test-updates

Table of Contents

• [Overview](#overview)
• [Core Philosophy](#core-philosophy)
• [What It Is](#what-it-is)
• [Quick Start](#quick-start)
• [Quick Checklist for First Time Use](#quick-checklist-for-first-time-use)
• [detailed Test Update](#detailed-test-update)
• [Targeted Test Updates](#targeted-test-updates)
• [TDD for New Features](#tdd-for-new-features)
• [Using the Scripts Directly](#using-the-scripts-directly)
• [When to Use It](#when-to-use-it)
• [Workflow Integration](#workflow-integration)
• [Phase 1: Discovery](#phase-1:-discovery)
• [Phase 2: Strategy](#phase-2:-strategy)
• [Phase 3: Implementation](#phase-3:-implementation)
• [Phase 4: Validation](#phase-4:-validation)
• [Quality Assurance](#quality-assurance)
• [Examples](#examples)
• [BDD-Style Test Generation](#bdd-style-test-generation)
• [Test Enhancement](#test-enhancement)
• [Integration with Existing Skills](#integration-with-existing-skills)
• [Success Metrics](#success-metrics)
• [Troubleshooting FAQ](#troubleshooting-faq)
• [Common Issues](#common-issues)
• [Performance Tips](#performance-tips)
• [Getting Help](#getting-help)

Test Updates and Maintenance

Overview

detailed test management system that applies TDD/BDD principles to maintain, generate, and enhance tests across codebases. This skill practices what it preaches - it uses TDD principles for its own development and serves as a living example of best practices.

Core Philosophy

• RED-GREEN-REFACTOR: Strict adherence to TDD cycle
• Behavior-First: BDD patterns that describe what code should do
• Invariant-Encoding: Tests guard design decisions, not just behavior
• Meta Dogfooding: The skill's own tests demonstrate the principles it teaches
• Quality Gates: detailed validation before considering tests complete

What It Is

A modular test management system that:

• Discovers what needs testing or updating
• Generates tests following TDD principles
• Enhances existing tests with BDD patterns
• Validate test quality through multiple lenses

Quick Start

Quick Checklist for First Time Use

• [ ] validate pytest is installed (pip install pytest)
• [ ] Have your source code in src/ or similar directory
• [ ] Create a tests/ directory if it doesn't exist
• [ ] Run Skill(sanctum:git-workspace-review) first to understand changes
• [ ] Start with Skill(test-updates) --target <specific-module> for focused updates

detailed Test Update

# Run full test update workflow
Skill(test-updates)

Verification: Run pytest -v to verify tests pass.

Targeted Test Updates

# Update tests for specific paths
Skill(test-updates) --target src/sanctum/agents
Skill(test-updates) --target tests/test_commit_messages.py

Verification: Run pytest -v to verify tests pass.

TDD for New Features

# Apply TDD to new code
Skill(test-updates) --tdd-only --target new_feature.py

Verification: Run pytest -v to verify tests pass.

Using the Scripts Directly

Human-Readable Output:

# Analyze test coverage gaps
python plugins/sanctum/scripts/test_analyzer.py --scan src/

# Generate test scaffolding
python plugins/sanctum/scripts/test_generator.py \
    --source src/my_module.py --style pytest_bdd

# Check test quality
python plugins/sanctum/scripts/quality_checker.py \
    --validate tests/test_my_module.py

Verification: Run pytest -v to verify tests pass.

Programmatic Output (for Claude Code):

# Get JSON output for programmatic parsing - test_analyzer
python plugins/sanctum/scripts/test_analyzer.py \
    --scan src/ --output-json

# Returns:
# {
#   "success": true,
#   "data": {
#     "source_files": ["src/module.py", ...],
#     "test_files": ["tests/test_module.py", ...],
#     "uncovered_files": ["module_without_tests", ...],
#     "coverage_gaps": [{"file": "...", "reason": "..."}]
#   }
# }

# Get JSON output - test_generator
python plugins/sanctum/scripts/test_generator.py \
    --source src/my_module.py --output-json

# Returns:
# {
#   "success": true,
#   "data": {
#     "test_file": "path/to/test_my_module.py",
#     "source_file": "src/my_module.py",
#     "style": "pytest_bdd",
#     "fixtures_included": true,
#     "edge_cases_included": true,
#     "error_cases_included": true
#   }
# }

# Get JSON output - quality_checker
python plugins/sanctum/scripts/quality_checker.py \
    --validate tests/test_my_module.py --output-json

# Returns:
# {
#   "success": true,
#   "data": {
#     "static_analysis": {...},
#     "dynamic_validation": {...},
#     "metrics": {...},
#     "quality_score": 85,
#     "quality_level": "QualityLevel.GOOD",
#     "recommendations": [...]
#   }
# }

Verification: Run pytest -v to verify tests pass.

When To Use It

Use this skill when you need to:

• Update tests after code changes
• Generate tests for new features
• Improve existing test quality
• validate detailed test coverage

Perfect for:

• Pre-commit test validation
• CI/CD pipeline integration
• Refactoring with test safety
• Onboarding new developers

When NOT To Use

• Auditing

test suites - use pensive:test-review

• Writing production code
• focus on implementation first
• Auditing

test suites - use pensive:test-review

• Writing production code
• focus on implementation first

Workflow Integration

Phase 1: Discovery

1. Scan codebase for test gaps
2. Analyze recent changes
3. Identify broken or outdated tests

See modules/test-discovery.md for detection patterns.

Phase 2: Strategy

1. Choose appropriate BDD style (see modules/bdd-patterns.md)
2. Plan test structure
3. Define quality criteria
4. Identify design invariants to encode as tests

Phase 2.5: Invariant-Encoding Tests

Before writing behavioral tests, identify the design invariants that the code relies on and write tests that would break if those invariants were violated.

What to encode:

• Module boundary constraints (A never imports from B)
• Data flow direction (events flow publisher-to-subscriber,

never the reverse)

• API contract shapes (public interfaces don't change

without versioning)

• Data structure choices (if a map was chosen over a list,

test the properties that justify that choice)

• Error handling strategies (fail-fast boundaries, recovery

zones)

Example:

def test_plugins_never_import_from_other_plugins():
    """Encode the invariant: plugins are independent modules.

    If this test breaks, someone is coupling plugins
    directly. Present the 3 options to a human:
    1. Preserve: revert the import, keep plugins independent
    2. Layer: add a shared interface in leyline instead
    3. Revise: merge the plugins (requires ADR)
    """
    for plugin_dir in plugin_dirs:
        imports = extract_imports(plugin_dir)
        for imp in imports:
            assert not imp.startswith("plugins."), (
                f"{plugin_dir} imports {imp} — "
                f"violates plugin independence invariant"
            )

Why this matters: Tests that encode invariants are load-bearing. When an agent later encounters a feature that clashes with the invariant, the test failure forces a conscious decision rather than a silent drift. Without these tests, bad invariant decisions compound until the codebase is unsalvageable.

When updating existing tests:

If an invariant-encoding test needs to change, do NOT silently update the assertion. Flag it for human review with the three options: preserve the invariant, layer on top, or revise the invariant. This is a judgment call that requires human wisdom — models default to the "average" of training data and get these wrong far too often.

Phase 3: Implementation

1. Write failing tests (RED) - see modules/tdd-workflow.md
2. Implement minimal passing code (GREEN)
3. Refactor for clarity (REFACTOR)

See modules/test-generation.md for generation templates.

Phase 4: Validation

1. Static analysis and linting

2