Context Engine

---
name: context-engine
description: Invoke when setting up a new brand, switching brands, or when any marketing task requires brand context, industry benchmarks, compliance rules, or platform specifications. This is the shared intelligence layer for all Digital Marketing Pro modules.
---

# 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 /dm: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: `/dm: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)