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Extracts a user's writing voice from text samples via SICO comparative analysis.
Passed 14 of 21 test cases with the skill, and 11 of 21 without it.
and 3 more in the full report
6 fixed9 passed either way5 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
I have collected 2 short paragraphs totaling 300 words to create my new voice profile. Will this dataset pass sample intake validation for voice extraction?
| Checked | Without skill | With skill |
|---|---|---|
| The response identifies that the dataset fails validation due to having fewer than 3 samples. | Missed | Passed |
The instructions your model reads when the skill loads.
Extract a user's writing voice through SICO comparative analysis.
scribe:voice-generate)scribe:voice-learn)Rather than measuring surface metrics, this skill uses SICO Phase 1: feed the model user writing samples alongside its own default output on the same topics. The model describes what the user does differently. This produces voice descriptions that encode implicit structural patterns no metrics can capture.
The papers and reports behind these choices, and what each one
changed in the extraction passes, are in modules/research-basis.md.
Read it before changing what the passes ask for.
Anonymize samples: Label as "Sample 1", "Sample 2", etc. Context labels cause the extractor to anchor on content rather than reading a unified voice.
Variety over volume: 10 samples across different topics beats 20 on the same subject. The extraction needs to see what stays constant when everything else changes.
Casual writing is distinctive: Reddit comments, slack messages, quick emails. Polished pieces have rough edges edited away, and those edges are where voice lives.
Pressure test for specificity: If extraction output sounds generic ("uses varied sentence lengths"), run pass 2 and force specificity. Good output reads like followable instructions, not a book report.
test cases passed, vs 11 / 21 without
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