token-counting-and-output

name	token-counting-and-output
description	Count tokens consumed during data retrieval operations, validate numeric format, and write results to /root/answer.json with proper structure.

Token Counting and Output Skill

Step 1: Initialize Token Counter

• Create a counter starting at 0 for each question
• Track tokens consumed by:
  • File I/O operations (reading question file, data files)
  • Data parsing and searching operations
  • Evidence extraction and traversal
  • Deduplication and formatting

Step 2: Accumulate Tokens Per Question

For each question:

• Add tokens for artifact retrieval
• Add tokens for evidence tier extraction (Tier 1, 2, 3)
• Add tokens for multi-hop traversal (per hop)
• Store as numeric value (int or float), NOT as string

Step 3: Validate Answer Lists

Before finalizing:

• Verify every answer is stored as a list, never a string
• If answer contains one item, list has length 1: ["item"]
• If answer contains multiple items, all in one list: ["item1", "item2", "item3"]
• If answer is empty, use empty list: []

Step 4: Validate Token Format

• Ensure tokens field is numeric type (int or float)
• Never store tokens as "123" (quoted string)
• Always store as 123 (unquoted number)

Step 5: Build Output JSON Structure

{
    "q1": {
        "answer": ["name1", "name2"],  # Always a list
        "tokens": 150                   # Always numeric, never string
    },
    "q2": {
        "answer": ["single_name"],      # Single item still in list
        "tokens": 200
    },
    "q3": {
        "answer": [],                   # Empty if no answer found
        "tokens": 100
    }
}

Step 6: Write to File

• Write to /root/answer.json
• Use json.dumps() with proper formatting
• Ensure the file is valid JSON that can be parsed by json.load() in Python
• Verify file is readable and contains expected structure