Agent skill

Coverage Enhancer

by ArabelaTso in ArabelaTso/Skills-4-SE

Analyze existing test suites and source code to suggest additional unit tests that improve test coverage.

Apache-2.0Auto-check passedTesting & QA

Install Coverage Enhancer

skills CLI
$ npx skills add ArabelaTso/Skills-4-SE --skill coverage-enhancer -a claude-code

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

GitHub CLI
$ gh skill install ArabelaTso/Skills-4-SE coverage-enhancer --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/coverage-enhancer .claude/skills/coverage-enhancer && 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
coverage-enhancer
GitHub stars
253
Token cost
~4.4k tokens
SKILL.md length
629 words
Files
1
Skills in repo
150
Repo updated
First seen
Licence
Apache-2.0

At a glance

Analyze existing test suites and source code to suggest additional unit tests that improve test coverage.

  • Works in 8 steps: Coverage Gap Analysis → Existing Test Analysis → Test Suggestion Generation → …
  • Working with test files and source code to identify untested code paths
  • SKILL.md covers Core Capabilities, Coverage Analysis Workflow, Coverage Analysis Patterns and Coverage Metrics, plus 2 more sections
  • Calls go, pytest and npm

What it does

Coverage Enhancer is an agent skill from ArabelaTso/Skills-4-SE. Analyze existing test suites and source code to suggest additional unit tests that improve test coverage. Use this skill when working with test files and source code to identify untested code paths, missing edge cases, uncovered branches, untested error conditions, and gaps in test coverage. Supports major testing frameworks (pytest, Jest, JUnit, Go testing, etc.) and generates targeted test suggestions based on coverage analysis.

Its SKILL.md is about 4.4k 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, Test coverage and Test generation. It works with Jest, JUnit and pytest. 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

  • Working with test files and source code to identify untested code paths
  • Missing edge cases
  • Uncovered branches
  • Untested error conditions

Example prompts

  • “/coverage-enhancer”

Requirements

  • Python 3

Workflow steps

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

  1. Coverage Gap Analysis
  2. Existing Test Analysis
  3. Test Suggestion Generation
  4. Analyze Existing Tests
  5. Analyze Source Code
  6. Prioritize Coverage Gaps
  7. Generate Test Suggestions
  8. Suggest Coverage Tool Integration

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:

    • go
    • pytest
    • npm
    • mvn

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

  • Network

    No URLs in SKILL.md. Its commands use 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

Coverage Enhancer loads about 4.4k tokens when it runs. Until then it costs about 113 tokens; SKILL.md has 629 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~113
When it runs · the whole SKILL.md, loaded when a task matches
~4.4k

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). 629 words, ~4,444 tokens.

Download SKILL.mdSave it as .claude/skills/coverage-enhancer/SKILL.md (or your agent's skills folder).
name
coverage-enhancer
description
Analyze existing test suites and source code to suggest additional unit tests that improve test coverage. Use this skill when working with test files and source code to identify untested code paths, missing edge cases, uncovered branches, untested error conditions, and gaps in test coverage. Supports major testing frameworks (pytest, Jest, JUnit, Go testing, etc.) and generates targeted test suggestions based on coverage analysis.

Coverage Enhancer

Analyze existing tests and source code to identify coverage gaps, then suggest specific additional tests to improve overall test coverage and code quality.

Core Capabilities

1. Coverage Gap Analysis

Identify untested areas in source code:

  • Uncovered lines - Code never executed by tests
  • Uncovered branches - Conditional paths not tested
  • Uncovered functions - Methods/functions without tests
  • Missing error handling tests - Exception paths not verified
  • Untested edge cases - Boundary conditions not covered
  • Insufficient scenarios - Limited test diversity
2. Existing Test Analysis

Understand current test coverage by:

  • Parsing existing test files
  • Identifying tested functions and methods
  • Recognizing test patterns and frameworks
  • Detecting coverage tools in use
  • Analyzing test quality and completeness
3. Test Suggestion Generation

Generate specific, actionable test recommendations:

  • Complete test code in the project's framework
  • Clear test names describing what's being tested
  • Setup, execution, and assertion steps
  • Integration with existing test structure
  • Prioritized by coverage impact

Coverage Analysis Workflow

Step 1: Analyze Existing Tests

Read and understand the current test suite:

Identify test framework:

python
# pytest
def test_something():
    assert result == expected

# unittest
class TestSomething(unittest.TestCase):
    def test_method(self):
        self.assertEqual(result, expected)

Map tested functionality:

  • Which functions/methods have tests?
  • What scenarios are covered?
  • What assertions are made?
  • What inputs are tested?

Identify test patterns:

  • Naming conventions
  • Setup/teardown patterns
  • Fixture usage
  • Mock/stub patterns
Step 2: Analyze Source Code

Examine the implementation to find gaps:

Identify code paths:

python
def process(value):
    if value < 0:        # Branch 1
        raise ValueError
    elif value == 0:     # Branch 2
        return None
    else:                # Branch 3
        return value * 2

Find untested branches:

  • If/else conditions not covered
  • Switch/case statements
  • Exception handlers (try/except/finally)
  • Early returns
  • Loop edge cases (zero iterations, one iteration, many)

Identify uncovered functions:

  • Helper functions without tests
  • Private methods (if testing them is valuable)
  • Class methods and properties
  • Static/class methods
Step 3: Prioritize Coverage Gaps

Focus on high-value additions:

Priority 1: Critical paths

  • Error handling and validation
  • Security-sensitive code
  • Data integrity operations
  • Public API methods

Priority 2: Complex logic

  • Conditional logic with multiple branches
  • Loops with edge cases
  • State transitions
  • Algorithm implementations

Priority 3: Completeness

  • Untested helper functions
  • Missing edge cases
  • Property getters/setters
  • Simple utility functions
Step 4: Generate Test Suggestions

Create specific, ready-to-use tests:

Format:

python
# Suggested test for uncovered branch: negative input validation
def test_process_negative_input():
    """Test that negative values raise ValueError."""
    with pytest.raises(ValueError):
        process(-1)

# Reason: This tests the value < 0 branch which is currently uncovered
# Coverage impact: +5 lines, +1 branch

Include:

  1. Test name (descriptive)
  2. Test implementation (complete code)
  3. Explanation of what's being tested
  4. Coverage impact estimate
  5. Integration notes (where to add in test file)
Step 5: Suggest Coverage Tool Integration

Recommend running coverage analysis:

bash
# Python
pytest --cov=mymodule --cov-report=html

# JavaScript
npm test -- --coverage

# Java
mvn test jacoco:report

# Go
go test -coverprofile=coverage.out
go tool cover -html=coverage.out

Coverage Analysis Patterns

Pattern 1: Branch Coverage

Uncovered code:

python
def calculate_discount(price, customer_type):
    if customer_type == "premium":
        return price * 0.8
    elif customer_type == "regular":
        return price * 0.9
    else:
        return price

Existing test:

python
def test_calculate_discount_premium():
    assert calculate_discount(100, "premium") == 80

Suggested additions:

python
def test_calculate_discount_regular():
    """Test discount calculation for regular customers."""
    assert calculate_discount(100, "regular") == 90
    # Coverage: Tests the 'regular' branch

def test_calculate_discount_no_discount():
    """Test that unknown customer types get no discount."""
    assert calculate_discount(100, "guest") == 100
    # Coverage: Tests the else branch

def test_calculate_discount_edge_cases():
    """Test discount calculation with edge case prices."""
    assert calculate_discount(0, "premium") == 0
    assert calculate_discount(0.01, "premium") == 0.008
    # Coverage: Tests edge cases within covered branches
Pattern 2: Exception Path Coverage

Uncovered code:

python
def divide(a, b):
    if b == 0:
        raise ValueError("Cannot divide by zero")
    return a / b

Existing test:

python
def test_divide_normal():
    assert divide(10, 2) == 5

Suggested addition:

python
def test_divide_by_zero():
    """Test that dividing by zero raises ValueError."""
    with pytest.raises(ValueError, match="Cannot divide by zero"):
        divide(10, 0)
    # Coverage: Tests the exception path (b == 0 branch)
    # Impact: +2 lines, +1 branch
Show full SKILL.md (251 more words)Show less
Pattern 3: Loop Coverage

Uncovered code:

python
def find_max(numbers):
    if not numbers:
        return None

    max_val = numbers[0]
    for num in numbers[1:]:
        if num > max_val:
            max_val = num
    return max_val

Existing test:

python
def test_find_max_normal():
    assert find_max([1, 5, 3, 2]) == 5

Suggested additions:

python
def test_find_max_empty():
    """Test that empty list returns None."""
    assert find_max([]) is None
    # Coverage: Tests the 'if not numbers' branch

def test_find_max_single_element():
    """Test with single element (zero loop iterations)."""
    assert find_max([42]) == 42
    # Coverage: Tests loop with zero iterations

def test_find_max_all_equal():
    """Test with all identical elements."""
    assert find_max([5, 5, 5, 5]) == 5
    # Coverage: Tests loop where condition never true

def test_find_max_negative_numbers():
    """Test with negative numbers."""
    assert find_max([-5, -1, -10, -3]) == -1
    # Coverage: Edge case for comparison logic
Pattern 4: Error Handler Coverage

Uncovered code:

python
def load_config(filename):
    try:
        with open(filename) as f:
            return json.load(f)
    except FileNotFoundError:
        return {}
    except json.JSONDecodeError as e:
        raise ValueError(f"Invalid JSON in {filename}: {e}")
    except Exception as e:
        raise RuntimeError(f"Unexpected error loading {filename}: {e}")

Existing test:

python
def test_load_config_success(tmp_path):
    config_file = tmp_path / "config.json"
    config_file.write_text('{"key": "value"}')
    assert load_config(str(config_file)) == {"key": "value"}

Suggested additions:

python
def test_load_config_file_not_found():
    """Test that missing file returns empty dict."""
    assert load_config("nonexistent.json") == {}
    # Coverage: Tests FileNotFoundError exception path

def test_load_config_invalid_json(tmp_path):
    """Test that invalid JSON raises ValueError."""
    config_file = tmp_path / "bad.json"
    config_file.write_text("{invalid json}")

    with pytest.raises(ValueError, match="Invalid JSON"):
        load_config(str(config_file))
    # Coverage: Tests JSONDecodeError exception path

def test_load_config_permission_error(tmp_path):
    """Test that permission errors raise RuntimeError."""
    config_file = tmp_path / "protected.json"
    config_file.write_text('{"key": "value"}')
    config_file.chmod(0o000)

    with pytest.raises(RuntimeError, match="Unexpected error"):
        load_config(str(config_file))
    # Coverage: Tests generic Exception handler
Pattern 5: State Transition Coverage

Uncovered code:

python
class Connection:
    def __init__(self):
        self.state = "closed"

    def connect(self):
        if self.state == "connected":
            raise RuntimeError("Already connected")
        self.state = "connected"

    def disconnect(self):
        if self.state == "closed":
            raise RuntimeError("Not connected")
        self.state = "closed"

Existing test:

python
def test_connection_happy_path():
    conn = Connection()
    conn.connect()
    assert conn.state == "connected"

Suggested additions:

python
def test_connection_double_connect():
    """Test that connecting twice raises error."""
    conn = Connection()
    conn.connect()

    with pytest.raises(RuntimeError, match="Already connected"):
        conn.connect()
    # Coverage: Tests invalid state transition

def test_connection_disconnect_when_not_connected():
    """Test that disconnecting when closed raises error."""
    conn = Connection()

    with pytest.raises(RuntimeError, match="Not connected"):
        conn.disconnect()
    # Coverage: Tests disconnect precondition check

def test_connection_full_lifecycle():
    """Test complete connect-disconnect cycle."""
    conn = Connection()
    assert conn.state == "closed"

    conn.connect()
    assert conn.state == "connected"

    conn.disconnect()
    assert conn.state == "closed"
    # Coverage: Tests all valid state transitions

Coverage Metrics

Line Coverage

Percentage of code lines executed by tests:

Total lines: 100
Covered lines: 75
Coverage: 75%

Target: 80%+ for critical code, 60%+ overall

Branch Coverage

Percentage of conditional branches tested:

python
if condition:    # Branch 1
    do_something()
else:            # Branch 2
    do_other()

# 100% branch coverage requires testing both paths

Target: 70%+ for complex logic

Function Coverage

Percentage of functions with at least one test:

Target: 90%+ for public APIs

Path Coverage

All possible execution paths tested:

python
def complex(a, b, c):
    if a:          # 2 branches
        if b:      # 2 branches
            if c:  # 2 branches
                return "all true"

Total paths: 2³ = 8 paths

Target: Cover critical paths, not necessarily all combinations

Integration with Coverage Tools

Python (pytest + coverage)

Run coverage:

bash
pytest --cov=mymodule --cov-report=term-missing --cov-report=html

Read coverage report:

python
# Look for:
# - Missing lines (shown in report)
# - Uncovered branches (with --cov-branch)
# - Files with low coverage (<80%)

Suggest tests based on missing lines

JavaScript (Jest)

Run coverage:

bash
npm test -- --coverage --verbose

Read coverage output:

javascript
// coverage/lcov-report/index.html shows:
// - Uncovered lines (highlighted in red)
// - Uncovered branches
// - Function coverage
Java (JaCoCo)

Run coverage:

bash
mvn test jacoco:report

Read report:

target/site/jacoco/index.html
Go

Run coverage:

bash
go test -coverprofile=coverage.out ./...
go tool cover -html=coverage.out

Test Suggestion Template

When suggesting tests, use this format:

## Coverage Gap: [Description]

**Location:** [file:line or function name]
**Current Coverage:** [X%]
**Impact:** +[N] lines, +[M] branches

### Suggested Test:

[Complete test code]

**Explanation:**
[What this test covers and why it's important]

**Where to add:**
[In which test file, near which existing test]
Example:
## Coverage Gap: Error handling for invalid input

**Location:** src/validator.py:45-48
**Current Coverage:** 60% (missing exception path)
**Impact:** +3 lines, +1 branch

### Suggested Test:

```python
def test_validate_email_invalid_format():
    """Test that invalid email format raises ValueError."""
    with pytest.raises(ValueError, match="Invalid email format"):
        validate_email("not-an-email")

    # Additional invalid cases
    with pytest.raises(ValueError):
        validate_email("")
    with pytest.raises(ValueError):
        validate_email("@example.com")

Explanation: This test covers the exception path when email validation fails. Currently, only the happy path (valid emails) is tested. This improves branch coverage and ensures proper error messages.

Where to add: In tests/test_validator.py, after test_validate_email_valid


## Best Practices

1. **Start with existing tests** - Always read current tests first to understand patterns
2. **Match the style** - Use same framework, naming, and structure as existing tests
3. **Focus on value** - Prioritize high-impact coverage gaps over achieving 100%
4. **Test behavior, not implementation** - Focus on what the code does, not how
5. **Keep tests isolated** - Each test should be independent
6. **Use descriptive names** - Test names should explain what's being verified
7. **Add explanations** - Comment why each test is needed for coverage
8. **Suggest coverage tools** - Help users measure and track coverage
9. **Consider mutation testing** - Suggest tests that would catch actual bugs
10. **Balance coverage and maintainability** - Don't over-test trivial code

## Common Coverage Gaps

### Gap 1: Error Cases Not Tested

```python
# Often only happy path is tested
def parse_int(s):
    return int(s)  # ValueError not tested

# Suggest:
def test_parse_int_invalid():
    with pytest.raises(ValueError):
        parse_int("not a number")
Gap 2: Edge Cases Missing
python
# Common values tested, boundaries ignored
def clamp(value, min_val, max_val):
    return max(min_val, min(max_val, value))

# Need tests for:
# - value == min_val
# - value == max_val
# - value < min_val
# - value > max_val
Gap 3: Else Branches Untested
python
if condition:
    # Tested
    do_something()
else:
    # Never tested!
    do_other()
Gap 4: Loop Edge Cases
python
for item in collection:
    process(item)

# Need tests for:
# - Empty collection
# - Single item
# - Many items
Gap 5: Cleanup/Finally Not Tested
python
try:
    risky_operation()
finally:
    cleanup()  # Often not verified

# Suggest test that verifies cleanup happens

Language-Specific Patterns

For language-specific coverage patterns and testing approaches:

Example: Complete Coverage Analysis

Source code:

python
def calculate_grade(score):
    """Calculate letter grade from numeric score."""
    if score < 0 or score > 100:
        raise ValueError("Score must be between 0 and 100")

    if score >= 90:
        return 'A'
    elif score >= 80:
        return 'B'
    elif score >= 70:
        return 'C'
    elif score >= 60:
        return 'D'
    else:
        return 'F'

Existing tests:

python
def test_calculate_grade_a():
    assert calculate_grade(95) == 'A'

def test_calculate_grade_c():
    assert calculate_grade(75) == 'C'

Coverage analysis:

  • Line coverage: 60% (6/10 lines)
  • Branch coverage: 40% (2/5 grade ranges, 0/2 error checks)

Suggested tests:

python
def test_calculate_grade_invalid_negative():
    """Test that negative scores raise ValueError."""
    with pytest.raises(ValueError, match="between 0 and 100"):
        calculate_grade(-1)
    # Coverage: +2 lines (score < 0 branch)

def test_calculate_grade_invalid_too_high():
    """Test that scores above 100 raise ValueError."""
    with pytest.raises(ValueError, match="between 0 and 100"):
        calculate_grade(101)
    # Coverage: +0 lines (same as above, but tests second condition)

def test_calculate_grade_b():
    """Test B grade threshold."""
    assert calculate_grade(85) == 'B'
    # Coverage: +1 line (score >= 80 branch)

def test_calculate_grade_d():
    """Test D grade threshold."""
    assert calculate_grade(65) == 'D'
    # Coverage: +1 line (score >= 60 branch)

def test_calculate_grade_f():
    """Test F grade for failing scores."""
    assert calculate_grade(45) == 'F'
    # Coverage: +1 line (else branch)

def test_calculate_grade_boundaries():
    """Test exact boundary values."""
    assert calculate_grade(90) == 'A'  # Exact boundary
    assert calculate_grade(89) == 'B'  # Just below
    assert calculate_grade(80) == 'B'  # Exact boundary
    assert calculate_grade(79) == 'C'  # Just below
    assert calculate_grade(70) == 'C'  # Exact boundary
    assert calculate_grade(60) == 'D'  # Exact boundary
    assert calculate_grade(0) == 'F'   # Lower bound
    assert calculate_grade(100) == 'A' # Upper bound
    # Coverage: Ensures all boundaries work correctly

Result: 100% line coverage, 100% branch coverage

© 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/coverage-enhancer of ArabelaTso/Skills-4-SE.

Open the folder on GitHubat commit 4f38503

Compare with similar skills

Coverage Enhancer 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.

Coverage Enhancer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Coverage Enhancer this skillArabelaTso/Skills-4-SE253—~4.4kAutomated safety check: PassApache-2.0
TDD Guidealirezarezvani/claude-skills28k—~3.4kAutomated safety check: PassMIT
TDD GuideLeoYeAI/openclaw-master-skills2.2k—~1.4kAutomated safety check: PassMIT
Code Testing Agentmicrosoft/testfx1k—~2.7kAutomated safety check: PassMIT
Test Taggingmicrosoft/testfx1k—~4.3kAutomated safety check: PassMIT
TDD Guideborghei/Claude-Skills881—~1.7kAutomated safety check: PassMIT

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Works with

Categories

Questions about Coverage Enhancer

What does Coverage Enhancer do?

Analyze existing test suites and source code to suggest additional unit tests that improve test coverage. Coverage Enhancer is an agent skill from ArabelaTso/Skills-4-SE. Analyze existing test suites and source code to suggest additional unit tests that improve test coverage.

When should I use Coverage Enhancer?

Coverage Enhancer fits situations like: working with test files and source code to identify untested code paths; missing edge cases; uncovered branches; untested error conditions.

How do I install Coverage Enhancer in Claude Code?

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

How do I install Coverage Enhancer in Codex?

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

Can I use Coverage Enhancer 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 coverage-enhancer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/coverage-enhancer, .gemini/skills/coverage-enhancer, .github/skills/coverage-enhancer and .opencode/skills/coverage-enhancer in your project.

What does Coverage Enhancer need to run?

Going by SKILL.md and its folder, Coverage Enhancer needs the command-line tools its instructions call (go, pytest, npm and mvn). Our summary lists: Python 3.

Does Coverage Enhancer access the network?

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

Is Coverage Enhancer 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 Coverage Enhancer use?

Coverage Enhancer 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 Coverage Enhancer use?

About 4.4k tokens (SKILL.md is roughly 18k 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 Coverage Enhancer?

Skills that share tags, products or a category with Coverage Enhancer: TDD Guide (alirezarezvani/claude-skills, 28k stars), TDD Guide (LeoYeAI/openclaw-master-skills, 2.2k stars), Code Testing Agent (microsoft/testfx, 1k stars) and Test Tagging (microsoft/testfx, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Coverage Enhancer?

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.