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Test Coverage Analyzer Skill · a5c-ai | DecimalAI

a5c-ai/test-coverage-analyzer

SkillScore82Maintained

Analyze test coverage and identify gaps before migration to ensure adequate safety nets

Testingby a5c-ai

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

QA & Test Engineering pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/a5c-ai-test-coverage-analyzer/SKILL.md

decimalai skills pull a5c-ai-test-coverage-analyzer --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/a5c-ai-test-coverage-analyzer/SKILL.md https://app.decimal.ai/s/a5c-ai-test-coverage-analyzer/SKILL.md

Raw file: /s/a5c-ai-test-coverage-analyzer/SKILL.md ↗ · machine-readable summary at /s/a5c-ai-test-coverage-analyzer.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

Runs

167

all versions · 30d

Eval pass

100%

global

Used when offered

100%

used / offered · all versions

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 56d ago

Yes — +5% lift · at higher cost+43% tokens0% turns82% of whole cases pass with skill (18/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-05	✗→✓	▲ Improved	47%	0%
case-04	✓→✓	＝ Same ✓	29%	0%
case-06	✓→✓	＝ Same ✓	50%	0%
case-08	✓→✓	＝ Same ✓	99%	0%
case-09	✓→✓	＝ Same ✓	65%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/31/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

a5c-ai / babysitter

library/specializations/code-migration-modernization/skills/test-coverage-analyzer/SKILL.md

View on GitHub ↗

License MITImported 7/31/2026Version v1

Skill contents

SKILL.md

Test Coverage Analyzer Skill

Analyzes test coverage comprehensively to identify gaps and ensure adequate test safety nets before undertaking migration efforts.

Purpose

Enable comprehensive test coverage analysis for:

Pre-migration coverage assessment
Critical path coverage verification
Coverage gap identification
Test strategy planning
Regression risk assessment

Capabilities

1. Line/Branch/Path Coverage Measurement

Calculate line coverage percentages
Measure branch coverage
Analyze path coverage
Track condition coverage

2. Coverage Gap Identification

Find untested code paths
Identify missing edge cases
Detect uncovered error handlers
Map coverage blind spots

3. Critical Path Coverage Analysis

Identify business-critical paths
Prioritize coverage by importance
Map risk vs coverage
Generate focused test recommendations

4. Integration Test Coverage Mapping

Track integration point coverage
Map API endpoint testing
Assess database operation coverage
Verify external service testing

5. Coverage Trend Analysis

Track coverage over time
Identify coverage regression
Monitor improvement progress
Generate trend reports

Tool Integrations

| Tool | Language | Integration Method | |------|----------|-------------------| | Istanbul/nyc | JavaScript/TypeScript | CLI | | JaCoCo | Java | CLI / Maven/Gradle | | Cobertura | Java/Python | CLI | | Coverage.py | Python | CLI | | SimpleCov | Ruby | CLI | | go test -cover | Go | CLI | | dotCover | .NET | CLI |

Output Schema

json
{
  "analysisId": "string",
  "timestamp": "ISO8601",
  "coverage": {
    "line": {
      "percentage": "number",
      "covered": "number",
      "total": "number"
    },
    "branch": {
      "percentage": "number",
      "covered": "number",
      "total": "number"
    },
    "function": {
      "percentage": "number",
      "covered": "number",
      "total": "number"
    }
  },
  "gaps": [
    {
      "file": "string",
      "uncoveredLines": ["number"],
      "uncoveredBranches": ["string"],
      "criticality": "high|medium|low",
      "recommendation": "string"
    }
  ],
  "criticalPaths": {
    "covered": "number",
    "total": "number",
    "uncoveredPaths": []
  }
}

Integration with Migration Processes

migration-testing-strategy: Coverage baseline establishment
code-refactoring: Pre-refactoring safety assessment
framework-upgrade: Regression protection verification

Related Skills

characterization-test-generator: Generate tests for gaps
static-code-analyzer: Combined quality analysis

Related Agents

migration-testing-strategist: Uses for test planning
regression-detector: Uses for regression prevention

Illustrative Want to see what a5c-ai/test-coverage-analyzer would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Latest benchmark · publisher runVerified

8/1/2026, 02:30 UTC · 22 cases

Lift

+5%

82% vs 77%

Agent turns

1.0 vs 1.0

Tokens

+43%

2,371.73 vs 1,660.36

fail → pass · 1pass → pass · 17fail → fail · 4

Per-case results (22)

Case	Status	Duration (ms)			Turns			Tokens			Tool calls
Case	Status	Without	With	Δ	Without	With	Δ	Without	With	Δ	Without	With	Δ
case-01 We are planning to migrate our Python billing service to a new framework. Before we start, I need you to run a coverage check using Coverage.py. Please output a JSON object containing a unique analysis identifier, the current timestamp, and the overall line, branch, and function coverage numbers (showing percentage, covered, and total). Also include an array of gaps detailing the specific files, missing lines and branches, how critical they are, and suggestions to fix them, plus a summary of covered versus total critical paths.	fail→fail	8,546	11,027	+29%	1	1	0%	1,785	3,155	+77%	0	0	—
case-02 I need to assess the regression risk for our TypeScript frontend before a major refactor. Run nyc to measure our current test safety net. Give me the results as a JSON payload. It should have an analysisId and timestamp, a coverage section breaking down line, branch, and function stats (percentage, covered amount, total amount). I also need a list of gaps showing the file, uncovered lines and branches, criticality level, and a recommendation, along with an object showing total, covered, and uncovered critical paths.	fail→fail	6,524	9,418	+44%	1	1	0%	1,407	2,862	+103%	0	0	—
case-03 Our Java payment gateway needs a thorough test coverage review via JaCoCo to find untested error handlers and missing edge cases. Please provide the analysis in JSON format. The response must include a timestamp and analysis ID, detailed coverage metrics for lines, branches, and functions (each with percentage, covered, and total counts). Furthermore, provide an array of coverage gaps that lists the file, specific uncovered lines and branches, the criticality, and a suggested fix, as well as a section detailing the covered and total critical paths including any uncovered ones.	fail→fail	12,604	11,559	-8%	1	1	0%	2,593	3,100	+20%	0	0	—
case-04 We have a legacy Ruby on Rails application. What standard CLI tool should we integrate to measure our test coverage before upgrading the framework?	pass→pass	8,884	7,424	-16%	1	1	0%	1,503	1,933	+29%	0	0	—
case-05 We are migrating a Golang microservice to a new cluster. Which built-in CLI command should we use to assess our current branch and line coverage?	fail→pass	6,893	6,037	-12%	1	1	0%	1,166	1,712	+47%	0	0	—
case-06 Our C# .NET Core backend needs a coverage assessment. What standard CLI tool should we use to map our coverage blind spots?	pass→pass	9,019	9,055	+0%	1	1	0%	1,503	2,247	+50%	0	0	—
case-07 We have a legacy system with both Java and Python components. Is there a single CLI tool we can use for both to calculate line coverage percentages?	fail→fail	12,148	8,684	-29%	1	1	0%	2,103	2,166	+3%	0	0	—
case-08 We are using Jest for our React project. We want to collect coverage. Should we install nyc to get coverage reports?	pass→pass	6,760	8,827	+31%	1	1	0%	1,165	2,316	+99%	0	0	—
case-09 We are using pytest for our Python backend. Does pytest natively calculate branch coverage on its own without any plugins?	pass→pass	6,142	7,643	+24%	1	1	0%	1,054	1,735	+65%	0	0	—
case-10 We are using JaCoCo in our Maven project. We want to fail the build if coverage is below 80%. Do we configure this in the maven-surefire-plugin?	pass→pass	7,864	8,551	+9%	1	1	0%	1,734	2,493	+44%	0	0	—
case-11 We are setting up SonarQube for our Java project. Does SonarQube run the unit tests and calculate the coverage percentages itself?	pass→pass	8,940	10,893	+22%	1	1	0%	1,303	2,705	+108%	0	0	—
case-12 We are using dotnet test for our C# project. Do we need to buy a commercial tool like dotCover to get code coverage metrics in our CI pipeline?	pass→pass	11,838	11,237	-5%	1	1	0%	2,093	2,629	+26%	0	0	—
case-13 We are checking the test safety net of our Express.js API. What standard CLI tool should we integrate to measure our test coverage before upgrading the framework?	pass→pass	7,430	6,685	-10%	1	1	0%	1,326	1,866	+41%	0	0	—
case-14 We've been running coverage checks on our Ruby app for a month. How do we configure our coverage tool to fail the build if coverage drops below 90%?	pass→pass	10,400	11,526	+11%	1	1	0%	1,895	2,760	+46%	0	0	—
case-15 Our Java application has a lot of try-catch blocks. How do we configure our coverage tool's Maven plugin to fail the build if branch coverage falls below 80%?	pass→pass	10,684	7,764	-27%	1	1	0%	2,179	2,155	-1%	0	0	—
case-16 We have limited time to write tests for our Python billing system before the migration. How do we configure our coverage tool to exit with a non-zero status if total coverage is below 85%?	pass→pass	7,063	9,214	+30%	1	1	0%	1,361	2,376	+75%	0	0	—
case-17 We are about to start moving our monolithic Node.js app to microservices. How do we configure our test runner's package.json to enforce a global branch coverage threshold of 80%?	pass→pass	9,254	10,229	+11%	1	1	0%	1,848	2,785	+51%	0	0	—
case-18 We are upgrading our Angular frontend from version 12 to 15. How do we configure the CLI to generate a coverage report when running tests?	pass→pass	8,995	9,161	+2%	1	1	0%	1,994	2,473	+24%	0	0	—
case-19 We are rewriting the core calculation engine of our Go service to be more efficient. How do we output a coverage profile to a file named 'coverage.out'?	pass→pass	7,895	6,161	-22%	1	1	0%	1,405	1,769	+26%	0	0	—
case-20 We need to automatically generate unit tests for our legacy Python codebase to increase coverage. What standard open-source tool can we use to automatically generate these tests?	pass→pass	11,299	10,118	-10%	1	1	0%	1,856	2,493	+34%	0	0	—
case-21 We want to analyze our Java codebase for high cyclomatic complexity and code smells before checking coverage. What standard static analysis Maven plugin should we use?	pass→pass	9,057	9,078	+0%	1	1	0%	1,714	2,401	+40%	0	0	—
case-22 We are migrating our AWS infrastructure and need to test our Terraform configurations. What standard open-source static analysis tool should we use to scan our Terraform code for security misconfigurations?	pass→pass	9,050	10,985	+21%	1	1	0%	1,541	2,047	+33%	0	0	—

These cases were also screened by the skill’s intent / safety pass.See the Trust review ↗Reproduce this benchmark in Colab ↗

How this skill was measured

DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +5 percentage points is the difference between those two pass rates over the 22 comparable cases.

Model measured: gemini-3.6-flash
Graded by: gemini-3.6-flash
Grading method: judged
Verification: verified
Pass rate without the skill: 77.3%
Pass rate with the skill: 81.8%
Cases attempted: 22
Cases counted toward lift: 22
Cases that regressed: 0
Skill version measured: v1
Run completed: 8/1/2026, 02:30 UTC

Measured example — same prompt, with vs. without the skill · from the benchmark run · case case-05

Prompt

We are migrating a Golang microservice to a new cluster. Which built-in CLI command should we use to assess our current branch and line coverage?

Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.

Show both answers

SkillScore blends 4 signals2 of 4 complete

BenchmarkPass rate WITH skill on a verified run82

Live evalNeeds ≥10 evaluated traces in 30 days

AI ratingNeeds ≥10 rated traces

AdoptionBreadth of real use across orgs82

Efficiency · separate axis (at equal correctness)+0% turns+43% tokens

Shown for transparency; not credited unless a verified run shows no correctness regression.

Backed by 2 of 4 signals — each added signal makes the score more robust.

Verified on gemini-3.6-flash · re-tested 55 days ago

Other measured skills in the registry, with their headline benchmark lift.