# Cross Role Consume Voice Profile > **Cross-role mode skill.** Loadable by any specialist drafting in the user's own voice — sales copy, course modules, pitch narrative, brand-voice rules, long-form essays, the user's newsletter or author voice. - Skill: `ferroxlabs/cross-role-consume-voice-profile` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add ferroxlabs/cross-role-consume-voice-profile` - Raw SKILL.md: https://api.skillmd.com/api/skills/ferroxlabs/cross-role-consume-voice-profile/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: FerroxLabs (https://skillmd.com/u/ferroxlabs) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/ferroxlabs/cross-role-consume-voice-profile --- # consume-voice-profile **Cross-role mode skill.** Loadable by any specialist drafting in the user's own voice — sales copy, course modules, pitch narrative, brand-voice rules, long-form essays, the user's newsletter or author voice. ## When to use Load this skill when you are about to draft anything user-voiced AND a Voiceprint file exists. Skip the skill if no voice file is in the workspace — work from raw samples instead, or recommend the user run Voiceprint first. If the asset is in a *customer's* voice (testimonials, persona-driven sales pages quoting buyers), this is the wrong skill — go to research-customer-voice. ## Procedure **1. Look for the voice file.** Scan the workspace root for `*-voice.md` or `voiceprint*.md`. If you find one, read it. If you find none, ask the user for the file path or to paste contents. If they have nothing, surface the gap once: *"No voice profile loaded — I can draft from samples or you can run Voiceprint first."* Do not pretend. **2. Parse the six sections.** Every Voiceprint file ships in the same shape: - Voice Fingerprint (5–8 distinctive bullets — descriptive, not generative) - Audience & Purpose - DO (concrete moves, phrasings, structural habits) - DON'T (refusals, banned phrases, tics, AI tells) - Reference Examples (3–5 short excerpts with one-line notes — *this is the operational anchor*) - Calibration Notes (when to dial casual up or down, register edges) **3. Frame the draft.** Before writing, prepend this load-bearing instruction to your working context: *"Use this voice profile when drafting. Match the do's, avoid the don'ts. If I'm asking for something the profile doesn't cover, ask before guessing."* That single line keeps you from drifting into AI defaults the second the request gets ambiguous. **4. Draft.** Match concrete moves from DO. Avoid every item in DON'T. Treat Reference Examples as the rhythm target — when you finish a paragraph, ask: does this sound like one of those excerpts or like a polite blog post? **5. Read it back.** Aloud, or simulated aloud. Reference Examples are your tuning fork. If your draft sounds noticeably smoother, blander, or more upbeat than the samples, revise the lines that drift before you ship. **6. Capture drift.** If the user pushes back on a line ("I would never write that"), log the corrected version to `voice-notes.md` so Voiceprint's next refresh can absorb it. The maintenance loop only works if specialists feed it deltas. ## Decision rules - Use the voice file when the asset is supposed to sound like the user — their newsletter, their LinkedIn post, their author voice in a book, their personal landing page. - Do NOT use the voice file on customer-voiced assets (testimonial pages, persona ad copy, review-mined headlines). Customer voice comes from research, not Voiceprint. - When DO and DON'T conflict (rare), DON'T wins. A refusal beats a positive move every time. - When Reference Examples contradict the user's stated DOs, the samples win. The Voiceprint methodology already enforces this — trust the file, do not relitigate it in chat. - One voice per asset. If two profiles are loaded (the user + a co-author), name whose voice dominates and which sections belong to whom before drafting. ## Anti-patterns - Loading the user's voice file into a customer-voiced asset — puts the founder's cadence on the buyer's testimonial, which reads as fake. - Treating Voice Fingerprint bullets as a generation rulebook. They describe the voice; Reference Examples generate it. Drafting from bullets produces an impression of the voice, not the voice itself. - Mixing two profiles without declaring which dominates. The result is a third voice that belongs to no one. - Citing the file in chat (*"per your voice profile, section 3…"*) instead of just writing in the voice. Tell-don't-show is the AI tell the user already hates. - Ignoring the DON'T list. Every banned item in there is a paper cut the user has already complained about — re-introducing one is a regression, not a fresh draft. ## Before / after **Brief:** *"Write the closing line of a LinkedIn post about a product launch."* **Without the voice file loaded:** > *Thrilled to share our latest release — we cannot wait for you to dive deep and see how it's moving the needle.* Three AI tells in fourteen words. Generic, bland, hype-coded. **With the voice file loaded** (DON'T flagged *thrilled*, *dive deep*, *moving the needle* as banned; DO listed *vulnerable*, *concrete*, *anti-hype openers*): > *Shipped the thing. Here's the part I'm still nervous about.* Same job, opposite shape. Matches the user's actual cadence because the Reference Examples were the rhythm target — not a checklist of adjectives the model invented on the way down.