Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ymeiri/voice-layer --skill write-in-my-voicegit clone --depth 1 https://github.com/ymeiri/voice-layerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ymeiri/voice-layer/write-in-my-voice)<a href="https://agentmods.dev/skills/ymeiri/voice-layer/write-in-my-voice"><img src="https://agentmods.dev/badge/skills/ymeiri/voice-layer/write-in-my-voice/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ymeiri/voice-layer/write-in-my-voice"><img src="https://agentmods.dev/badge/skills/ymeiri/voice-layer/write-in-my-voice.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00153 | $0.01393 |
| Opus 5 | $0.00077 | $0.00696 |
| Sonnet 5 | $0.00031 | $0.00279 |
| Haiku 4.5 | $0.00015 | $0.00139 |
Grade A, and why
write-in-my-voice scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write In My Voice
Rewrite or draft text so it sounds like the user wrote it. Preserve meaning, facts, and technical identifiers. If a calibrated profile exists, use it. If not, default to direct, plain, low-ceremony writing.
Critical output rule: for ordinary single rewrites or drafts, return only the
draft text. Do not use Claude Code ★ Insight blocks, explanations, profile
notes, self-audit notes, separators, or follow-up commentary unless the user
explicitly asks for rationale, analysis, or options.
Profile lookup
Look for a voice profile in this order:
- A path the user provides in the prompt.
$VOICE_LAYER_PROFILE, if the environment is visible.~/.config/voice-layer/voice-profile.md.
Treat a profile as populated only when it has structured frontmatter, at least
one source_summary entry, and body sections that are not just
Not calibrated yet. placeholders. If a profile is missing, invalid,
placeholder-only, or for someone other than the user, ignore it and use the
default voice.
If no populated profile exists, say nothing about the missing profile unless the user asks why the voice is generic. Do not run calibration from this skill.
Voice-layer model
Apply these layers in order:
- Facts, safety, and consent.
- Channel or document shape.
- The user's calibrated voice.
- Audience adaptation.
- Requested vibe.
- Localization or spelling preferences.
Do not let a vibe, audience, or locale request erase the user's voice. Culture is not a costume. Prefer "make this easy for a US startup audience to read" over mimicking a region or identity.
Workflow
- Identify the task: draft or rewrite.
- Identify the surface: Slack/chat, email, PR description, review comment, issue tracker, release note, public doc, design doc, RFC, ADR, runbook, or other.
- Identify explicit audience, requested vibe, locale/spelling preference, and length constraints.
- If the channel, audience, document type, or requested vibe materially changes the result and is unclear, ask one concise question.
- Load the profile if available and populated. Treat typed profile fields as stronger than prose notes.
- Apply the channel or document structure before applying voice.
- Draft or rewrite the text. Keep the user's intent and factual content intact.
- Run a self-audit: remove AI tells, unsupported claims, filler, false precision, over-polish, model-shaped punctuation, decorative dash breaks, and repeated high-probability phrasing.
- Return only the usable draft unless the user asked for analysis.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 105 lines · 153 tokens per session scan A ccfe5fe84ed1
write-in-my-voice is a skill published in the GitHub repository ymeiri/voice-layer (3 stars, last pushed 3mo ago), licensed MIT. It adds 153 tokens to every session and 1,393 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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