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.
git clone --depth 1 https://github.com/ssheleg/super-uxWrote 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/commands/ssheleg/super-ux/brand-update)<a href="https://agentmods.dev/commands/ssheleg/super-ux/brand-update"><img src="https://agentmods.dev/badge/commands/ssheleg/super-ux/brand-update/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/commands/ssheleg/super-ux/brand-update"><img src="https://agentmods.dev/badge/commands/ssheleg/super-ux/brand-update.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 | $0.00013 | $0.00216 |
| Opus 5.5 | $0.00005 | $0.00086 |
| Sonnet 5.5 | $0.00003 | $0.00043 |
| Haiku 4.5 | $0.00001 | $0.00022 |
Grade A, and why
brand-update 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 2d 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.
What it actually says
Run the brand-voice skill in Update mode.
- Name what changed — positioning, a persona, a price, a tier name, a new surface, a fact past its review date.
- Apply the edits where they belong. A renamed entity propagates to
terminology.md,strings.mdand everylocales/<code>.mdin the same change — a rename that lands in one file and not the others is how two spellings start. - Changed files drop to
Status: draftuntil re-approved. - Re-stamp
Last calibrated. - Run
python3 docs/brand/lint.pyand report what moved.
If the foundation changed rather than the copy, say so: the pack derives from it, and a positioning change may deserve a different pack rather than a patched one.
Additional context from the user: $ARGUMENTS
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.
- 2d ago Changed · -17 tokens per session d0d8460fee5f
- 1mo ago First seen · 22 lines · 30 tokens per session scan A 79a59ccbf6eb
brand-update is a command published in the GitHub repository ssheleg/super-ux (6 stars, last pushed 2d ago), licensed MIT. It adds 13 tokens to every session and 216 once invoked, about $0.0001 per session on Opus 5.5. 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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