Brand Research logo

Brand Research

OrganizationPopular
gooseworks-ai
brand-research

Research a company or brand from its website and produce a reusable Brand Core covering products, audience, competitors, positioning, offers, messaging evidence, voice, and visual identity. Use before growth, ad, content, creator, or product work when reliable brand context is missing.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namebrand-research
Stars
1.2K
Forks
208
Bundled files
11
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by gooseworks-ai on GitHub. Read the source before you install it.

Installation

Install the Brand Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git /tmp/goose-skills
mkdir -p .claude/skills
cp -r /tmp/goose-skills/skills/ads/composites/brand-research .claude/skills/brand-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Brand Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Brand Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Brand Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Brand Research

Build a sourced Brand Core that future research, analysis, and creative workflows can reuse without rediscovering the company every time.

The required path is research-only and works with local files. GooseWorks sync, ad imports, and paid asset generation are optional extensions—not prerequisites for a complete result.

Inputs

  • website — required canonical company or brand website.
  • focus — optional product, collection, market, or campaign to prioritize.
  • output_dir — optional; defaults to a clearly named local brand folder.
  • depthquick or full (default full).
  • sync_to_gooseworks — optional, default false.
  • include_existing_ads — optional, default true in full mode.
  • generate_assets — optional paid extension, default false.

Brand Core output

Create:

text
brand-core/
  summary.md
  products.md
  audience.md
  competitors.md
  positioning-and-offers.md
  messaging.md
  visual-identity.md
  sources.md
  brand-core.json

Use local paths that work outside GooseWorks. brand-core.json is a structured echo for other agent skills; the Markdown remains the human-readable source of truth.

Workflow

1. Resolve the entity

Open the provided website and confirm the company name, canonical domain, market, and focus product. If the site is inaccessible or the identity remains ambiguous, ask for the minimum clarification instead of researching the wrong entity.

2. Research the first-party source

Review the homepage, product/collection pages, about page, pricing or offer pages, FAQ, policies, store navigation, social links, and press/brand resources. Capture:

  • what the company sells and how the catalog is organized;
  • prices, offers, bundles, guarantees, subscriptions, and availability;
  • product claims, ingredients/materials, use cases, and differentiators;
  • stated audiences and customer outcomes;
  • brand voice, visual system, proof, and trust markers.

Do not turn marketing claims into facts. Label them as brand-stated claims until corroborated.

3. Research audience evidence

Use reviews, forums, search, social posts, and comments to identify pains, desired outcomes, triggers, objections, alternatives, product language, and use contexts. Preserve short representative language with source links. Use comment-mining for relevant public social threads.

4. Map competitors

Identify direct competitors, substitutes, and reference brands. For each, record positioning, key offer, price band when visible, proof style, and how the focus brand plausibly wins or loses. Separate a verified competitor from a likely competitor inferred from category overlap.

5. Inspect current creative when useful

In full mode, use competitor-ad-intelligence with the brand as advertiser to inspect current Meta, Google, or LinkedIn ads through ScrapeCreators. Extract recurring hooks, offers, proof, product presentation, formats, CTAs, and landing destinations. Do not infer spend or conversion performance from ad-library presence.

6. Synthesize the Brand Core

Write:

  • summary.md: company, category, markets, business model, brand promise, voice in three words, and important unknowns.
  • products.md: product/collection catalog with source URL, price/offer, claims, use cases, and priority.
  • audience.md: audience segments, jobs-to-be-done, triggers, pains, objections, alternatives, and exact sourced language.
  • competitors.md: direct competitors, substitutes, reference brands, positioning comparison, and evidence.
  • positioning-and-offers.md: value proposition, differentiators, offers, proof, guarantees, and gaps.
  • messaging.md: repeated claims, hooks, objections, proof points, CTAs, useful angles, and what the brand should not say.
  • visual-identity.md: logo use, colors, typography when identifiable, photography, layout, product presentation, and off-brand patterns.
  • sources.md: URL, access date, source type, and which claims it supports.

7. Confirm uncertainty

Show a concise confirmation summary: company, priority products/services, audience, likely competitors, offers, and messaging angles. Mark low-confidence findings and ask only about material gaps.

8. Optional GooseWorks sync

Only when requested and the GooseWorks MCP tools are available:

  1. Reuse an existing brand when the domain matches; otherwise create one.
  2. Import the ecommerce catalog through the existing product import tools when relevant.
  3. Update the Brand Kit/Core using only confirmed findings.
  4. Never overwrite stronger first-party brand data without showing the change.

The local Brand Core remains usable even if sync fails.

9. Optional paid assets

Asset generation is never required to finish brand research. If the user explicitly asks:

  • use product-photoshoot for product photography;
  • use goose-graphics for branded graphics;
  • quote credits and confirm before any paid generation.

brand-core.json

json
{
  "brand": {"name":"","website":"","category":"","markets":[]},
  "products": [{"name":"","url":"","price":"","claims":[],"offers":[]}],
  "audiences": [{"segment":"","jobs":[],"pains":[],"objections":[],"language":[]}],
  "competitors": [{"name":"","url":"","relationship":"direct|substitute|reference","evidence":""}],
  "positioning": {"promise":"","differentiators":[],"proof":[],"offers":[]},
  "messaging": {"hooks":[],"angles":[],"claims":[],"ctas":[],"never_say":[]},
  "visual_identity": {"colors":[],"typography":[],"photography":[],"off_limits":[]},
  "sources": [{"url":"","accessed_at":"","supports":[]}],
  "unknowns": []
}

Omit unknown values rather than inventing them.

Quality checks

  • Every material claim is attributable to a source or clearly labeled as an inference.
  • Products and offers match the live site and include canonical URLs.
  • Audience conclusions include customer evidence, not only brand copy.
  • Competitors are classified as verified or inferred.
  • Messaging angles trace back to repeated evidence.
  • No paid generation ran without explicit confirmation.
  • The local output is complete even when GooseWorks is not connected.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Brand Research AI skill do?

Research a company or brand from its website and produce a reusable Brand Core covering products, audience, competitors, positioning, offers, messaging evidence, voice, and visual identity. Use before growth, ad, content, creator, or product work when reliable brand context is missing.

Why use Brand Research on TypingMind?

Because you install it once and use it with any model. Brand Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Brand Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Brand Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Brand Research?

As many as you like. As long as a model supports skills, you can use Brand Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Brand Research AI skill free?

Yes. It is published on GitHub by gooseworks-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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