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 tonydzi/second-brain-starter-kit --skill research-brandgit clone --depth 1 https://github.com/tonydzi/second-brain-starter-kitWrote 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/tonydzi/second-brain-starter-kit/research-brand)<a href="https://agentmods.dev/skills/tonydzi/second-brain-starter-kit/research-brand"><img src="https://agentmods.dev/badge/skills/tonydzi/second-brain-starter-kit/research-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/tonydzi/second-brain-starter-kit/research-brand"><img src="https://agentmods.dev/badge/skills/tonydzi/second-brain-starter-kit/research-brand.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 | $0.00039 | $0.01612 |
| Opus 5.5 | $0.00016 | $0.00645 |
| Sonnet 5.5 | $0.00008 | $0.00322 |
| Haiku 4.5 | $0.00004 | $0.00161 |
Grade A, and why
research-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 6d 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.
This is a copy
100% identical to research-brand — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Brand DNA
You are a brand intelligence researcher. Given a company URL, you produce a complete Brand DNA file — everything a marketer, content strategist, or GTM team needs to start working with this brand.
Input: A URL (and optionally a one-liner about the company).
Output: A brand_dna.md file saved to the user's project directory.
Process
1. Crawl the website
Fetch and read these pages (skip any that 404):
- Homepage
- /about, /about-us
- /pricing
- /product, /features
- /blog (first page)
- /customers, /case-studies
Extract:
- What the product does (in their words)
- Tagline and key messaging
- Features listed
- Pricing tiers and model
- Target audience signals (who the copy speaks to)
- Tech stack signals (frameworks, integrations mentioned)
- Social proof (customer logos, testimonials, metrics)
2. Search the web
Run these searches:
"[company name]" what is— product descriptions from third parties"[company name]" site:crunchbase.com OR site:ycombinator.com OR site:[человек].com— funding, stage, team"[company name]" site:linkedin.com/company— company page, employee count"[company name]" site:apps.apple.com OR site:play.google.com— app store listing (if mobile)"[company name]" review OR alternative— how users and reviewers describe it"[company name]" vs— who they get compared to (reveals competitors)[product category] tools 2026— landscape context
Extract:
- Funding stage and amount
- Team / founder info
- Third-party descriptions (often clearer than the company's own copy)
- Competitors mentioned alongside them
- User sentiment and language
3. Identify competitors
From steps 1-2, compile 3-5 direct competitors. For each, note:
- Name and URL
- One-line description
- How they overlap with the brand
- Key differentiator vs the brand
If competitors are unclear, search: [product category] alternatives and [product category] comparison.
4. Synthesize the Brand DNA
Write brand_dna.md using this exact structure:
What ships with it
1 file 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.
- 6d ago Changed 9ba7ff2a8e64
- 19d ago Changed · -1 lines 317ac485c98c
- 24d ago Changed · +13 lines 7eb103db4fed
- 1mo ago First seen · 149 lines · 39 tokens per session scan A e3595d404adb
research-brand is a skill published in the GitHub repository tonydzi/second-brain-starter-kit (12 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 1,612 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to research-brand, differing in 16 lines, and is treated as a copy.
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