context-engine
Load brand context for marketing tasks. Use when: setting up brands, switching context, or needing industry benchmarks.
What this skill does
# Context Engine — Shared Marketing Intelligence
## When to Use This Skill
- User is setting up a new brand or project for marketing
- User switches between brands/clients (agency use case)
- Any other marketing skill needs brand context, industry data, compliance rules, or platform specs
- User asks about industry benchmarks, platform requirements, or regulatory compliance
## Required Context
This skill loads and manages:
1. **Brand Profile** — identity, voice, audiences, competitors, goals (from `~/.claude-marketing/brands/`)
2. **Industry Profiles** — benchmarks, KPIs, channel effectiveness per industry (see `industry-profiles.md`)
3. **Compliance Rules** — geographic privacy laws + industry regulations (see `compliance-rules.md`)
4. **Platform Specs** — character limits, image sizes, algorithm signals per platform (see `platform-specs.md`)
5. **Scoring Rubrics** — standardized evaluation criteria for all content types (see `scoring-rubrics.md`)
## Brand Profile Management
### Loading a Brand
1. Check `~/.claude-marketing/brands/_active-brand.json` for the currently active brand
2. If active brand exists, load `~/.claude-marketing/brands/{slug}/profile.json`
3. If no active brand, prompt: "No active brand configured. Run /digital-marketing-pro:brand-setup to create one, or tell me about your brand and I'll help set it up."
### Brand Profile Schema
```json
{
"brand_name": "",
"brand_slug": "",
"created_at": "",
"updated_at": "",
"schema_version": "1.0.0",
"identity": {
"tagline": "",
"mission": "",
"vision": "",
"values": [],
"unique_selling_proposition": "",
"positioning_statement": "",
"elevator_pitch": ""
},
"business_model": {
"type": "",
"revenue_model": "",
"price_range": "",
"sales_cycle_length": "",
"average_deal_size": "",
"customer_lifetime_value": ""
},
"industry": {
"primary": "",
"secondary": [],
"regulated": false,
"regulation_codes": [],
"compliance_notes": ""
},
"target_markets": [],
"brand_voice": {
"formality": 5,
"energy": 5,
"humor": 3,
"authority": 5,
"personality_traits": [],
"tone_keywords": [],
"avoid_words": [],
"prefer_words": [],
"this_not_that": [],
"sample_content": []
},
"channels": {
"active": [],
"primary": "",
"handles": {}
},
"competitors": [],
"goals": {
"primary_objective": "",
"kpis": [],
"budget_range": "",
"team_size": ""
}
}
```
### Switching Brands
When user says "switch to [brand name]":
1. Run: `python "scripts/setup.py" --switch-brand SLUG`
2. The script handles fuzzy matching, validation, and updates `_active-brand.json`
3. Confirm: "Switched to [brand_name]. All marketing outputs will now use this brand's voice, compliance rules, and context."
Or use: `/digital-marketing-pro:switch-brand`
## How Other Modules Use This Skill
Every module should:
1. Check if an active brand exists before producing marketing outputs
2. Load relevant industry profile for benchmarks and channel recommendations
3. Auto-apply compliance rules based on brand's `target_markets` and `industry.regulation_codes`
4. Reference platform specs when creating platform-specific content
5. Use scoring rubrics when evaluating or grading content quality
6. Use **adaptive scoring** — run `adaptive-scorer.py` to get brand-specific weights before content scoring
7. **Save campaign data** — use `campaign-tracker.py` to persist plans, performance, and insights
8. **Check past campaigns** — before making recommendations, check if similar campaigns exist in brand history
## Business Model Types
The following types trigger different funnel models, KPI frameworks, and channel strategies:
- `B2B_SaaS` — MRR/ARR focused, product-led or sales-led growth
- `B2C_eCommerce` — ROAS focused, product catalog marketing
- `B2C_DTC` — Direct-to-consumer brand building + performance
- `B2B_Services` — Thought leadership, long sales cycles
- `Local_Business` — Google Business Profile, local SEO, reviews
- `Agency` — Multi-client management, white-label outputs
- `Creator` — Personal brand, audience building, monetization
- `Enterprise` — ABM, buying committees, complex sales
- `Non_Profit` — Donor acquisition, awareness, advocacy
- `Marketplace` — Two-sided acquisition, liquidity, trust
## Brand Voice Scoring
The brand voice scorer (`brand-voice-scorer.py`) automatically normalizes profile data:
- Reads `brand_voice.formality` (1-10 int scale) → converts to 0.0-1.0 float internally
- Maps `brand_voice.prefer_words` → `preferred_words`, `brand_voice.avoid_words` → `avoided_words`
- Supports both the full profile schema (from brand-setup) and legacy direct schemas
## Data Persistence
Campaign data, performance snapshots, and marketing insights persist across sessions:
```
~/.claude-marketing/brands/{slug}/
├── campaigns/ # Campaign plans and post-mortems
│ ├── _index.json # Campaign index for quick lookup
│ └── {id}.json # Individual campaign data
├── performance/ # Performance snapshots over time
│ └── {campaign}-{date}.json
├── insights.json # Marketing learnings (last 200)
├── content-library/ # Saved content pieces
└── voice-samples/ # Brand voice reference content
```
Use `campaign-tracker.py` for all persistence operations.
## MCP Integrations
When MCP servers are configured (in `.mcp.json`), modules can pull real data:
- **Google Analytics** → actual traffic/conversion data for performance reports
- **Google Search Console** → real ranking data for SEO audits
- **Google Ads / Meta** → live campaign performance for paid advertising
- **HubSpot** → CRM data for funnel analysis
- **Mailchimp** → email campaign metrics
- **Google Sheets** → export reports and calendars
All MCP servers connect to the USER'S OWN accounts via their API keys.
## Reference Files
- **industry-profiles.md** — 20+ industry profiles with benchmarks, channels, compliance, content types
- **compliance-rules.md** — Geographic privacy laws (16 jurisdictions) + industry regulations (10+ sectors)
- **platform-specs.md** — Social media, email, and ad platform specifications
- **scoring-rubrics.md** — Content quality, ad creative, email, and landing page scoring criteria
- **intelligence-layer.md** — How the adaptive intelligence system works (scoring, learning, persistence)
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