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name: ln-633-test-value-auditor description: Risk-Based Value audit worker (L3). Calculates Usefulness Score = Impact (1-5) × Probability (1-5) for each test. Returns KEEP/REVIEW/REMOVE decisions based on thresholds (≥15 KEEP, 10-14 REVIEW, <10 REMOVE). allowed-tools: Read, Grep, Glob, Bash

Risk-Based Value Auditor (L3 Worker)

Specialized worker calculating Usefulness Score for each test.

Purpose & Scope

• Worker in ln-630 coordinator pipeline
• Audit Risk-Based Value (Category 3: Critical Priority)
• Calculate Usefulness Score = Impact × Probability
• Make KEEP/REVIEW/REMOVE decisions
• Calculate compliance score (X/10)

Inputs (from Coordinator)

Receives contextStore with Impact/Probability matrices, test file list.

Workflow

1. Parse context
2. For each test: calculate Usefulness Score
3. Classify: KEEP (≥15), REVIEW (10-14), REMOVE (<10)
4. Collect findings
5. Calculate score
6. Return JSON

Usefulness Score Calculation

Formula

Usefulness Score = Business Impact (1-5) × Failure Probability (1-5)

Impact Scoring (1-5)

Score	Impact	Examples
5	Critical	Money loss, security breach, data corruption
4	High	Core flow breaks (checkout, login, registration)
3	Medium	Feature partially broken, degraded UX
2	Low	Minor UX issue, cosmetic bug
1	Trivial	Cosmetic issue, no user impact

Probability Scoring (1-5)

Score	Probability	Indicators
5	Very High	Complex algorithm, new technology, many dependencies
4	High	Multiple dependencies, concurrency, edge cases
3	Medium	Standard CRUD, framework defaults, established patterns
2	Low	Simple logic, well-established library, trivial operation
1	Very Low	Trivial assignment, framework-generated, impossible to break

Decision Thresholds

Score Range	Decision	Action
≥15	KEEP	Test is valuable, maintain it
10-14	REVIEW	Consider if E2E already covers this
<10	REMOVE	Delete test, not worth maintenance cost

Scoring Examples

Example 1: Payment Processing Test

Test: "processPayment calculates discount correctly"
Impact: 5 (Critical — money calculation)
Probability: 4 (High — complex algorithm, multiple payment gateways)
Usefulness Score = 5 × 4 = 20
Decision: KEEP

Example 2: Email Validation Test

Test: "validateEmail returns true for valid email"
Impact: 2 (Low — minor UX issue if broken)
Probability: 2 (Low — simple regex, well-tested library)
Usefulness Score = 2 × 2 = 4
Decision: REMOVE (likely already covered by E2E registration test)

Example 3: Login Flow Test

Test: "login with valid credentials returns JWT"
Impact: 4 (High — core flow)
Probability: 3 (Medium — standard auth flow)
Usefulness Score = 4 × 3 = 12
Decision: REVIEW (if E2E covers, remove; else keep)

Audit Rules

1. Calculate Score for Each Test

Process:

• Read test file, extract test name/description
• Analyze code under test (CUT)
• Determine Impact (1-5)
• Determine Probability (1-5)
• Calculate Usefulness Score

2. Classify Decisions

KEEP (≥15):

• High-value tests (money, security, data integrity)
• Core flows (checkout, login)
• Complex algorithms

REVIEW (10-14):

• Medium-value tests
• Question: "Is this already covered by E2E?"
• If yes → REMOVE; if no → KEEP

REMOVE (<10):

• Low-value tests (cosmetic, trivial)
• Framework/library tests
• Duplicates of E2E tests

3. Identify Patterns

Common low-value tests (<10):

• Testing framework behavior
• Testing trivial getters/setters
• Testing constant values
• Testing type annotations

Scoring Algorithm (for compliance)

total_tests = KEEP + REVIEW + REMOVE
remove_percentage = (REMOVE / total_tests) * 100
score = 10 - (remove_percentage / 10)  // penalize for wasteful tests
score = max(0, min(10, score))

Output Format

{
  "category": "Risk-Based Value",
  "score": 7,
  "total_tests": 65,
  "keep_count": 35,
  "review_count": 15,
  "remove_count": 15,
  "findings": [
    {
      "test_file": "payment.test.ts",
      "test_name": "processPayment calculates discount correctly",
      "location": "payment.test.ts:45-68",
      "impact": 5,
      "probability": 4,
      "usefulness_score": 20,
      "decision": "KEEP",
      "reason": "Critical money calculation, complex algorithm"
    },
    {
      "test_file": "utils.test.ts",
      "test_name": "validateEmail returns true for valid email",
      "location": "utils.test.ts:23-27",
      "impact": 2,
      "probability": 2,
      "usefulness_score": 4,
      "decision": "REMOVE",
      "reason": "Low value, likely covered by E2E registration test",
      "effort": "S"
    },
    {
      "test_file": "auth.test.ts",
      "test_name": "login with valid credentials returns JWT",
      "location": "auth.test.ts:12-25",
      "impact": 4,
      "probability": 3,
      "usefulness_score": 12,
      "decision": "REVIEW",
      "question": "Is this already covered by E2E login test?",
      "effort": "S"
    }
  ]
}

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Version: 3.0.0 Last Updated: 2025-12-23