Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ferdinandobons/brand-docsnpx agentmods add commands/ferdinandobons/brand-docs/brand-extractWrote 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/ferdinandobons/brand-docs/brand-extract)<a href="https://agentmods.dev/commands/ferdinandobons/brand-docs/brand-extract"><img src="https://agentmods.dev/badge/commands/ferdinandobons/brand-docs/brand-extract/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/ferdinandobons/brand-docs/brand-extract"><img src="https://agentmods.dev/badge/commands/ferdinandobons/brand-docs/brand-extract.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 | $0.00000 | $0.00068 |
| Opus 5.5 | $0.00000 | $0.00027 |
| Sonnet 5.5 | $0.00000 | $0.00014 |
| Haiku 4.5 | $0.00000 | $0.00007 |
Grade A, and why
brand-extract 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 1mo 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
/brand-extract
Extract a Brand Profile from an Office template.
Run from the plugin root (or set BRAND_DOCS_ROOT to it):
python scripts/cli.py extract --name <brand> --template <template.docx|template.pptx|template.xlsx> --scope project
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.
- 1mo ago First seen · 10 lines · 0 tokens per session scan A 36a135d9d0fe
brand-extract is a command published in the GitHub repository ferdinandobons/brand-docs (279 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 68 tokens. 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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canva
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