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 raulpetruta/voice-calibration-plugin --skill voice-calibrationgit clone --depth 1 https://github.com/raulpetruta/voice-calibration-pluginWrote 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/raulpetruta/voice-calibration-plugin/voice-calibration)<a href="https://agentmods.dev/skills/raulpetruta/voice-calibration-plugin/voice-calibration"><img src="https://agentmods.dev/badge/skills/raulpetruta/voice-calibration-plugin/voice-calibration/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/raulpetruta/voice-calibration-plugin/voice-calibration"><img src="https://agentmods.dev/badge/skills/raulpetruta/voice-calibration-plugin/voice-calibration.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 | $0.00094 | $0.01153 |
| Opus 5 | $0.00047 | $0.00576 |
| Sonnet 5 | $0.00019 | $0.00231 |
| Haiku 4.5 | $0.00009 | $0.00115 |
Grade A, and why
voice-calibration 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Voice Calibration
Learn to write and talk like a specific person by collecting writing samples through interactive prompts, analyzing stylistic patterns, and generating a reusable voice profile.
Two Modes
1. Calibration Mode
Run when the user wants to create or update their voice profile. Guide them through writing prompts, analyze the results, and generate a profile.
2. Application Mode
When a voice profile exists (.voice-profile.md in the project root or ~/.claude/voice-profile.md), read it and apply the style to your writing when the user asks you to write in their voice.
Calibration Workflow
Follow these five phases in order. Present one prompt at a time and wait for the user's response before continuing.
Phase 1: Introduction
Explain the process briefly:
I'll give you a series of short writing prompts — tiny stories, opinions, casual messages, descriptions. Write naturally, exactly how you'd normally express yourself. There are no wrong answers.
How many prompts would you like? I recommend 8-10 for a solid profile, but we can do as few as 6 or as many as 12.
Also ask:
- What name should the profile use?
- Any languages or registers to capture? (e.g., "I code-switch between English and Spanish")
Phase 2: Writing Prompts
Read references/PROMPTS.md for the full prompt bank.
Selection rules:
- Pick prompts from at least 4 different categories to capture range
- Always include at least one from Casual Conversation and one from Opinions & Arguments — these reveal the most personality
- Present prompts one at a time
- After the user responds, acknowledge briefly and move to the next prompt — do not analyze or comment on their style mid-flow
- If a user's response is very short (under 20 words), gently ask them to expand: "Could you add a bit more? Even a few extra sentences help me pick up on your patterns."
Phase 3: Analysis
Once all samples are collected, read references/ANALYSIS-GUIDE.md and analyze every sample against each dimension listed there.
What ships with it
4 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 · 113 lines · 94 tokens per session scan A e45d7c8ca741
voice-calibration is a skill published in the GitHub repository raulpetruta/voice-calibration-plugin (12 stars, last pushed 5mo ago), licensed MIT. It adds 94 tokens to every session and 1,153 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 2026-08-30.
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