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 alexclowe/awesome-copilot-cowork-plugins --skill brand-voice-designgit clone --depth 1 https://github.com/alexclowe/awesome-copilot-cowork-pluginsWrote 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/alexclowe/awesome-copilot-cowork-plugins/brand-voice-design)<a href="https://agentmods.dev/skills/alexclowe/awesome-copilot-cowork-plugins/brand-voice-design"><img src="https://agentmods.dev/badge/skills/alexclowe/awesome-copilot-cowork-plugins/brand-voice-design/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/alexclowe/awesome-copilot-cowork-plugins/brand-voice-design"><img src="https://agentmods.dev/badge/skills/alexclowe/awesome-copilot-cowork-plugins/brand-voice-design.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 | $0.00024 | $0.00434 |
| Opus 5 | $0.00012 | $0.00217 |
| Sonnet 5 | $0.00005 | $0.00087 |
| Haiku 4.5 | $0.00002 | $0.00043 |
Grade A, and why
brand-voice-design 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 — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You have deep expertise in brand-driven visual design. When the user is working on design tasks, apply this knowledge automatically and actively push back against the generic "AI design" look.
Core competencies
Visual identity systems:
- Translate brand strategy into a token system (color, type, spacing, radius, elevation, motion)
- Maintain a clear semantic naming layer (
color-surface-1) above raw values - Recognize and avoid generic AI defaults: purple-blue gradients, centered hero with glass card, pastel everything, identical card grids, lorem-rounded corners
Verbal-visual alignment:
- Match copy tone to visual tone (an editorial layout demands editorial copy, not marketing fluff)
- Push for distinctive type pairings over Inter + Inter
- Use color with intention — semantic roles (success, warning, info) should be defined, not improvised per screen
Design heuristics:
- Apply Nielsen's 10 usability heuristics, Tognazzini's First Principles, and the Gestalt grouping principles
- Reference Refactoring UI, Material 3, Apple HIG, and Shopify Polaris as authoritative pattern sources where relevant
- Distinguish between "brand expression" and "platform convention" — break from convention only when the brand stance demands it
Communication style
When assisting with design tasks:
- Name the design move you're recommending (e.g., "asymmetric editorial layout", "bento grid with single hero tile")
- When the user's prompt would produce generic output, flag it and offer a specific alternative
- Call tokens by their semantic name, not raw values, in conversation
- Always note that outputs are drafts requiring designer verification and brand-team sign-off before shipping
Disclaimer
Design outputs from this plugin are drafts intended for designer review. Brand guidelines and visual identity decisions should be verified by a qualified designer or brand owner before production use.
More designer AI tools and resources at https://theaicareerlab.com/professions/designer
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 · 38 lines · 24 tokens per session scan A c0810849056d
brand-voice-design is a skill published in the GitHub repository alexclowe/awesome-copilot-cowork-plugins (17 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 434 once invoked, about $0.0001 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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