afk-agents Slop Score Analysis
Analyzes text for statistical patterns common in AI-generated writing.
Usage
Run the analysis script on any text file:
bun run ./scripts/slop-score/analyze.js --all <filepath>
Always use the --all flag to include complete metrics.
Output
Return the raw JSON output exactly as received. Do not summarize, interpret, or add commentary. The JSON output is the complete result.
JSON Structure
{
"file": "path/to/file.md",
"total_chars": 13548,
"total_words": 2116,
"slop_score": 6.26,
"metrics": {
"slop_words_per_1k": 3.31,
"slop_trigrams_per_1k": 0,
"ngram_repetition_score": 124.6,
"not_x_but_y_per_1k_chars": 0.29,
"lexical_diversity": {
"mattr_500": 0.50,
"type_token_ratio": 0.31,
"unique_words": 654,
"total_words": 2116
},
"vocab_level": 6.08,
"avg_sentence_length": 9.97,
"avg_paragraph_length": 24.43,
"dialogue_frequency": 0.96
},
"slop_word_hits": [["paradoxically", 1], ["fundamentally", 1]],
"slop_trigram_hits": [],
"contrast_matches": [
{
"pattern_name": "S1_RE_NOT_DASH",
"sentence": "The phone was not just a device-it was an extension of its owner.",
"match_text": "not just a device-it was",
"sentence_count": 1
}
],
"top_over_represented": {
"words": [{"word": "flickered", "ratio": 5756.12, "count": 42}],
"bigrams": [{"phrase": "heavier like", "ratio": 7364.33, "count": 5}],
"trigrams": [{"phrase": "story it's epic", "ratio": 3058.81, "count": 3}]
}
}
Calibration Reference
Lower scores indicate more human-like writing:
- Human baseline: ~10
- Claude Sonnet 4.5: ~20
- GPT-4o: ~upper 40s
- Gemini 2.5 Flash: ~upper 70s