the time when run repeatedly.

**Fix**: Add proper await or increase timeout.

**Likelihood**: High (85%)
Example 3: Dependency Update Breaking Tests

User request:

"All tests started failing after pip install"

Investigation:

  1. Check requirements: git diff HEAD~1 requirements.txt
  2. Find updated package: requests 2.28.0 → 2.31.0
  3. Review changelog for breaking changes
  4. Test with old version: pip install requests==2.28.0

Report:

markdown
## Root Cause: Breaking Change in requests 2.31.0

The `requests` library changed response encoding behavior in v2.31.0.

**Evidence**:
- Tests pass with requests==2.28.0
- Tests fail with requests==2.31.0
- Changelog mentions encoding changes

**Fix**: Update test expectations or pin requests version.

**Likelihood**: High (95%)

Tips for Effective Analysis

Start with the obvious:

  • What changed most recently?
  • What does the error message say?
  • What file is the test testing?

Follow the stack trace:

  • Start from the innermost frame
  • Identify which line in your code fails
  • Work backwards to understand why

Look for patterns:

  • Do multiple tests fail the same way?
  • Are failures in related tests?
  • Is there a common dependency?

Use version control:

  • Git history is your friend
  • Use git bisect for complex cases
  • Compare working vs broken states

Verify assumptions:

  • Don't assume—test your hypotheses
  • Try potential fixes
  • Check related code

Document findings:

  • Record what you tried
  • Note what worked and what didn't
  • Build institutional knowledge

Reference

For comprehensive failure patterns and their causes, see failure-patterns.md.

© 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

SKILL.md and 1 other file (references) in skills/regression-root-cause-analyzer of ArabelaTso/Skills-4-SE.

  • SKILL.md
  • references/failure-patterns.md

Open the folder on GitHubat commit 4f38503

Compare with similar skills

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Works with

Questions about Regression Root Cause Analyzer

What does Regression Root Cause Analyzer do?

Locate root causes of failing regression tests by analyzing code changes, error messages, and test dependencies. Regression Root Cause Analyzer is an agent skill from ArabelaTso/Skills-4-SE. Locate root causes of failing regression tests by analyzing code changes, error messages, and test dependencies.

When should I use Regression Root Cause Analyzer?

Regression Root Cause Analyzer fits situations like: regression tests start failing after code changes; investigating test failures in CI/CD; debugging flaky tests; understanding why previously passing tests now fail.

How do I install Regression Root Cause Analyzer in Claude Code?

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

How do I install Regression Root Cause Analyzer in Codex?

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

Can I use Regression Root Cause Analyzer 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 regression-root-cause-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/regression-root-cause-analyzer, .gemini/skills/regression-root-cause-analyzer, .github/skills/regression-root-cause-analyzer and .opencode/skills/regression-root-cause-analyzer in your project.

What does Regression Root Cause Analyzer need to run?

Going by SKILL.md and its folder, Regression Root Cause Analyzer needs the command-line tools its instructions call (git, pytest, pip and npm). Our summary lists: Python 3; Node.js.

Does Regression Root Cause Analyzer access the network?

SKILL.md contains no URLs. Its commands use git, pip and npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Regression Root Cause Analyzer 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 Regression Root Cause Analyzer use?

Regression Root Cause Analyzer 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 Regression Root Cause Analyzer use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Regression Root Cause Analyzer?

Skills that share tags, products or a category with Regression Root Cause Analyzer: TiDB Test Diff Triage (pingcap/tidb, 41k stars), Debugging and Error Recovery (addyosmani/agent-skills, 103k stars), Debug (gnomeria/usbtree, 690 stars) and Investigate (blueberrycongee/termcanvas, 406 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Regression Root Cause Analyzer?

ArabelaTso (a GitHub user) maintains it in ArabelaTso/Skills-4-SE, which has 253 GitHub stars. The repository holds 150 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.