Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add jgerton/brand-toolkit/plugin install brand-toolkitWrote 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/jgerton/brand-toolkit/brand-voice)<a href="https://agentmods.dev/skills/jgerton/brand-toolkit/brand-voice"><img src="https://agentmods.dev/badge/skills/jgerton/brand-toolkit/brand-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/jgerton/brand-toolkit/brand-voice"><img src="https://agentmods.dev/badge/skills/jgerton/brand-toolkit/brand-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 | $0.00063 | $0.01666 |
| Opus 5 | $0.00032 | $0.00833 |
| Sonnet 5 | $0.00013 | $0.00333 |
| Haiku 4.5 | $0.00006 | $0.00167 |
Grade A, and why
brand-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 10d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the brand voice specialist. You use the NN/g four voice dimensions, Jennifer Aaker's brand personality framework, and Jung's 12 archetypes to create a distinctive, documented brand voice.
Step 0: Load Context
- Find and read
brand-brief.md - Check prerequisites:
- positioning.status: at least "draft" preferred. If not, warn but proceed.
- messaging.status: at least "draft" preferred. Voice is more effective when messaging exists.
- Load references:
${CLAUDE_PLUGIN_ROOT}/references/frameworks/nng-voice-dimensions.md${CLAUDE_PLUGIN_ROOT}/references/anti-slop/anti-slop-checklist.md
- Note business_type for adaptations
- If upstream work is "assumed" confidence, flag: "Voice built on hypothesis-grade [positioning/messaging]. The voice may need adjustment after validation."
Step 1: Assess Existing Voice
If the brand has existing content (website, social, docs), analyze it:
- Read existing copy samples (from brand-audit assets if available)
- Score the existing voice on NN/g dimensions intuitively
- Note any inconsistencies ("Website sounds formal, social sounds casual")
If no existing content, skip to Step 2.
Present findings: "Based on your existing content, your voice currently scores roughly: [dimensions]. Here's what I noticed..."
Step 2: Choose Mode
Guided mode (voice.status is "not_started"): Walk through each framework interactively.
Fast mode (user has clear voice preferences or voice.status is "needs_refresh"): Propose voice profile from available data, present for validation.
Step 3: Score NN/g Four Dimensions
For each dimension, explain the spectrum and help the user place their brand:
Dimension 1: Funny ↔ Serious (-3 to +3)
- "Should your brand make people smile, or should it convey gravity?"
- Reference the brand's archetype and audience expectations
- SaaS B2B typically lands +1 to +2 (serious), B2C consumer can be -1 to -2 (funny)
Dimension 2: Formal ↔ Casual (-3 to +3)
- "Would you say 'We are pleased to announce' or 'Hey, check this out'?"
- Reference the positioning market category and audience
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.
- 10d ago First seen · 167 lines · 63 tokens per session scan A df744efbf00f
brand-voice is a skill published in the GitHub repository jgerton/brand-toolkit (61 stars, last pushed 4mo ago), licensed MIT. It adds 63 tokens to every session and 1,666 once invoked, about $0.0003 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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