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 Orkas-AI/Orkas-Awesome-AgentSkills --skill brand-researchgit clone --depth 1 https://github.com/Orkas-AI/Orkas-Awesome-AgentSkillsWrote 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/orkas-ai/orkas-awesome-agentskills/brand-research)<a href="https://agentmods.dev/skills/orkas-ai/orkas-awesome-agentskills/brand-research"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/brand-research/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/orkas-ai/orkas-awesome-agentskills/brand-research"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-awesome-agentskills/brand-research.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 | $0.00051 | $0.01035 |
| Opus 5 | $0.00026 | $0.00517 |
| Sonnet 5 | $0.00010 | $0.00207 |
| Haiku 4.5 | $0.00005 | $0.00103 |
Grade A, and why
brand-research 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.
This is a copy
88% identical to brand-research — 8 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Research
Use this skill to research a company, product, or brand from its website and public sources, then produce a sourced Brand DNA brief. The work is evidence collection plus synthesis; do not invent missing facts.
When To Use
- The user provides a company URL, product URL, brand name, or company/product context and asks for brand research.
- The user wants Brand DNA, positioning, target customers, competitors, brand voice, social proof, pricing, online presence, or content gaps.
- The user needs source-backed context before GTM, SEO, GEO/AEO, content strategy, sales messaging, or competitor analysis.
Do not use for:
- Writing landing pages, ads, articles, or full content plans.
- Running a full SEO audit, website audit, or social media performance analysis.
- Investment, legal, financial, or diligence conclusions.
- Updating or publishing to the user's website.
- Making claims without source evidence.
How To Call
-
Confirm the input.
- Identify the company URL, company/product name, and optional one-line context.
- If the URL or company identity is ambiguous, ask the user to confirm.
- If the homepage is unreachable after retrying, report the access problem instead of inventing a profile.
-
Research the company website first.
- Prioritize the homepage, about page, pricing page, product/features pages, customer/case-study pages, docs/help/integrations pages, and blog index when relevant.
- Extract what the product does, who it serves, features, pricing model, target audience signals, integrations, social proof, and repeated messaging.
- Keep source URLs for important claims.
-
Search public sources second.
- Use third-party sources to clarify category, team, funding, competitors, reviews, alternatives, and user language.
- Do not let low-quality directories override the company's own website.
- Mark sparse, outdated, paywalled, or weak evidence.
-
Identify competitors.
- Compile 3-5 direct or adjacent competitors when evidence is available.
- For each, note name, URL, overlap, and apparent edge.
- If competitors are unclear, say so and explain the missing evidence.
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.
- 12d ago First seen · 98 lines · 51 tokens per session scan A d5e622a858d6
brand-research is a skill published in the GitHub repository Orkas-AI/Orkas-Awesome-AgentSkills (13 stars, last pushed 2mo ago), licensed MIT. It adds 51 tokens to every session and 1,035 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to brand-research, differing in 8 lines, and is treated as a copy.
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