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 calibrate-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/calibrate-my-voice)<a href="https://agentmods.dev/skills/ymeiri/voice-layer/calibrate-my-voice"><img src="https://agentmods.dev/badge/skills/ymeiri/voice-layer/calibrate-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/calibrate-my-voice"><img src="https://agentmods.dev/badge/skills/ymeiri/voice-layer/calibrate-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 | $0.00108 | $0.01766 |
| Opus 5 | $0.00054 | $0.00883 |
| Sonnet 5 | $0.00022 | $0.00353 |
| Haiku 4.5 | $0.00011 | $0.00177 |
Grade A, and why
calibrate-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 11d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Calibrate My Voice
Create or update a local voice-layer profile for the write-in-my-voice skill. Calibration is a consented setup workflow, not a hidden preprocessing step.
Defaults
- Profile path:
~/.config/voice-layer/voice-profile.md. - Template:
assets/voice-profile.template.md. - Raw samples: do not retain them after analysis unless the user explicitly asks.
- Exact examples in the profile: keep short and only when the user approves.
- Assistant-generated text: do not treat it as the user's voice unless the user explicitly accepted or edited it.
- Retention promises apply to the generated profile and files this skill creates. The active agent, connector, or host application may still persist session transcripts or tool-result artifacts outside the profile. Before reading connector/private sources, disclose this limitation and, where possible, prefer metadata-only inventory, scoped reads, temporary files outside the repo, and cleanup after analysis.
Consent gates
Before reading private sources, state the source, scope, and what will be retained. Ask for confirmation if the user has not already been explicit.
Start every calibration with source negotiation unless the user already gave a complete, explicit source plan and explicitly excluded all other sources.
The negotiation must let the user choose between pasted samples and agent-collected samples. If tools or connectors are available, offer them as options without using them yet.
If using connectors, MCP tools, hosted agents, or agent session exports, explain that raw source content may be visible to the active agent and may be persisted by the agent host as session or tool logs even when the voice profile itself keeps only derived patterns. Do not imply that derived-patterns retention erases all external session artifacts.
Do not use a hard-coded product menu as the final menu. First inventory what the current agent can plausibly collect from, then build the source menu from that local capability set.
What ships with it
7 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.
- 11d ago First seen · 111 lines · 108 tokens per session scan A 6cf84e780152
calibrate-my-voice is a skill published in the GitHub repository ymeiri/voice-layer (3 stars, last pushed 3mo ago), licensed MIT. It adds 108 tokens to every session and 1,766 once invoked, about $0.0005 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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