Brand Discovery logo

Brand Discovery

OrganizationPopular
rampstackco
brand-discovery

Run upstream brand discovery covering audience research, competitive landscape, category dynamics, problem space, and positioning territory exploration. Use this skill at the very start of a brand or website project when the user needs to understand who they're for, who they compete with, what the audience actually needs, and where the brand could plausibly stand. Triggers on brand discovery, audience research, market research, competitive scan, category research, customer research, who is this for, who are we, positioning research, intake, kickoff. Also triggers when a creative brief is requested but the upstream inputs (audience, competitors, problem space) are not yet clear.

Overview

Publisherrampstackco
Repositoryclaude-skills
Skill namebrand-discovery
Stars
1K
Forks
134
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

    Published by rampstackco on GitHub. Read the source before you install it.

Installation

Install the Brand Discovery 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.
    https://github.com/rampstackco/claude-skills/tree/main/skills/brand-discovery
  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/rampstackco/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/brand-discovery .claude/skills/brand-discovery
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Brand Discovery 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 Discovery 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 Discovery 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 Discovery

Upstream of every brief, identity, and content plan. Discovery answers four questions: who the brand is for, what they need, who else is competing for that need, and where the brand could plausibly stand that competitors do not.


When to use

  • The very first phase of a new brand or website project
  • Understanding an audience before any creative work begins
  • Mapping competitors and category dynamics
  • Surfacing the problem space the brand will operate in
  • Generating positioning territories before brief or ideation
  • When a creative brief was requested but the inputs are missing

When NOT to use

  • The audience and category are already well-understood (jump to creative-brief or brand-ideation)
  • Validating a specific design or feature with users (use usability-testing)
  • Mapping the customer journey of an existing audience (use journey-mapping)
  • Generating brand names or visual directions (use brand-ideation)

Required inputs

  • The product, service, or organization being branded
  • Whatever is already known about the audience and category (often very little)
  • Access to existing materials (sales calls, support tickets, reviews, analytics)
  • Any constraints (parent brand, regulatory, geographic)
  • A timeline (a 1-week discovery looks different than a 6-week one)

The framework: 4 dimensions

Discovery covers four dimensions. Each has its own sources, methods, and outputs.

1. Audience

Who specifically does this serve?

Layers to surface:

  • Demographic: Age range, geography, language, life stage, income (only if relevant; do not over-collect demographics)
  • Psychographic: Values, motivations, beliefs, fears
  • Behavioral: What they currently do to address the problem, what tools they use, where they spend time online and offline
  • Jobs-to-be-done: The functional, emotional, and social jobs they hire a brand to perform

Sources:

  • Existing customer interviews (5 to 8 ideal)
  • Sales call recordings or transcripts
  • Support ticket themes
  • Review and forum analysis (Reddit, Trustpilot, App Store, niche communities)
  • First-party analytics (search console queries, on-site search, top pages)
  • Social listening (what they post about the category)

Output: 1 to 3 named audience segments, each with a one-page profile.

2. Competitors

Who else competes for the same audience and need?

Three layers of competitor:

  • Direct: Solves the same problem the same way (e.g., another SaaS in the category)
  • Indirect: Solves the same problem a different way (e.g., a spreadsheet replacing a SaaS tool)
  • Status quo: Doing nothing, doing it manually, or living with the problem

The third is most often forgotten and most often the actual competitor.

Per competitor, document:

  • Who they target (audience overlap with you)
  • How they position (what they claim to be)
  • What they actually deliver (often different from positioning)
  • Pricing model and structure
  • Strengths and weaknesses from the audience's perspective
  • Recent moves (launches, pivots, hires, departures)

Sources:

  • Their own website and marketing
  • Reviews of their product or service
  • Their content and SEO presence (use seo-competitor for the search angle)
  • Social proof and customer voices

Competitive scan benefits from quantitative grounding: not just "who are the competitors" but "how much traffic do they earn, where does it come from, who is the audience overlap." Similarweb is the standard for this kind of competitive landscape analysis; pair with Ahrefs for the SEO-specific overlap.

Output: Competitor matrix (3 to 8 competitors deep), plus a one-line "what makes them dangerous" for each.

3. Category and problem space

What is the broader context this brand operates in?

Map:

  • The problem. What is the actual user problem? Not the surface symptom, the underlying job to be done.
  • The category. How is the category structured? Is it new, mature, fragmenting, consolidating?
  • The conventions. What does every brand in the category do the same way? (These are the conventions you can break.)
  • The shifts. What is changing in the category? Technology, regulation, audience behavior, distribution.
  • The moats. What protects incumbents? Brand, distribution, network effects, switching costs?
  • The vocabulary. What language does the category use? What is jargon, what is meaningful, what is empty?

Sources:

  • Industry reports and analyst coverage
  • Trade publications and conferences
  • Adjacent category observations
  • Customer language vs. category language (the gap is informative)

Output: A category map and a list of conventions to consider breaking (or keeping deliberately).

4. Positioning territory

Given the audience, competitors, and category, where could this brand plausibly stand?

This is not yet "the positioning." Discovery surfaces possible territories. brand-ideation narrows them and commits.

Generate territories from:

  • Underserved audience segments (audiences others ignore)
  • Underserved jobs (jobs the category does not do well)
  • Category convention violations (what would happen if you broke the rules everyone follows)
  • Honest brand truths (what is genuinely true about this brand that competitors cannot also claim)
  • Category shifts (where the puck is going)

Per territory, document:

  • The statement (one sentence)
  • Why it could work (proof point)
  • Who would resonate (the audience for this territory)
  • Who is competing in this territory (often, no one good)
  • Risk (what makes it fragile)

Output: 3 to 5 distinct territories. Not yet committed. Inputs to brand-ideation.


Workflow

  1. Define the discovery scope. 1 week for a startup pre-launch. 4 to 6 weeks for a major rebrand. Set expectations.
  2. Audit existing inputs. Sales calls, support tickets, reviews, analytics, internal docs. Often more is known than people think.
  3. Audience research. 5 to 8 interviews if possible. Plus secondary research from review and forum analysis.
  4. Competitor mapping. 3 to 8 competitors deep, including indirect and status-quo competitors.
  5. Category mapping. Conventions, shifts, vocabulary, moats.
  6. Territory generation. 3 to 5 plausible positioning territories.
  7. Write the discovery report. Use the template in references/discovery-report-template.md.
  8. Hand off to next phase. Discovery feeds into creative-brief, brand-ideation, or content-strategy depending on where the project goes next.

Failure patterns

  • Skipping discovery to "save time." Every shortcut here costs 10x downstream when the brand fails to land.
  • Audience research that confirms what you already believe. If your audience research validates every assumption, you did not actually research. Look for surprises.
  • Demographic-heavy audience profiles. "Women aged 25 to 45" is not insight. Behavior, beliefs, and jobs-to-be-done are.
  • Listing every competitor as if equal. Most competitors do not matter. Pick the 3 that are genuinely dangerous.
  • Forgetting status-quo as competition. The biggest competitor is usually "doing nothing" or "doing it manually."
  • Outputting territories without rejection criteria. A territory without a "what this rejects" is not a territory.
  • Treating discovery as a one-time event. Categories shift. Audiences evolve. Re-run discovery at least every 3 years.

Output format

Default output is a discovery report at discovery-report.md plus appendices.

Structure:

  1. Executive summary (5 to 10 bullets)
  2. Audience (1 to 3 named segments with profiles)
  3. Competitors (matrix and per-competitor analysis)
  4. Category and problem space
  5. Positioning territories (3 to 5 candidates)
  6. Implications and recommendations
  7. Open questions that require further research

Appendices:

  • Interview notes (sanitized)
  • Competitor research data
  • Source list

If required data is unavailable

This skill's output depends on data, measurements, or tool results it cannot generate on its own. When a required input, tool, or data source is unavailable or unverifiable, the sanctioned output is the deliverable with the gap stated: what was needed, what was actually obtained or verified, and which parts of the output are affected. Fabricating, estimating, or interpolating a required number to complete the deliverable is never sanctioned. A stated gap is a complete answer.


Reference files

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 Discovery AI skill do?

Run upstream brand discovery covering audience research, competitive landscape, category dynamics, problem space, and positioning territory exploration. Use this skill at the very start of a brand or website project when the user needs to understand who they're for, who they compete with, what the audience actually needs, and where the brand could plausibly stand. Triggers on brand discovery, audience research, market research, competitive scan, category research, customer research, who is this for, who are we, positioning research, intake, kickoff. Also triggers when a creative brief is re...

Why use Brand Discovery on TypingMind?

Because you install it once and use it with any model. Brand Discovery 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 Discovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rampstackco/claude-skills/tree/main/skills/brand-discovery. 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 Discovery?

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 Discovery?

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

Is the Brand Discovery AI skill free?

Yes. It is published on GitHub by rampstackco 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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