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test-review

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Table of Contents

Test Review Workflow

Evaluate and improve test suites with TDD/BDD rigor.

Quick Start

/test-review

Verification: Run pytest -v to verify tests pass.

When To Use

  • Reviewing test suite quality
  • Analyzing coverage gaps
  • Before major releases
  • After test failures
  • Planning test improvements

When NOT To Use

  • Writing new tests - use parseltongue:python-testing
  • Updating existing tests - use sanctum:test-updates

Required TodoWrite Items

  1. test-review:languages-detected
  2. test-review:coverage-inventoried
  3. test-review:scenario-quality
  4. test-review:gap-remediation
  5. test-review:evidence-logged

Progressive Loading

Load modules as needed based on review depth:

  • Basic review: Core workflow (this file)
  • Framework detection: Load modules/framework-detection.md
  • Coverage analysis: Load modules/coverage-analysis.md
  • Quality assessment: Load modules/scenario-quality.md
  • Remediation planning: Load modules/remediation-planning.md

Workflow

Step 1: Detect Languages (test-review:languages-detected)

Identify testing frameworks and version constraints. → See: modules/framework-detection.md

Quick check:

find . -maxdepth 2 -name "Cargo.toml" -o -name "pyproject.toml" -o -name "package.json" -o -name "go.mod"

Verification: Run the command with --help flag to verify availability.

Step 2: Inventory Coverage (test-review:coverage-inventoried)

Run coverage tools and identify gaps. → See: modules/coverage-analysis.md

Quick check:

git diff --name-only | rg 'tests|spec|feature'

Verification: Run pytest -v to verify tests pass.

Step 3: Assess Scenario Quality (test-review:scenario-quality)

Evaluate test quality using BDD patterns and assertion checks. → See: modules/scenario-quality.md

Focus on:

  • Given/When/Then clarity
  • Assertion specificity
  • Anti-patterns (dead waits, mocking internals, repeated boilerplate)

Step 4: Plan Remediation (test-review:gap-remediation)

Create concrete improvement plan with owners and dates. → See: modules/remediation-planning.md

Step 5: Log Evidence (test-review:evidence-logged)

Record executed commands, outputs, and recommendations. → See: imbue:evidence-logging

Test Quality Checklist (Condensed)

  • Clear test structure (Arrange-Act-Assert)
  • Critical paths covered (auth, validation, errors)
  • Specific assertions with context
  • No flaky tests (dead waits, order dependencies)
  • Reusable fixtures/factories

Output Format

## Summary
[Brief assessment]

## Framework Detection
- Languages: [list] | Frameworks: [list] | Versions: [constraints]

## Coverage Analysis
- Overall: X% | Critical: X% | Gaps: [list]

## Quality Issues
[Q1] [Issue] - Location - Fix

## Remediation Plan
1. [Action] - Owner - Date

## Recommendation
Approve / Approve with actions / Block

Verification: Run the command with --help flag to verify availability.

Integration Notes

  • Use imbue:evidence-logging for reproducible evidence capture
  • Reference imbue:diff-analysis for risk assessment
  • Format output using imbue:structured-output patterns

Exit Criteria

  • Frameworks detected and documented
  • Coverage analyzed and gaps identified
  • Scenario quality assessed
  • Remediation plan created with owners and dates
  • Evidence logged with citations

Troubleshooting

Common Issues

Tests not discovered Ensure test files match pattern test_*.py or *_test.py. Run pytest --collect-only to verify.

Import errors Check that the module being tested is in PYTHONPATH or install with pip install -e .

Async tests failing Install pytest-asyncio and decorate test functions with @pytest.mark.asyncio

Source

git clone https://github.com/athola/claude-night-market/blob/master/plugins/pensive/skills/test-review/SKILL.mdView on GitHub

Overview

Test Review evaluates test suites for coverage gaps and quality, guiding audits, remediation planning, and evidence logging. It aligns with TDD/BDD practices and uses a progressive loading workflow to scope analysis. Do not use for writing new tests or updating existing tests, per the documented exclusions.

How This Skill Works

The workflow starts by identifying test languages/frameworks (test-review:languages-detected), then inventories coverage (test-review:coverage-inventoried), and finally assesses scenario quality (test-review:scenario-quality) to plan remediation (test-review:gap-remediation) and log evidence (test-review:evidence-logged). Modules are loaded progressively (framework-detection, coverage-analysis, scenario-quality, remediation-planning, content-assertion-quality) to control depth.

When to Use It

  • Reviewing test suite quality
  • Analyzing coverage gaps
  • Before major releases
  • After test failures
  • Planning test improvements

Quick Start

  1. Step 1: Run /test-review to initialize the workflow.
  2. Step 2: Verify test execution with pytest -v.
  3. Step 3: Progress through Step 1-5: languages-detected, coverage-inventoried, scenario-quality, gap-remediation, evidence-logged.

Best Practices

  • Start with languages/frameworks detection to tailor analysis.
  • Inventory coverage before proposing remediation.
  • Evaluate Given/When/Then clarity and assertion specificity.
  • Log evidence and preserve artifacts for traceability.
  • Use progressive loading to manage review depth and scope.

Example Use Cases

  • Audit a Python pytest suite to identify API coverage gaps and flaky tests.
  • Assess feature scenarios for Given/When/Then clarity and replace vague steps.
  • Plan remediation for missing test cases and align with gap-finder outputs.
  • Leverage coverage-analyzer and scenario-evaluator to quantify quality deficits.
  • Conduct pre-release reviews to ensure coverage improvements prior to release.

Frequently Asked Questions

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