goose-ads
Edit, resize, animate and study image ads with GooseWorks in this chat. New static or image ads go to the make-static-ads skill…
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
Claude Code
$ npx -y skills add gooseworks-ai/goose-skills --skill brand-research --agent claude-code
Codex
$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a codex -y
Cursor
$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a cursor -y
Gemini CLI
$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a gemini-cli -y
GitHub Copilot
$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a github-copilot -y
OpenCode
$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a opencode -y
Windsurf
$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a windsurf -y
name: brand-research description: 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.
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.
Create:
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.
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.
Review the homepage, product/collection pages, about page, pricing or offer pages, FAQ, policies, store navigation, social links, and press/brand resources. Capture:
Do not turn marketing claims into facts. Label them as brand-stated claims until corroborated.
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.
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.
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.
Write:
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.
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.
Asset generation is never required to finish brand research. If the user explicitly asks:
{
"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 i
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