Calculate Priority Score

Calculate numeric priority score and category for issues based on multiple factors.

When to Use

• Bug prioritization
• Security vulnerability risk assessment
• Task ordering
• Resource allocation decisions

Instructions

Step 1: Receive Issue Attributes

Accept issue attributes as input.

Expected Input:

{
  "severity": "critical|high|medium|low",
  "impact": "breaking|major|minor|none",
  "likelihood": "certain|likely|possible|unlikely"
}

Step 2: Load Scoring Matrix

Use scoring matrix to assign points.

Severity Scores:

• critical: 10
• high: 7
• medium: 5
• low: 2

Impact Scores:

• breaking: 10
• major: 7
• minor: 3
• none: 0

Likelihood Scores:

• certain: 10
• likely: 7
• possible: 5
• unlikely: 2

Step 3: Calculate Total Score

Sum all factor scores.

Formula:

score = severity + impact + likelihood

Range: 0-30

Step 4: Determine Priority Category

Map score to priority category.

Priority Categories:

• P0 (Critical): 25-30

  • Label: "Critical - Immediate Action Required"
  • Action: Drop everything, fix now

• P1 (High): 19-24

  • Label: "High - Fix This Sprint"
  • Action: Prioritize in current sprint

• P2 (Medium): 12-18

  • Label: "Medium - Schedule for Next Sprint"
  • Action: Include in backlog, address soon

• P3 (Low): 5-11

  • Label: "Low - Schedule When Convenient"
  • Action: Nice to have, low priority

• P4 (Minimal): 0-4

  • Label: "Minimal - Consider Closing"
  • Action: May not be worth fixing

Step 5: Return Scored Result

Return complete priority assessment.

Expected Output:

{
  "score": 27,
  "category": "P0",
  "label": "Critical - Immediate Action Required",
  "factors": {
    "severity": 10,
    "impact": 10,
    "likelihood": 7
  },
  "recommendation": "Drop everything, fix now"
}

Error Handling

• Invalid Severity: Return error listing valid values
• Invalid Impact: Return error listing valid values
• Invalid Likelihood: Return error listing valid values
• Missing Factor: Return error requesting all factors

Examples

Example 1: Critical Bug

Input:

{
  "severity": "critical",
  "impact": "breaking",
  "likelihood": "certain"
}

Output:

{
  "score": 30,
  "category": "P0",
  "label": "Critical - Immediate Action Required",
  "factors": {
    "severity": 10,
    "impact": 10,
    "likelihood": 10
  },
  "recommendation": "Drop everything, fix now"
}

Example 2: Medium Priority Issue

Input:

{
  "severity": "medium",
  "impact": "minor",
  "likelihood": "likely"
}

Output:

{
  "score": 15,
  "category": "P2",
  "label": "Medium - Schedule for Next Sprint",
  "factors": {
    "severity": 5,
    "impact": 3,
    "likelihood": 7
  },
  "recommendation": "Include in backlog, address soon"
}

Example 3: Low Priority Enhancement

Input:

{
  "severity": "low",
  "impact": "minor",
  "likelihood": "unlikely"
}

Output:

{
  "score": 7,
  "category": "P3",
  "label": "Low - Schedule When Convenient",
  "factors": {
    "severity": 2,
    "impact": 3,
    "likelihood": 2
  },
  "recommendation": "Nice to have, low priority"
}

Example 4: High-Impact but Unlikely

Input:

{
  "severity": "high",
  "impact": "breaking",
  "likelihood": "unlikely"
}

Output:

{
  "score": 19,
  "category": "P1",
  "label": "High - Fix This Sprint",
  "factors": {
    "severity": 7,
    "impact": 10,
    "likelihood": 2
  },
  "recommendation": "Prioritize in current sprint"
}

Validation

• Calculates score correctly
• Maps to correct priority category
• Handles all valid factor values
• Returns clear recommendations
• Validates input factors

Supporting Files

• scoring-matrix.json

  : Factor scoring rules (see Supporting Files section)