kenneth-liao/ai-launchpad-marketplace/brand-guidelines

Brand Guidelines Generator

Create a self-contained brand guidelines skill through guided discovery. The generated skill lives at the user level and enforces brand identity across all future Claude Code sessions.

Workflow Overview

Execute these phases in strict order. Phase 0 is optional (skip if the user has no existing assets to share). Never skip Phases 1-4. Each phase builds on the previous.

Phase 0: Context Ingestion (Optional)

Before starting discovery, ask the user if they have existing business assets to share. Existing context dramatically reduces the number of questions needed — the skill extracts what it can and only asks about what's missing or ambiguous.

Opening prompt: "Before we start defining your brand, do you have any existing assets I can learn from? These could be your website, newsletter archives, social media profiles, pitch decks, brand documents, images, or anything that represents your brand today. This is optional — we can build entirely from scratch too."

Supported input types:

Analysis protocol:

For each provided asset, extract and categorize signals into the 6 discovery dimensions:

After analysis, present a summary:

"Here's what I extracted from your assets:

- Brand name: {name} | Tagline: {tagline or "none found"}

- Mission signals: {1-2 sentence summary of what the brand appears to be about}

- Voice signals: {detected traits, e.g., "Reads as friendly and expert — conversational but backs up claims"}

- Tone signals: {detected modifiers, e.g., "Short punchy sentences, casual vocabulary, avoids jargon"}

- Audience signals: {who the content seems to target}

- Asset types spotted: {list of visual content types found}

I'll use these as starting points during discovery. You'll have full control to confirm, adjust, or override everything."

Store the complete analysis as context_analysis with per-dimension confidence levels:

• High confidence — clear, unambiguous signal (e.g., brand name from a logo, explicit mission statement)
• Medium confidence — strong signal but inferred (e.g., voice traits from writing style analysis)
• Low confidence — weak or mixed signals (e.g., audience guessed from content topics)

Phase 1: Brand Discovery

Guide the user through structured questions to define their brand identity. Use the AskUserQuestion tool to present options. Ask questions one dimension at a time to keep the conversation focused.

Load the full question bank from references/discovery-framework.md.

Rules:

• Ask dimensions in order (they build on each other)
• One dimension per AskUserQuestion call — do not batch across dimensions
• If Phase 0 produced smart defaults, adapt each dimension based on confidence level (see Smart Default Behavior below)
• For open-ended dimensions, use AskUserQuestion with broad options that prompt elaboration
• For multi-choice dimensions, present all options with descriptions and enable multiSelect
• After each answer, give a brief 1-sentence acknowledgment contextualizing the choice, then move to the next dimension
• Complete ALL 6 dimensions before moving to Phase 2
• If the user wants to go back and change a previous answer, allow it

Smart Default Behavior (when Phase 0 data exists):

Dimensions (in order):

1. Brand name & tagline
2. Mission & value proposition
3. Voice & tone traits
4. Tone modifiers
5. Target audiences
6. Asset types & design system mapping

Dimension 6 — Special handling:

Before presenting asset type options, scan ~/.claude/.context/design-systems/ to discover available design systems. For each directory found, read the design system markdown file to extract the style name.

After the user selects their asset types, ask a follow-up for each selected asset type: which design system should be used? Present three options per asset type:

• Each discovered design system (by style name)
• "Create new design system" — flags this type for Phase 4
• "Decide later" — leaves the mapping empty for now

Store the complete mapping as asset_ds_mapping.

Phase 2: Synthesis & Preview

After all 6 dimensions are answered, synthesize into a formatted brand summary and present for confirmation.

Steps:

1. Derive the brand slug from the brand name: lowercase, spaces and special characters replaced by hyphens (e.g., "AI Launchpad Newsletter" → ai-launchpad-newsletter)
2. Synthesize voice traits + tone modifiers into 3-4 voice application rules — concrete, actionable guidelines for how this brand should sound
3. Derive brand anti-patterns from the inverse of chosen voice traits (see mapping in template reference)
4. Build audience profiles — for each audience segment, infer goals, frustrations, what resonates, and preferred platforms based on the user's description
5. Format the complete brand summary:

Present to the user:

## Brand Summary: {brand_name}
 
**Tagline:** {tagline}
**Mission:** {mission}
**Value Prop:** {value_prop}
 
**Voice Traits:** {trait_1}, {trait_2}
**Tone Modifiers:** {modifier_1}, {modifier_2}
 
**Voice Application Rules:**
- {rule_1}
- {rule_2}
- {rule_3}
 
**Audiences:**
- Primary: {primary_audience}
- Secondary: {secondary_audience}
 
**Asset Type → Design System Mapping:**
| Asset Type | Design System |
|------------|---------------|
| {type_1} | {ds_1 or "Create new" or "Decide later"} |
| ... | ... |
 
**Anti-Patterns (things this brand should NEVER do):**
- {anti_pattern_1}
- {anti_pattern_2}
- ...

1. Ask the user: "Does this brand summary look right? Want to change anything before I generate the skill?"
2. If the user wants changes, update the relevant fields and re-present
3. Once confirmed, proceed to Phase 3

Phase 3: Skill Generation

Generate the brand guidelines skill at ~/.claude/skills/{brand-slug}/SKILL.md.

Steps:

1. Load the template from references/brand-skill-template.md
2. Fill every {{placeholder}} with the confirmed brand data from Phase 2
3. Ensure the generated skill is fully self-contained — all brand data embedded directly, no references to external config files
4. Create the directory ~/.claude/skills/{brand-slug}/ if it doesn't exist
5. Write the generated SKILL.md to ~/.claude/skills/{brand-slug}/SKILL.md
6. Verify the generated skill — read the file back and check:

• No unfilled {{placeholder}} markers remain
• All 6 sections are present (Brand Identity, Voice & Tone, Target Audiences, Design System Resolution, How To Apply, Brand Anti-Patterns)
• The asset type mapping table has the correct number of rows
• If any issues found, fix and re-write before proceeding

1. Inform the user:

> "Your brand guidelines skill has been created at ~/.claude/skills/{brand-slug}/SKILL.md. Restart Claude Code to activate it — user-level skills are loaded at startup."

Phase 4: Optional DS Creation

If any asset types in asset_ds_mapping were mapped to "Create new design system", offer to create them now.

Steps:

1. List all asset types mapped to "Create new"
2. Ask the user: "You flagged {N} asset type(s) for new design systems: {list}. Want to create them now, or come back later?"
3. If the user wants to create now:

a. For each asset type, invoke the creator-stack:design-system skill (suggest "user level" as the output location so it's available system-wide) b. After each design system is created, update the brand skill's mapping table:

• Read ~/.claude/skills/{brand-slug}/SKILL.md
• Replace the "Create new" entry for that asset type with the new design system's style name and path
• Write the updated file

1. If the user wants to come back later, remind them they can update the mapping manually or re-invoke this skill in "update" mode

Updating an Existing Brand Skill

If the user already has a brand skill (detected by checking ~/.claude/skills/ for existing brand directories), offer an abbreviated update flow.