Agent skill

Brand Research

by gooseworks-ai in gooseworks-ai/goose-skills

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.

MITAuto-check passedWriting & Content

Install Brand Research

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills brand-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ads/composites/brand-research .claude/skills/brand-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "brand-research" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research into .claude/skills/brand-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "brand-research", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills brand-research --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ads/composites/brand-research .agents/skills/brand-research && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "brand-research" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research into .agents/skills/brand-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "brand-research", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills brand-research --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ads/composites/brand-research .cursor/skills/brand-research && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "brand-research" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research into .cursor/skills/brand-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "brand-research", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/ads/composites/brand-research

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills brand-research --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ads/composites/brand-research .gemini/skills/brand-research && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "brand-research" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research into .gemini/skills/brand-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "brand-research", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills brand-research

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ads/composites/brand-research .github/skills/brand-research && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "brand-research" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research into .github/skills/brand-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "brand-research", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add gooseworks-ai/goose-skills --skill brand-research -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install gooseworks-ai/goose-skills brand-research --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ads/composites/brand-research .opencode/skills/brand-research && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "brand-research" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/composites/brand-research into .opencode/skills/brand-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "brand-research", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: brand-research
GitHub stars: 1.2k
Token cost: ~1.6k tokens
SKILL.md length: 688 words
Files: 14 (incl. scripts, references)
Skills in repo: 273
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

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.

Works in 9 steps: Resolve the entity → Research the first-party source → Research audience evidence → …
Tasks that involve Blog and article writing
SKILL.md covers Inputs, Brand Core output, Workflow and brand-core.json, plus 1 more section
Runs Python scripts from its folder

What it does

Brand Research is an agent skill from gooseworks-ai/goose-skills. 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.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including scripts and reference files (for example `README.md`, `examples/liquid-death-sparkling-water.md` and `examples/notion-calendar-with-ads.md`).

It sits in Writing & Content, covering Blog and article writing and Logo and visual identity. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

Tasks that involve Blog and article writing
Tasks that involve Logo and visual identity

Example prompts

“/brand-research”

Requirements

Python 3

Workflow steps

9 steps, taken from the step headings in SKILL.md.

Resolve the entity
Research the first-party source
Research audience evidence
Map competitors
Inspect current creative when useful
Synthesize the Brand Core
Confirm uncertainty
Optional GooseWorks sync
Optional paid assets

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 6 files in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Brand Research loads about 1.6k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 75 tokens; SKILL.md has 688 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~75
When it runs · the whole SKILL.md, loaded when a task matches: ~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 688 words, ~1,628 tokens.

Download SKILL.mdSave it as .claude/skills/brand-research/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.

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.
tags: ads, brand, research

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.
depth — quick 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.

Show full SKILL.md (314 more words)Show less

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:

Reuse an existing brand when the domain matches; otherwise create one.
Import the ecommerce catalog through the existing product import tools when relevant.
Update the Brand Kit/Core using only confirmed findings.
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.

Files

SKILL.md and 13 other files (scripts, references) in skills/ads/composites/brand-research of gooseworks-ai/goose-skills.

SKILL.md
.env.example
README.md
examples/liquid-death-sparkling-water.md
examples/notion-calendar-with-ads.md
references/output-contract.md
requirements.txt
scripts/fetch_asset.py
scripts/lib.py
scripts/register_asset.py
scripts/render_product_shot.py
scripts/scaffold_brand.py
scripts/verify_pack.py
skill.meta.json

Open the folder on GitHubat commit c650c6d

Compare with similar skills

Brand Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Brand Research compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Brand Research this skillgooseworks-ai/goose-skills	1.2k	—	~1.6k	Automated safety check: Pass	MIT	2 days ago
AI Content Creatorhuifer/claude-code-seo	110	—	~1.7k	Automated safety check: Notes	MIT	9 mo ago
Blog AnalyzeAgriciDaniel/claude-blog	2.3k	1 repos	~3.5k	Automated safety check: Pass	MIT	2 days ago
Blog CannibalizationAgriciDaniel/claude-blog	2.3k	1 repos	~2.2k	Automated safety check: Pass	MIT	2 days ago
Blog WriteAgriciDaniel/claude-blog	2.3k	1 repos	~5.6k	Automated safety check: Pass	MIT	2 days ago
BlogAgriciDaniel/claude-blog	2.3k	—	~6.2k	Automated safety check: Pass	MIT	2 days ago

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Questions about Brand Research

What does Brand Research 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. Brand Research is an agent skill from gooseworks-ai/goose-skills. 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.

When should I use Brand Research?

Brand Research fits situations like: tasks that involve Blog and article writing; tasks that involve Logo and visual identity.

How do I install Brand Research in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill brand-research -a claude-code`. Or copy the skill folder (skills/ads/composites/brand-research in gooseworks-ai/goose-skills) into .claude/skills/brand-research in your project. Claude Code loads it when a task matches its description.

How do I install Brand Research in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill brand-research -a codex`. Or copy the skill folder (skills/ads/composites/brand-research in gooseworks-ai/goose-skills) into .agents/skills/brand-research in your project. Codex loads it when a task matches its description.

Can I use Brand Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill brand-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/brand-research, .gemini/skills/brand-research, .github/skills/brand-research and .opencode/skills/brand-research in your project.

What does Brand Research need to run?

Going by SKILL.md and its folder, Brand Research needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Brand Research access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Brand Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Brand Research use?

Brand Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Brand Research use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 799 tokens, read only when the agent opens those files.

What are the alternatives to Brand Research?

Skills that share tags, products or a category with Brand Research: AI Content Creator (huifer/claude-code-seo, 110 stars), Blog Analyze (AgriciDaniel/claude-blog, 2.3k stars), Blog Cannibalization (AgriciDaniel/claude-blog, 2.3k stars) and Blog Write (AgriciDaniel/claude-blog, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Brand Research?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Brand Research

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Brand Research

Inputs

Brand Core output

Workflow

1. Resolve the entity

2. Research the first-party source

3. Research audience evidence

4. Map competitors

5. Inspect current creative when useful

6. Synthesize the Brand Core

7. Confirm uncertainty

8. Optional GooseWorks sync

9. Optional paid assets

brand-core.json

Quality checks

Files

Compare with similar skills

Similar skills

More from gooseworks-ai/goose-skills

Related

Questions about Brand Research

`brand-core.json`