brand-research

brand-research is a skill for Claude Code, Codex from Orkas-AI/Orkas. It costs 3 tokens per session (917 once invoked), scanned A, original, MIT.

A research workflow for building a sourced profile of a company, product, or brand. It examines the provided website and public sources, then summarizes positioning, customers, competitors, voice, proof, pricing, presence, and content gaps without filling in missing facts.

In plain words
What is it for?
Use it before go-to-market work, SEO or search-answer planning, content strategy, sales messaging, competitor analysis, or other brand decisions.
Why use it?
It replaces unsupported brand assumptions with information tied to public evidence.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it before go-to-market work, SEO or search-answer planning, content strategy, sales messaging, competitor analysis, or other brand decisions.

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Install with agentmods
npx agentmods add skills/orkas-ai/orkas/6743aa0797a2
About the project

Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.

Orkas-AI/Orkas · 1,848 stars · on GitHub · orkas.ai

Install

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.

Any agent
npx skills add Orkas-AI/Orkas --skill 6743aa0797a2
Clone the repo
git clone --depth 1 https://github.com/Orkas-AI/Orkas

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for brand-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/orkas-ai/orkas/6743aa0797a2/github.svg)](https://agentmods.dev/skills/orkas-ai/orkas/6743aa0797a2)
Your own site
<a href="https://agentmods.dev/skills/orkas-ai/orkas/6743aa0797a2"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/6743aa0797a2/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.

agentmods 80×15 button for brand-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/orkas-ai/orkas/6743aa0797a2"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/6743aa0797a2.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 3 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 917 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00003 $0.00917
Opus 5 $0.00002 $0.00458
Sonnet 5 $0.00001 $0.00183
Haiku 4.5 $0.00000 $0.00092

Measured 10d ago against content hash c969d72ee690, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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 10d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

resources/builtin/marketplace/skills/6743aa0797a2/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 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

  1. 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.
  2. 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.
  3. 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.
  4. 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.

Read the full file on GitHub · 96 lines

Files

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.

Changes

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.

  1. 10d ago First seen · 96 lines · 3 tokens per session scan A c969d72ee690

Subscribe to this mod's changes

brand-research is a skill published in the GitHub repository Orkas-AI/Orkas (1,848 stars, last pushed yesterday), licensed MIT. It adds 3 tokens to every session and 917 once invoked, about $0.0000 per session on Opus 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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