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context-engine
Load brand context for marketing tasks. Use when: setting up brands, switching context, or needing industry benchmarks.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Load brand context for marketing tasks. Use when: setting up brands, switching context, or needing industry benchmarks.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Design A/B and multivariate tests. Use when: sample size calculation, testing hypothesis, CRO experimentation.
Generate platform-specific ad copy. Use when: Google RSA, Meta, LinkedIn, TikTok ad variations with quality scoring.
Audit AI search visibility. Use when: checking brand presence in ChatGPT, Perplexity, AI Overviews, Gemini.
Optimize AI engine visibility. Use when: AEO/GEO strategy, citation optimization, entity consistency across AI platforms.
Portfolio-level agency dashboard aggregating health metrics across all client brands — campaign status, budget pacing, KPI attainment, team utilization. Use when reviewing cross-brand portfolio health, preparing for agency leadership standups, or getting a single-view snapshot of all client accounts.
Analyze marketing performance. Use when: KPI frameworks, attribution modeling, anomaly investigation, measurement strategy.
| name | context-engine |
| description | Load brand context for marketing tasks. Use when: setting up brands, switching context, or needing industry benchmarks. |
| argument-hint | [brand-slug] |
This skill loads and manages:
~/.claude-marketing/brands/)industry-profiles.md)compliance-rules.md)platform-specs.md)scoring-rubrics.md)~/.claude-marketing/brands/_active-brand.json for the currently active brand~/.claude-marketing/brands/{slug}/profile.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": ""
}
}
When user says "switch to [brand name]":
python "${CLAUDE_PLUGIN_ROOT}/scripts/setup.py" --switch-brand SLUG_active-brand.jsonOr use: /digital-marketing-pro:switch-brand
Every module should:
target_markets and industry.regulation_codesadaptive-scorer.py to get brand-specific weights before content scoringcampaign-tracker.py to persist plans, performance, and insightsThe following types trigger different funnel models, KPI frameworks, and channel strategies:
B2B_SaaS — MRR/ARR focused, product-led or sales-led growthB2C_eCommerce — ROAS focused, product catalog marketingB2C_DTC — Direct-to-consumer brand building + performanceB2B_Services — Thought leadership, long sales cyclesLocal_Business — Google Business Profile, local SEO, reviewsAgency — Multi-client management, white-label outputsCreator — Personal brand, audience building, monetizationEnterprise — ABM, buying committees, complex salesNon_Profit — Donor acquisition, awareness, advocacyMarketplace — Two-sided acquisition, liquidity, trustThe brand voice scorer (brand-voice-scorer.py) automatically normalizes profile data:
brand_voice.formality (1-10 int scale) → converts to 0.0-1.0 float internallybrand_voice.prefer_words → preferred_words, brand_voice.avoid_words → avoided_wordsCampaign 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.
When MCP servers are configured (in .mcp.json), modules can pull real data:
All MCP servers connect to the USER'S OWN accounts via their API keys.