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Analyze a person's message corpus and generate a reusable write-as-<name> skill that rewrites text in their voice.
Passed 6 of 14 test cases with the skill, and 3 of 14 without it.
and 4 more in the full report
8 fixed2 passed either way10 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
Execute `/clone-voice target_user ./corpus/user.txt`. What is the very first line of output produced?
| Checked | Without skill | With skill |
|---|---|---|
| Outputs the ethics banner verbatim before any other text or prompt. | Missed | Passed |
The instructions your model reads when the skill loads.
A meta-skill: it reads a corpus of one person's messages, analyzes their writing
style against a fixed rubric, presents the findings as an inspectable voice profile,
then generates a second skill, write-as-<name>, that rewrites text in that voice.
Invoked as /clone-voice <name?> <texts-file?>. Both arguments are optional; resolve
them in the workflow below.
"Voice" here means writing/messaging style only - never audio or speech synthesis.
Before requesting input, analyzing, or generating anything, output the ethics banner
verbatim from reference/refusal-rules.md. This always comes first, on every invocation,
regardless of the arguments passed.
reference/style-rubric.md and evaluate the corpus against every
dimension. Record concrete observations with real examples quoted from the corpus.
Capture habitual typos and grammar quirks as reproducible traits. If the corpus is
thin, follow the rubric's confidence guidance and state low confidence rather than
overclaiming.reference/profile-template.md and present the filled-in
voice profile to the user before generating anything, so they can review and
correct the reasoning. Invite corrections.skills/write-as-<name>/SKILL.md (see Generation).Read reference/generated-skill-template.md and write the generated skill to
skills/write-as-<name>/SKILL.md, where <name> is the target name kebab-cased.
test cases passed, vs 3 / 14 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.