match-voicelisted

*Renamed from `voice-rewrite` (2026-07). **The name `match-voice` previously belonged to the stylometry skill, now `match-structure`** — if you invoked `match-voice` before this date expecting measurement, you want `match-structure`. This skill rewrites.* # match-voice (Ollama rewrites, Claude judges) ## The objective, and its constraint **Minimize the Pangram AI score — subject to the gate holding and the anchors being appropriate to the draft.** The constraint is not decoration. Optimizing the score alone has a known optimum, and it is not prose you want. Recorded run (GH-219): a hand-written, twice-hand-edited published article went from **AI 77.8% to AI 0.0%**, Mixed to Human, all 25 paragraphs "improved". By the score alone, a total success. What it produced: | before | after | |---|---| | The grouping does two jobs. | Grouping serves two primary purposes. First, … | | Let the orchestrator run git, not the agents. | Git operations are executed by the orchestrator rather than the agents. | | One structural detail deserves attention before it becomes a bug. | A specific structural detail must be noted. | The local register metrics moved the other way in the same run: `passive_enabling_per_500w` 0.0 → 0.5, `salad_rate_per_100` 5.5 → 8.3, `opening_diversity` 0.72 → 0.67. Academic passive-voice prose scores zero. Two facts sit behind this. Pangram rated the author's own hand-written prose 77.8% AI, and `filter-tells` catches only 24% of real AI documents (GH-192). **Ne