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 SupercmoHQ/superCMO-skills --skill analyzing-brandgit clone --depth 1 https://github.com/SupercmoHQ/superCMO-skillsWrote 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/supercmohq/supercmo-skills/analyzing-brand)<a href="https://agentmods.dev/skills/supercmohq/supercmo-skills/analyzing-brand"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/analyzing-brand/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/supercmohq/supercmo-skills/analyzing-brand"><img src="https://agentmods.dev/badge/skills/supercmohq/supercmo-skills/analyzing-brand.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00114 | $0.02376 |
| Opus 5.5 | $0.00046 | $0.00950 |
| Sonnet 5.5 | $0.00023 | $0.00475 |
| Haiku 4.5 | $0.00011 | $0.00238 |
Grade A, and why
analyzing-brand 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand
Analyze what a brand is from its website. Not for analyzing a single product's facts — that is analyzing-products skill.
Workflow
Step 1: Check whether the brand is already known
Read brand.md in ./supercmo-company. Where it already holds this brand, hand it back and stop — re-researching bills again and tells the user nothing new. Carry on where it's missing, where it's a different brand, or where the user asked to re-analyze. A
request for a detailed run of a brand already saved is a re-analysis too: run Step 3 again for a
fresh screenshot (its link doesn't last), then Step 4 in detailed mode with the hero photos
from brand.md's Assets, and patch only what they add.
Step 2: Check what you were given
| What you have | What to do |
|---|---|
| A brand website | Carry on. |
| A product page — Amazon, Shopify, a single listing | Wrong skill. Hand it to analyzing-products, and say which you used. |
| Nothing, or a URL that won't load | Ask for the website. A brand described from memory is invented, not read. |
| No mode named, by the caller or the brief | Run quick mode. Don't ask: detailed mode runs only when the caller or the user asks for it. |
When another skill runs this one (onboarding, a campaign plan), ask the user nothing: report a missing website or a site that couldn't be read back to that skill, and skip Step 6's hand-over — the calling skill gives the one reply.
Step 3: Read the site
Call url_extraction with the homepage as the url and no prompt or schema. It returns the
page's own text in data.markdown, and beside it branding — the colours, fonts and logo the page
actually renders — and screenshot, a picture of the page as a visitor first sees it. Read the
brand's identity off the text yourself, as references/reading-the-brand.md lays out: the brand's
name, what it sells, the logo, the tagline, how it writes, who it sells to, what sets it apart, and
the proof it offers for it. metadata.title and metadata.description are the brand's own words too:
use them where the text is thin. Keep branding and the screenshot for Step 4.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed · +25 lines 589ccacd52cc
- 1mo ago First seen · 112 lines · 114 tokens per session scan A 625035cad171
analyzing-brand is a skill published in the GitHub repository SupercmoHQ/superCMO-skills (242 stars, last pushed 6d ago), licensed Apache-2.0. It adds 114 tokens to every session and 2,376 once invoked, about $0.0005 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 2026-08-30.
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