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 Owl-Listener/designpowers --skill voice-and-tonegit clone --depth 1 https://github.com/Owl-Listener/designpowersWrote 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/owl-listener/designpowers/voice-and-tone)<a href="https://agentmods.dev/skills/owl-listener/designpowers/voice-and-tone"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/voice-and-tone/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/owl-listener/designpowers/voice-and-tone"><img src="https://agentmods.dev/badge/skills/owl-listener/designpowers/voice-and-tone.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 | $0.00034 | $0.00647 |
| Opus 5 | $0.00017 | $0.00324 |
| Sonnet 5 | $0.00007 | $0.00129 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
voice-and-tone 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Voice and Tone
Voice is who you are. Tone is how you say it right now. Voice stays constant. Tone adapts to context. This skill defines both so every word sounds like the same person wrote it.
When to Use
- At the start of a project, during or after
design-strategy - When the content-writer agent needs voice guardrails
- When interface copy sounds inconsistent across screens
Step 1: Define Voice Attributes
Choose 3-5. For each, define "this, not that":
| Attribute | This | Not that |
|---|---|---|
| Warm | Friendly, approachable | Sycophantic, emoji-heavy |
| Knowledgeable | Confident, precise | Academic, condescending |
| Direct | Clear, action-oriented | Blunt, cold, robotic |
| Encouraging | Celebrates effort | Patronising, fake-cheerful |
The "not that" column prevents drift.
Step 2: Define Tone by Context
| Context | Feel | Example |
|---|---|---|
| Success | Celebration, warmth | "Your monstera is happy. Next water Thursday." |
| Error | Calm, helpful, no blame | "We couldn't save that. Check your connection and try again." |
| Onboarding | Welcoming, confidence-building | "Let's get to know your plants. About 30 seconds." |
| Empty state | Inviting, action-oriented | "Your windowsill is empty. Add your first plant." |
| Loading | Reassuring, brief | "Checking your plants..." |
| Destructive | Clear, calm, reversible | "Remove this plant? You can undo this." |
Step 3: Build the Vocabulary
| Always use | Never use |
|---|---|
| water | irrigate |
| happy | optimal |
| check it out | investigate |
| you | the user |
The content-writer agent uses this as a constraint.
Step 4: Set Reading Level
| Audience | Target |
|---|---|
| General consumer | Grade 6-8 |
| Professional tool | Grade 8-10 |
| Technical docs | Grade 10-12 |
Voice Audit Checklist
- Every screen sounds like the same person wrote it
- Voice attributes are present in the copy
- Tone matches the context
- Vocabulary list words used consistently
- Reading level at or below target
- Copy works read aloud by a screen reader
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 · 80 lines · 34 tokens per session scan A 4b78a892de17
voice-and-tone is a skill published in the GitHub repository Owl-Listener/designpowers (245 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 647 once invoked, about $0.0002 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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