PROJECT VOLUME
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Code by language:                                files           SLOC
Python                                               2              8
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Total SLOC                                              = 8
Files in scan                                           = 4
Documentation                                           = 12 lines (2 files)
Documentation-to-Code Ratio (MD/SLOC)                   = 1.500 [▚▞▚▞▚▞▚▞▚▞▚▞▚▞▚▞▚▞▚▞] 150.0% RECURSION
                                                         You ran slopcount inside slop. Recursion
Comments                                                = 12 lines
Comments-to-Code Ratio (comment/SLOC)                   = 1.500 [████████████████████] 150.0% COMMENT_DRIVEN
                                                         Comment-driven development. The code is an attachment
Detected SLOP                                           = 16 lines
Slop-to-Code Ratio (SLOP/SLOC)                          = 2.000 [████████████████████] 200.0% INFESTED
                                                         Full slop infestation. Call the exterminators
COMPREHENSION EFFORT & COST
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Reading documentation                                   = 0.0 h  (43 words / 238.0 wpm × 2.3)
Reading code                                            = 0.0 h  (8 SLOC / 200.0 per hour)
Reading comments                                        = 0.0 h  (72 words, lines × 6 estimate)
Cognitive processing                                    = 0.1 h  (7 points × 0.5 min)
Total reading time                                      = 0.1 h

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Cost Ladder (write / regenerate / comprehend)
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COCOMO  write the whole tree (docs count as code) = $ 352 (0.0 person-months · 0.7 mo · 0.0 people)
           docs                   0.0 person-months · $ 170
           source code            0.0 person-months · $ 170
             code                 0.0 person-months · $ 170
             comments               —  (scc does not count comments)
           data                   0.0 person-months · $ 0
LOCOMO  regenerate it with an LLM                = $ 0.01 (0.0 h + 0.0 h review)
           docs                   0.0 h · $ 0.01
           source code            0.0 h · $ 0.01
             code                 0.0 h · $ 0.01
             comments               —  (scc does not count comments)
           data                   0.0 h · $ 0.00
SLOCOMO comprehend the project                   = $ 25 (0.1 h reading · 0.0 person-months) — per person
           (a team multiplies by headcount — see the scale below)
           docs                   0.0 h · $ 2
           source code            0.1 h · $ 23
             code                 0.1 h · $ 22  (incl. cognitive 0.1 h)
             comments             0.0 h · $ 1
           data                     —  (not read)

Team Comprehension Cost (headcount × per person)
    1 person = 0.0 person-months · $ 25
    2 people = 0.0 person-months · $ 49
    3 people = 0.0 person-months · $ 74
    5 people = 0.0 person-months · $ 123
    8 people = 0.0 person-months · $ 196
   13 people = 0.0 person-months · $ 319
   21 people = 0.0 person-months · $ 515

Comprehension Tokens (LOCOMO round-trip: in + out)      = 2,775
Context Windows Consumed                                = 0.0139 × 200K / 0.0028 × 1M
GPU-hours of Regret                                     = 0.0077

Coffee Required                                         = 1 cup ($ 4.00)
Therapy Recommended                                     = 1 session ($ 150.00)
DETECTED SLOP
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Totals grouped by slop origin (dominant slop source first):
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Origin                           files    slop lines    slop %  cognitivity
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Prose (comments/docstrings)          2             3      18.8  high      
Markdown specs                       1             2      12.5  medium    
Code style                           1             2      12.5  medium    
Git history                          0             0       0.0  low       
Environment markers                  1             —         —  —         
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Top slop files:
  1. README.md         ████████████████████  13 lines
  2. src/defensive.py  ███░░░░░░░░░░░░░░░░░  2 lines
  3. src/greeter.py    ██░░░░░░░░░░░░░░░░░░  1 line
Agents detected (not counted as slop): CLAUDE.md
Run with --evidence to see every finding with its source line.
