| name | cf-style-guide |
| description | Import brand voice profiles from documents or URLs. Use when setting up or updating a brand. |
| argument-hint | [brand-name or URL] |
| effort | medium |
Brand Style Guide Importer
Import brand voice profiles from existing style guide documents, URLs, or manual input. Extracts tone, formality, personality traits, writing style, approved/banned terminology, and compliance guardrails into a structured brand profile JSON that the ContentForge pipeline uses for every piece of content it produces.
When to Use
Use /contentforge:cf-style-guide when:
- You're onboarding a new brand and have an existing style guide document (.docx, .pdf) or URL
- You need to update an existing brand profile with revised guidelines
- You want to extract terminology and guardrails from compliance documents
- You're setting up ContentForge for a regulated industry (Pharma, BFSI, Healthcare, Legal) where guardrails are critical
- You want to validate that an existing brand profile matches current guidelines
- A client provided a style guide URL (Notion page, Google Doc, website page) and you need to import it
For creating a brand profile from scratch (no existing style guide), use /contentforge:brand-setup with interactive mode.
For using an existing brand profile, just reference it by name in /contentforge:create-content --brand=BrandName.
What This Command Does
- Load Style Guide — Fetch style guide from URL (via WebFetch), parse .docx/.pdf document, or accept manual input
- Extract Voice Characteristics — Identify tone (authoritative, conversational, technical, witty), formality level (1-5), personality traits, and writing style patterns
- Identify Terminology — Parse approved terms, banned/prohibited terms, industry-specific jargon, preferred spellings, and acronym definitions
- Parse Compliance Requirements — Extract guardrails, required disclaimers, prohibited claims, regulatory requirements, and sensitivity guidelines
- Generate Brand Profile JSON — Create or update a structured JSON profile following the
brand-registry-template.json schema
- Save and Validate — Save profile to Google Drive (via MCP) or local cache using the brand-cache-manager pattern, and validate the profile works with the ContentForge pipeline
- Configure Tracking Backend — Choose where ContentForge tracks quality scores and delivers output files: Google Sheets + Drive, Airtable, or local filesystem
Required Inputs
Minimum Required:
- Brand Name — The name for this brand profile (used in
--brand= across all skills)
Style Guide Source (one of):
- URL — Public URL to a style guide page (Notion, Google Docs published link, website page, Confluence page)
- Document — Path to a .docx or .pdf style guide file
- Manual Input — Interactive mode where you provide voice/terminology/guardrails step by step
Import Scope:
- voice — Extract only voice and tone characteristics
- terminology — Extract only approved/banned terms
- guardrails — Extract only compliance requirements and guardrails
- all (default) — Extract everything: voice + terminology + guardrails
How to Use
Import from URL
/contentforge:cf-style-guide AcmeMed --source=https://acmemed.com/brand-guidelines
Import from Document
/contentforge:cf-style-guide AcmeMed --source=./AcmeMed-Style-Guide.docx
Import from Notion Page
/contentforge:cf-style-guide AcmeMed --source=https://www.notion.so/acme/Brand-Guidelines-abc123
Import Only Terminology
/contentforge:cf-style-guide AcmeMed --source=https://acmemed.com/terminology --scope=terminology
Import Only Guardrails (Compliance)
/contentforge:cf-style-guide AcmeMed --source=./compliance-requirements.pdf --scope=guardrails
Manual Input (No Document)
/contentforge:cf-style-guide AcmeMed --source=manual
Prompts you for:
- Voice & Tone (select from presets or describe)
- Formality level (1-5)
- Personality traits (3-5 adjectives)
- Approved terminology (comma-separated)
- Banned terminology (comma-separated)
- Guardrails and compliance requirements
Update Existing Profile
/contentforge:cf-style-guide AcmeMed --source=https://acmemed.com/updated-guidelines --update
Merges new information into the existing profile without overwriting unchanged fields.
What Happens
Step 0: Check Drive for existing brand profile (v3.12.10+, Cowork only)
Before parsing any new source, check whether this brand already has a profile saved in Drive from a previous session. This is critical in Cowork because the sandbox FS is recycled — without this check, every Cowork session would re-create the same brand from scratch.
python {scripts_dir}/drive-sync-state.py --action read-config
If the config returns configured: false OR environment != "cowork-sandbox", skip to Step 1 (this is the local-mode flow).
If the config returns configured: true AND a Drive MCP is available in your tool list:
- Use the Drive MCP to search for
{drive_root_folder_name}/_brands/{brand-slug}/profile.json
- If found:
- If not found in Drive: proceed to Step 1 (normal creation flow). After Step 6 (Save and Validate), upload the new profile to Drive (Step 6.5 below).
Step 6.5: Push new profile to Drive (v3.12.10+, Cowork only)
After Step 6 saves the profile locally, check if it needs uploading:
python {scripts_dir}/drive-sync-state.py --action profile-needs-upload --brand "{brand}"
If needs_upload: true AND Cowork+Drive is configured AND a Drive MCP is available:
- Use the Drive MCP to upload
~/.claude-marketing/{brand-slug}/Brand-Guidelines/{BrandName}-brand-profile.json to {drive_root}/_brands/{brand-slug}/profile.json (create the folder structure if missing).
- Capture the returned Drive file ID and URL.
- Mark synced:
python {scripts_dir}/drive-sync-state.py --action profile-mark-uploaded \
--brand "{brand}" --drive-file-id "<id>" --drive-url "<url>"
- Tell the user: "Brand profile saved to Drive:
{drive_url} (persists across sessions and is team-shareable)."
If local-mode (no Cowork config), skip — the profile is fine where it is on the host filesystem.
Step 1: Load Style Guide Source (1-2 minutes)
From URL:
- Fetch page content using WebFetch
- Convert HTML to structured text
- Identify sections by heading hierarchy (H1/H2/H3)
- Handle multi-page style guides (follow pagination or table of contents links)
From Document (.docx/.pdf):
- Parse document structure (headings, paragraphs, lists, tables)
- Extract text with formatting context (bold = emphasis, tables = structured data)
- Handle multi-section documents with table of contents
From Manual Input:
- Interactive prompts for each profile section
- Provide examples and presets for each field
- Allow free-text input for complex requirements
Example:
Style Guide Loaded
================================================================
Source: https://acmemed.com/brand-guidelines
Page Title: "AcmeMed Brand Voice & Content Guidelines"
Sections Found: 8
1. Brand Overview
2. Voice & Tone
3. Writing Style
4. Approved Terminology
5. Banned Terms & Phrases
6. Regulatory Compliance
7. Visual Identity (skipped — not relevant to content)
8. Social Media Guidelines
Content Length: 4,200 words
Parsing: Complete
================================================================
Step 2: Extract Voice Characteristics (1-2 minutes)
Analyze the style guide to identify voice and tone patterns.
Extraction Categories:
Tone:
- Primary tone: authoritative, conversational, technical, witty, empathetic, inspiring
- Secondary tone: (optional, for nuance)
- Tone variations by content type (e.g., blog = conversational, whitepaper = authoritative)
Formality Level (1-5):
1 = Very Casual (slang OK, first person, contractions)
2 = Casual (contractions OK, approachable, some humor)
3 = Balanced (professional but warm, contractions selective)
4 = Formal (no contractions, third person preferred, structured)
5 = Very Formal (academic, no contractions, passive voice OK)
Personality Traits (3-5 adjectives):
- Extracted from explicit statements ("Our brand is...") or inferred from examples
- Examples: data-driven, empathetic, innovative, trustworthy, bold
Writing Style Patterns:
- Sentence length preference (short/medium/long)
- Paragraph length preference
- Use of rhetorical questions
- Active vs passive voice preference
- First/second/third person preference
- Use of statistics and data
- Storytelling style
Example Output:
Voice Characteristics Extracted
================================================================
Tone:
Primary: Authoritative
Secondary: Empathetic
By Content Type:
Article: Authoritative + data-driven
Blog: Authoritative + approachable
Whitepaper: Authoritative + academic
Formality: 4 (Formal)
No contractions in articles/whitepapers
Contractions OK in blog posts only
Personality Traits: data-driven, trustworthy, innovative, empathetic, precise
Writing Style:
Sentence Length: Medium (15-25 words average)
Paragraphs: 3-5 sentences
Voice: Active (90%+)
Person: Third person for articles, second person for blogs
Rhetorical Questions: Sparingly (1-2 per piece max)
Statistics: Heavy use, always cited
Storytelling: Patient stories as examples (anonymized)
Confidence: 92% (style guide was explicit about most elements)
================================================================
Step 3: Identify Terminology (1-2 minutes)
Parse approved and banned terminology from the style guide.
Terminology Categories:
Approved Terms:
- Brand-specific terminology (proprietary terms, product names)
- Industry-standard terms (preferred over alternatives)
- Preferred spellings (healthcare vs health care, e-health vs eHealth)
- Acronym definitions (with expansion rules)
Banned Terms:
- Competitor names or products
- Outdated terminology
- Insensitive or non-inclusive language
- Overpromising terms (for regulated industries)
- AI telltale phrases (if specified in guide)
Conditional Terms:
- Terms allowed in some contexts but not others
- Terms requiring disclaimers or qualifiers
Example Output:
Terminology Extracted
================================================================
Approved Terms (47 total):
Brand Terms:
"AcmeMed" (never "Acme Med" or "ACMEMED")
"AcmeDiagnostics" (product name, always capitalized)
"AcmeCare Platform" (full name on first use, "the Platform" after)
Industry Terms:
"healthcare" (one word, not "health care")
"precision medicine" (preferred over "personalized medicine")
"clinical decision support" (preferred over "clinical AI")
"value-based care" (preferred over "value-driven care")
Acronyms:
"AI" — Artificial Intelligence (expand on first use)
"EMR" — Electronic Medical Record (expand on first use)
"HIPAA" — never expand (universally known in target audience)
Banned Terms (23 total):
"revolutionary" — overpromising, use "innovative" instead
"breakthrough" — overpromising, use "advancement" instead
"cure" — regulatory risk, use "treatment" or "therapy"
"guaranteed" — compliance violation in healthcare
"CompetitorX", "CompetitorY" — no competitor mentions
"patients love it" — unsubstantiated claim
"cutting-edge" — cliche, use specific technology descriptions
... (16 more)
Conditional Terms (8 total):
"FDA-cleared" — only for products with actual FDA clearance
"clinically validated" — only with citation to clinical trial
"reduces costs" — only with specific percentage and source
================================================================
Step 4: Parse Compliance Requirements (1-2 minutes)
Extract guardrails, disclaimers, and regulatory requirements.
Guardrail Categories:
Required Disclaimers:
- Legal disclaimers to include in specific content types
- Industry-specific disclaimers (e.g., "This is not medical advice")
- Regional disclaimers (jurisdiction-specific requirements)
Prohibited Claims:
- Claims that cannot be made without specific evidence
- Absolute claims ("best", "only", "first") without qualification
- Efficacy claims without clinical data
- Pricing claims without current verification
Compliance Rules:
- HIPAA requirements for patient data references
- FDA guidelines for product claims
- FTC requirements for endorsements
- Industry-specific regulations
Sensitivity Guidelines:
- Patient privacy (no identifiable information)
- Cultural sensitivity requirements
- Disability-inclusive language
- Age-appropriate content guidelines
Example Output:
Compliance Requirements Extracted
================================================================
Required Disclaimers (4):
1. All articles: "This content is for informational purposes only
and does not constitute medical advice."
2. Product mentions: "AcmeDiagnostics is pending FDA clearance
for [specific use case]." (update status quarterly)
3. Patient stories: "Patient names and identifying details have
been changed to protect privacy."
4. Clinical data: "Results may vary. Clinical outcomes depend
on individual patient factors."
Prohibited Claims (6):
1. No efficacy claims without peer-reviewed citation
2. No "FDA-approved" (use "FDA-cleared" for 510(k) devices)
3. No cost savings claims without specific study reference
4. No comparison claims vs competitors
5. No absolute claims ("best", "only", "first") without qualification
6. No patient testimonials as efficacy evidence
Compliance Rules:
HIPAA: Never include PHI (Protected Health Information)
FDA: Follow 510(k) promotional guidelines for device content
FTC: Disclose any sponsored or partnership content
Sensitivity Guidelines:
Language: Person-first (e.g., "patients with diabetes" not "diabetics")
Imagery descriptions: Diverse, inclusive, respectful
Avoid: Military metaphors for disease ("battle cancer", "fight disease")
Confidence: 96% (compliance section was highly structured)
================================================================
Step 5: Generate Brand Profile JSON (1 minute)
Create the structured JSON profile.
Schema — follow config/brand-registry-template.json exactly. Its top-level sections are:
brand_name, industry, company_info, voice, terminology, citation_rules, guardrails, content_patterns, seo_preferences, target_audience, quality_thresholds, tracking, google_integration, knowledge_vault_config, data_sources, output_preferences, visual_identity, content_pillars, competitor_analysis, notification_preferences, metadata.
Fill the sections your import scope covers; leave the rest as template defaults. The excerpt below shows only the sections this skill populates — it is not the full schema.
SYNTHETIC EXAMPLE (excerpt):
{
"brand_name": "AcmeMed",
"industry": "Healthcare",
"voice": {
"primary_tone": "authoritative",
"secondary_tone": "empathetic",
"formality_level": 4,
"personality_traits": ["data-driven", "trustworthy", "innovative", "empathetic", "precise"],
"tone_by_content_type": {
"article": "authoritative + data-driven",
"blog": "authoritative + approachable",
"whitepaper": "authoritative + academic",
"faq": "clear + helpful",
"research_paper": "academic + precise"
}
},
"content_patterns": {
"sentence_length": "medium",
"paragraph_length": "3-5 sentences",
"active_voice_target": 90,
"person": {
"article": "third",
"blog": "second",
"whitepaper": "third"
},
"contractions": {
"article": false,
"blog": true,
"whitepaper": false
},
"rhetorical_questions": "sparingly",
"statistics_usage": "heavy",
"storytelling": "patient stories, anonymized"
},
"terminology": {
"approved": [
{"term": "AcmeMed", "note": "Never 'Acme Med' or 'ACMEMED'"},
{"term": "healthcare", "note": "One word, not 'health care'"},
{"term": "precision medicine", "note": "Preferred over 'personalized medicine'"}
],
"banned": [
{"term": "revolutionary", "replacement": "innovative"},
{"term": "breakthrough", "replacement": "advancement"},
{"term": "cure", "replacement": "treatment or therapy"},
{"term": "guaranteed", "note": "Compliance violation in healthcare"}
],
"conditional": [
{"term": "FDA-cleared", "condition": "Only for products with actual FDA clearance"},
{"term": "clinically validated", "condition": "Only with citation to clinical trial"}
],
"acronyms": [
{"acronym": "AI", "expansion": "Artificial Intelligence", "expand_on_first_use": true},
{"acronym": "HIPAA", "expansion": "Health Insurance Portability and Accountability Act", "expand_on_first_use": false}
]
},
"guardrails": {
"required_disclaimers": [
{"context": "all_articles", "text": "This content is for informational purposes only and does not constitute medical advice."},
{"context": "product_mentions", "text": "AcmeDiagnostics is pending FDA clearance for [specific use case]."}
],
"prohibited_claims": [
"No efficacy claims without peer-reviewed citation",
"No 'FDA-approved' — use 'FDA-cleared' for 510(k) devices",
"No cost savings claims without specific study reference"
],
"compliance": {
"hipaa": "Never include PHI",
"fda": "Follow 510(k) promotional guidelines",
"ftc": "Disclose sponsored or partnership content"
},
"sensitivity": {
"language": "person-first",
"avoid_metaphors": ["military metaphors for disease"],
"inclusivity": "diverse, respectful, representative"
}
},
"metadata": {
"industry": "Healthcare",
"sub_industry": "Health Technology / Medical Devices",
"target_audiences": ["Healthcare Executives", "Clinical Decision Makers", "Health System IT Leaders"],
"content_types_supported": ["article", "blog", "whitepaper", "faq", "research_paper"],
"import_confidence": 94
}
}
Step 6: Save and Validate (1 minute)
Save Profile:
- Local (canonical path):
~/.claude-marketing/{brand-slug}/Brand-Guidelines/{BrandName}-brand-profile.json — this is the path every other ContentForge skill reads
- Google Drive (Cowork mode, via MCP):
{drive_root}/_brands/{brand-slug}/profile.json (see Step 6.5)
- Notion (MCP, optional): additionally save to a brand database in the Notion workspace for team visibility
Validation Checks:
- Profile JSON is valid and parseable
- All required fields are present
- Terminology lists are non-empty
- Pipeline compatibility test: run a mock Phase 5 (brand compliance check) with a test paragraph
Example Validation:
Brand Profile Validation
================================================================
Profile: AcmeMed v1.0.0
JSON Valid: Yes
Required Fields: 12/12 present
Voice Complete: Yes (tone, formality, personality, style)
Terminology: 47 approved, 23 banned, 8 conditional
Guardrails: 4 disclaimers, 6 prohibited claims, 3 compliance rules
Acronyms: 12 defined
Pipeline Compatibility Test:
Phase 3 (Drafting): Can apply voice settings — PASS
Phase 5 (Brand Compliance): Can check terminology — PASS
Phase 6 (SEO): No conflicts with SEO settings — PASS
Phase 6.5 (Humanizer): Can apply personality — PASS
Profile Saved:
Local: ~/.claude-marketing/acmemed/Brand-Guidelines/AcmeMed-brand-profile.json
Drive (Cowork mode): <drive_root>/_brands/acmemed/profile.json
Cache Hash: SHA256:a3f2c1... (for fast cache lookup)
Status: READY — Profile can be used with /contentforge:create-content --brand=AcmeMed
================================================================
Step G: Tracking & Delivery Backend (1-2 minutes)
Choose where ContentForge tracks quality scores and delivers output files. This step configures the tracking section of the brand profile.
Step G.0 — Probe environment + existing config FIRST
Before offering the three-option menu, run two probes (same flow as commands/brand-setup.md, which is the canonical brand-setup document):
python scripts/plugin-metadata.py --section environment
python scripts/detect-drive-mcp.py
- If
environment == "cowork-sandbox": the "Local" backend writes to the ephemeral Linux sandbox — files vanish at session end. A Drive route (Anthropic platform integration or a Pipedream/Composio/Zapier/Make Drive aggregator MCP) is effectively REQUIRED for persistent output. If a Drive MCP is visible in your tool list, confirm and use it (skip the menu). If not, warn the user and point them to Cowork → Settings → Integrations → Google Drive, or /contentforge:cf-cowork-setup.
- If
detect-drive-mcp.py returns recommended_path: "mcp": confirm the detected connector and go straight to the MCP-based Drive route — skip the service-account flow.
- If it returns
recommended_path: "service_account": confirm the found credentials (client_email) and use the service-account route.
- If both are present: ask which to use; default to MCP (simpler auth, Cowork-compatible).
- If
recommended_path: "none" in local Claude Code: show the three-option menu below (Local is a fine default on a real host filesystem).
Present the user with three options (only when G.0 found nothing):
Step G: Tracking & Delivery Backend
================================================================
Choose where ContentForge tracks quality scores and delivers
output files for this brand:
1. Google Sheets + Drive (Recommended if you have Google Workspace)
Tracks in Google Sheets, delivers .docx to Google Drive
Requires: Service account credentials (~5 min setup)
2. Airtable (Recommended for simplicity)
Tracks in Airtable, delivers .docx as record attachments
Requires: Personal Access Token (~2 min setup)
3. Local (No setup required)
Tracks in local JSON, delivers .docx to local filesystem
No auth needed, but no cloud access or collaboration
Your choice: ___
================================================================
If user picks Google Sheets + Drive:
- Check if Google credentials already exist at
~/.claude-marketing/google-credentials.json
- If not, guide through service account setup:
- Create a GCP project at console.cloud.google.com
- Enable Google Sheets API and Google Drive API
- Create a service account and download the JSON key file
- Save to
~/.claude-marketing/google-credentials.json
- Share the target Google Sheet and Drive folder with the service account email
- Ask for the Google Sheet ID (from the Sheet URL)
- Ask for the Google Drive folder ID (from the folder URL)
- Set in brand profile:
"tracking": {
"backend": "google_sheets",
"google_sheets": {
"sheet_id": "{user-provided}",
"tab_name": "ContentForge Tracking",
"credentials_path": "~/.claude-marketing/google-credentials.json"
},
"google_drive": {
"folder_id": "{user-provided}",
"credentials_path": "~/.claude-marketing/google-credentials.json"
}
}
- Run
python {scripts_dir}/sheets-tracker.py --action init --sheet-id {sheet_id} to create the tracking schema
If user picks Airtable:
- Check if
AIRTABLE_TOKEN environment variable exists
- If not, guide through token creation:
- Go to airtable.com/create/tokens
- Create a Personal Access Token with
data.records:read, data.records:write, schema.bases:read, schema.bases:write scopes
- Select the target base (or create a new one)
- Set the token as
AIRTABLE_TOKEN environment variable
- Ask for the Airtable Base ID (from the base URL:
airtable.com/{base_id}/...)
- Set in brand profile:
"tracking": {
"backend": "airtable",
"airtable": {
"base_id": "{user-provided}",
"table_name": "ContentForge Tracking"
}
}
- Run
python {scripts_dir}/airtable-tracker.py --action init --base-id {base_id} to create the tracking table with schema
If user picks Local:
- No setup required
- Set in brand profile:
"tracking": {
"backend": "local",
"local": {
"tracking_dir": "~/.claude-marketing/{brand}/tracking"
}
}
- Run
python {scripts_dir}/local-tracker.py --action init --brand "{brand}" to create the tracking directory and initial tracking.json
If user skips Step G (presses enter without choosing or says "skip"):
Example Output:
Tracking Backend Configured
================================================================
Backend: Airtable
Base ID: appXXXXXXXXXXXXXX
Table: ContentForge Tracking (created with 20-column schema)
Token: AIRTABLE_TOKEN detected
Tracking table initialized with columns:
requirement_id, brand, content_type, title, target_audience,
word_count_target, priority, status, created_at, started_at,
completed_at, quality_score, content_quality, citation_integrity,
brand_compliance, seo_performance, readability, actual_word_count,
output_file (Attachment), notes
To switch backends later: /contentforge:cf-switch-backend
================================================================
Step 7: Audience Personas
Ask the user about their target audience:
Who is the primary audience for this brand's content?
Please provide:
1. Job title/role (e.g., "VP of Engineering", "Marketing Manager", "Small business owner")
2. Industry/company size (e.g., "Enterprise SaaS, 1000+ employees")
3. Reading level (executive summary / professional / technical / general public)
4. Key pain points (what problems are they trying to solve?)
5. Goals (what outcomes do they want from reading your content?)
Optional: Secondary audience(s) if the brand targets multiple personas.
Store in target_audience.primary_persona with fields: title, industry, company_size, reading_level, pain_points (array), goals (array).
If user skips: Set target_audience.primary_persona to default generic persona and log warning.
Step 8: Competitor Analysis
Ask the user about competitors:
Who are your top 3-5 content competitors?
These are brands whose content ranks for the same keywords or targets the same audience.
For each competitor, provide:
- Name and URL
- What they do well in content (e.g., "great technical depth", "strong SEO")
- What they miss or do poorly (e.g., "no video content", "outdated stats")
This helps ContentForge differentiate your content from theirs.
Store in competitor_analysis.top_competitors array. Each entry: name, url, content_strengths (array), content_gaps (array).
If user skips: Leave empty but note: "Competitor analysis skipped — Phase 1 Research will still analyze SERP competitors, but won't have your strategic differentiation context."
Step 9: Content Pillars
Ask the user about content strategy:
What are your brand's core content pillars (topic areas you want to own)?
Examples:
- "AI in Healthcare" — our flagship thought leadership topic
- "Product Tutorials" — how-to content for our platform
- "Industry Trends" — quarterly market analysis
List 3-5 pillars with a brief description and target keywords for each.
Store in content_pillars array. Each entry: name, description, keywords (array), content_types (array).
If user skips: Leave empty. Content will be produced without pillar context.
Step 10: Visual Identity
Ask the user about brand visuals:
What are your brand's visual identity elements?
1. Brand colors:
- Primary color (hex, e.g., #0066CC)
- Secondary color (hex)
- Accent color (hex, optional)
2. Preferred image style: photorealistic / illustration / flat design / mixed
3. Logo description (brief text description — we don't store image files)
These are used for chart generation (Phase 3.5) and AI image prompts.
Store in visual_identity with fields: brand_colors (primary, secondary, accent), image_style, logo_description.
If user skips: Use defaults (primary: #0066CC, secondary: #FF6600) and note in profile.
Output
The style guide import produces:
| Output | Description |
|---|
| Brand Profile JSON | Structured profile following brand-registry-template.json schema |
| Voice Summary | Human-readable summary of tone, formality, personality, style |
| Terminology Count | Total approved, banned, and conditional terms extracted |
| Guardrails List | Disclaimers, prohibited claims, compliance rules |
| Validation Status | Pipeline compatibility test results |
| Save Location | Where the profile was saved (Drive, Notion, local) |
Output Example
Style Guide Import Complete
================================================================
Brand: AcmeMed
Source: https://acmemed.com/brand-guidelines
Import Scope: All (voice + terminology + guardrails)
Processing Time: 6 minutes
Results:
Voice: Authoritative + Empathetic, Formality 4/5
Personality: data-driven, trustworthy, innovative, empathetic, precise
Terminology: 47 approved, 23 banned, 8 conditional, 12 acronyms
Guardrails: 4 disclaimers, 6 prohibited claims, 3 compliance rules
Audience: {persona_title} at {company_size} ({reading_level})
Competitors: {count} competitors analyzed
Content Pillars: {count} pillars defined
Visual Identity: {primary_color} / {secondary_color} | Style: {image_style}
Import Confidence: 94%
Validation: PASS (all pipeline phases compatible)
Saved to:
Local: ~/.claude-marketing/acmemed/Brand-Guidelines/AcmeMed-brand-profile.json
Drive (Cowork mode): <drive_root>/_brands/acmemed/profile.json
Use with: /contentforge:create-content --brand=AcmeMed
================================================================
MCP Integrations
Optional (HTTP)
- Notion — Save brand profile to a Notion database for team-wide access and collaborative editing. Import style guides from Notion pages.
- Google Drive — Save brand profile JSON to Drive for shared access and backup. Read existing profiles from Drive.
Fallback (No MCP)
Without MCP connections, profiles are saved to the canonical local path ~/.claude-marketing/{brand-slug}/Brand-Guidelines/{BrandName}-brand-profile.json. Profiles can be manually shared by copying the JSON file. URL-based style guide import uses WebFetch (built-in), which works without any MCP connection.
Troubleshooting
"Could not extract voice characteristics"
Cause: Style guide doesn't have explicit voice/tone section, or the page structure is too unstructured.
Solution: Use --source=manual to provide voice characteristics interactively, then import terminology and guardrails from the document separately.
"0 approved terms found"
Cause: Terminology is embedded in prose rather than structured lists.
Solution: Check if the style guide has a terminology table or glossary section. If not, use --source=manual --scope=terminology to add terms interactively.
"URL fetch failed"
Cause: Page requires authentication (private Notion, Google Doc not published, login-required page).
Solution: If the page is in Notion, use the Notion MCP to access it instead of URL fetch. For Google Docs, use the published web link (File > Share > Publish to Web). For login-required pages, download the page as .docx or .pdf and use the document source.
"Profile validation failed — Phase 5 incompatible"
Cause: Terminology lists contain conflicts (same term in approved and banned lists) or the profile JSON is malformed.
Solution: Review the profile JSON for conflicts. Use --update mode to fix specific fields without reimporting the entire guide.
"Import confidence below 70%"
Cause: Style guide was vague, lacked structure, or covered primarily visual identity (not content voice).
Solution: Supplement with manual input for low-confidence sections. The profile will flag which sections have low confidence so you know what to manually verify.
Limitations
- PDF parsing can miss complex layouts (multi-column, heavy formatting). For best results, convert to .docx first.
- Non-English style guides are processed but terminology extraction is less accurate outside English
- Implicit voice — If a style guide shows examples but doesn't explicitly state voice characteristics, extraction confidence will be lower
- Visual identity sections (logos, colors, fonts) are skipped — this tool focuses on content voice only
- Maximum document size: 50 pages / 25,000 words (larger documents should be split into sections)
Agent Used
None. This skill uses deterministic parsing (document structure analysis, pattern matching for terminology, rule extraction for guardrails) combined with WebFetch for URL-based sources. No agent-based reasoning is needed since the extraction follows structured patterns.
Related Skills
Agent: None (deterministic parsing)
MCP: Google Drive (optional via Anthropic platform integration / Pipedream / Composio / Zapier / Make aggregator), Notion (optional)
Output: Brand profile JSON at ~/.claude-marketing/{brand-slug}/Brand-Guidelines/{BrandName}-brand-profile.json, voice summary, terminology count, guardrails list, validation status, tracking backend config
