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Agent skill

Context Engine

by indranilbanerjee in indranilbanerjee/digital-marketing-pro

Load and manage the shared marketing context other skills build on — the active brand profile (voice, audiences, competitors, goals), industry benchmark profiles, geographic and industry compliance…

MITAuto-check passedEducation

Install Context Engine

skills CLI
$ npx skills add indranilbanerjee/digital-marketing-pro --skill context-engine -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install indranilbanerjee/digital-marketing-pro context-engine --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-pro.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/context-engine .claude/skills/context-engine && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
context-engine
GitHub stars
855
Used in
1 other repo
Token cost
~3.2k tokens
SKILL.md length
1,112 words
Files
57
Skills in repo
162
Repo updated
First seen
Licence
MIT

At a glance

Load and manage the shared marketing context other skills build on — the active brand profile (voice, audiences, competitors, goals), industry benchmark profiles, geographic and industry compliance…

  • Works in 5 steps: Brand Profile — identity, voice,… → Industry Profiles — benchmarks, KPIs,… → Compliance Rules — geographic privacy… → …
  • /digital-marketing-pro:context-engine
  • SKILL.md covers When to Use This Skill, Required Context, Brand Profile Management and How Other Modules Use This Skill, plus 5 more sections
  • Calls python

What it does

Context Engine is an agent skill from indranilbanerjee/digital-marketing-pro. Load and manage the shared marketing context other skills build on — the active brand profile (voice, audiences, competitors, goals), industry benchmark profiles, geographic and industry compliance rules, platform specs, and scoring rubrics — plus brand switching and campaign-data persistence under ~/.claude-marketing/. Triggers on "/digital-marketing-pro:context-engine", "switch to brand X", "what are the benchmarks for my industry", "which compliance rules apply to us", "load my brand context". Pairs with…

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 56 other files (for example `30-60-90-framework.md`, `actionable-persona-format.md` and `advanced-reporting-guide.md`).

It sits in Education, covering Quizzes and assessments. The repository describes itself as: An open-source AI marketing operating system for strategy, SEO, AEO/GEO, paid media, content, CRM, and analytics - grounded in brand context, human approval, and verifiable… The licence is MIT.

When your agent uses it

  • /digital-marketing-pro:context-engine
  • Switch to brand X
  • What are the benchmarks for my industry
  • Which compliance rules apply to us

Example prompts

  • “/digital-marketing-pro:context-engine”
  • “switch to brand X”
  • “what are the benchmarks for my industry”
  • “/context-engine”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  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)

What it can do on your machine

Read from SKILL.md and the folder at commit 3343924. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Context Engine loads about 3.2k tokens when it runs. Until then it costs about 174 tokens; SKILL.md has 1,112 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~174
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from indranilbanerjee/digital-marketing-pro at commit 3343924, republished under its MIT licence (© indranilbanerjee). 1,112 words, ~3,236 tokens.

Download SKILL.mdSave it as .claude/skills/context-engine/SKILL.md (or your agent's skills folder). This skill also uses 56 other files; get the full folder from GitHub.
name
context-engine
description
Load and manage the shared marketing context other skills build on — the active brand profile (voice, audiences, competitors, goals), industry benchmark profiles, geographic and industry compliance rules, platform specs, and scoring rubrics — plus brand switching and campaign-data persistence under ~/.claude-marketing/. Triggers on "/digital-marketing-pro:context-engine", "switch to brand X", "what are the benchmarks for my industry", "which compliance rules apply to us", "load my brand context". Pairs with /digital-marketing-pro:brand-setup to create profiles and /digital-marketing-pro:switch-brand to change them; its reference files are read by nearly every sibling skill.
argument-hint
[brand-slug]

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 "${CLAUDE_PLUGIN_ROOT}/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

Core context & specs
  • industry-profiles.md — 20+ industry profiles with benchmarks, channels, compliance, content types
  • platform-specs.md — Social media, email, and ad platform specifications
  • platform-publishing-specs.md — API-level publishing requirements and content formats per platform (payloads, field mapping, validation)
  • google-seo-reference.md — Concise Google SEO quick reference (crawling/indexing/serving, surfaces, schema status, algorithm dates)
  • schema-templates.json — Ready-to-use JSON-LD schema templates with Google support/deprecation status
  • india-market-context.md — India regional market context: regulation (DPDP), platforms, and market dynamics
Show full SKILL.md (535 more words)Show less
Methodology frameworks
  • engagement-flow-methodology.md — The 12-Part sequential engagement methodology every command, skill, and agent reads back to
  • four-core-documents-spec.md — Full spec of the four Part 3 Core Documents (61 steps) that form the strategic spine
  • decision-matrix-rerun.md — Which Part 3/4 documents to re-run as v2 after Part 5 client validation
  • two-views-model.md — Keeping v1 (unbiased research) and v2 (client-validated) views authoritative for different questions
  • update-back-rule.md — Corrections land in the source document, not just the deliverable that caught the error
  • stone-vs-opinion.md — Confidence tagging of intake facts: verifiable Stone vs client Opinion
  • living-instruction-file-spec.md — Spec for the per-engagement Living Project Instruction File (single source of truth)
  • 30-60-90-framework.md — Default first-quarter phasing: Foundation / Optimization / Scale milestones
  • actionable-persona-format.md — Six-question persona format that replaces biographical narratives
  • b2b-decision-making-unit.md — B2B buying-committee roles overlay for every B2B persona
  • five-digital-markets.md — Strategic taxonomy of the five digital market types; market type determines channel
  • channel-families.md — Operational grouping of the 17 Part 9 channels into seven families
  • in-market-out-market.md — Budget split logic between in-market (3–5%) and out-market (95–97%) audiences
  • fixed-vs-variable-budget.md — Separating committed monthly spend from data-backed variable spend
  • unit-economics-framework.md — CAC/LTV foundation every channel and budget decision checks back to
  • three-scenario-forecasting.md — Every projection presented as conservative/expected/optimistic scenarios
  • decision-framework.md — Multi-dimensional decision framework: name, weight, and score every dimension
  • competitor-3-question-output.md — The three questions every competitor analysis must answer per competitor
Execution guides
  • execution-workflows.md — Standard operating procedures for publishing, sending, and launching marketing actions
  • seo-execution-guide.md — SEO execution via CMS APIs, search console ops, schema deployment, rank monitoring
  • geo-execution-guide.md — Generative Engine Optimization: AI visibility monitoring, entities, citations
  • multilingual-execution-guide.md — End-to-end multilingual campaign pipeline: translation services, RTL/Indic/CJK, SEO
  • transcreation-framework.md — Transcreation vs translation vs localization, with process and QA scoring
  • crm-integration-guide.md — CRM connection patterns, object mapping, and data sync (Salesforce, HubSpot, etc.)
  • custom-mcp-guide.md — Adding or building MCP servers beyond the opt-in connector catalog
  • self-healing-ops-guide.md — Automated campaign monitoring and correction within safety guardrails
  • approval-framework.md — Risk classification determining auto-execute vs explicit-approval flows
  • agency-operations-guide.md — Multi-client SOPs: onboarding, portfolio health, credential isolation, white-labeling
  • team-roles-framework.md — Team roles, permissions, approval chains, and capacity planning
  • guidelines-framework.md — How brand guidelines, restrictions, and style rules are structured and enforced
Compliance & EU
  • compliance-rules.md — Geographic privacy laws (16 jurisdictions) + industry regulations (10+ sectors)
  • eu-code-of-practice.md — EU Code of Practice on AI-generated content + AI Act Article 50 obligations for marketers
Templates & rubrics
  • scoring-rubrics.md — Content quality, ad creative, email, and landing page scoring criteria
  • eval-rubrics.md — Detailed scoring rubrics for the six eval dimensions used by eval-runner.py
  • eval-framework-guide.md — Architecture and usage of the automated six-dimension content QA pipeline
  • growth-plan-template.md — Flagship Part 8 client-facing Growth Plan deliverable template
  • yearly-planner-template.md — Part 8 twelve-month operating calendar template
  • monthly-report-template.md — Decision-driving monthly client report structure
  • reporting-cadence.md — Matching metric review frequency (daily→quarterly) to decision velocity
  • advanced-reporting-guide.md — PDF report generation, dashboards, attribution, cohort and variance reporting
Intelligence & memory
  • intelligence-layer.md — How the adaptive intelligence system works (scoring, learning, persistence)
  • memory-architecture.md — The 5-layer persistent brand knowledge system
  • compound-intelligence-guide.md — Intelligence graph that makes each decision better than the last
  • creative-intelligence-guide.md — Creative fatigue prediction, content decay, and refresh prioritization
  • market-intelligence-guide.md — Macro signal detection: economic indicators, market timing, regulatory tracking
  • competitive-monitoring-guide.md — Ongoing competitor change detection, social listening, share of voice
  • narrative-warfare-guide.md — Narrative territory mapping, counter-narratives, and category creation
  • journey-growth-guide.md — Journey state machines, growth loops, dark funnel analysis, journey simulation
  • marketing-science-guide.md — Causal inference, Bayesian MMM, incrementality, and experimentation rigor
  • synthetic-audience-guide.md — AI-simulated audience research, focus groups, and message testing with calibration

© indranilbanerjee, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 56 other files in skills/context-engine of indranilbanerjee/digital-marketing-pro.

  • SKILL.md
  • 30-60-90-framework.md
  • actionable-persona-format.md
  • advanced-reporting-guide.md
  • agency-operations-guide.md
  • approval-framework.md
  • b2b-decision-making-unit.md
  • channel-families.md
  • competitive-monitoring-guide.md
  • competitor-3-question-output.md
  • compliance-rules.md
  • compound-intelligence-guide.md
  • creative-intelligence-guide.md
  • crm-integration-guide.md
  • custom-mcp-guide.md
  • decision-framework.md
  • decision-matrix-rerun.md
  • engagement-flow-methodology.md
  • eu-code-of-practice.md
  • eval-framework-guide.md
  • eval-rubrics.md
  • … and 36 more

Open the folder on GitHubat commit 3343924

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in indranilbanerjee/digital-marketing-pro, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Codebase to Coursezarazhangrui/codebase-to-course5.7k—~4.4kAutomated safety check: PassNone
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Scholar EvaluationK-Dense-AI/claude-scientific-writer2.4k2 repos~2.9kAutomated safety check: NotesMIT

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Categories

Questions about Context Engine

What does Context Engine do?

Load and manage the shared marketing context other skills build on — the active brand profile (voice, audiences, competitors, goals), industry benchmark profiles, geographic and industry compliance…. Context Engine is an agent skill from indranilbanerjee/digital-marketing-pro.claude-marketing/.

When should I use Context Engine?

Context Engine fits situations like: /digital-marketing-pro:context-engine; switch to brand X; what are the benchmarks for my industry; which compliance rules apply to us.

How do I install Context Engine in Claude Code?

Run `npx skills add indranilbanerjee/digital-marketing-pro --skill context-engine -a claude-code`. Or copy the skill folder (skills/context-engine in indranilbanerjee/digital-marketing-pro) into .claude/skills/context-engine in your project. Claude Code loads it when a task matches its description.

How do I install Context Engine in Codex?

Run `npx skills add indranilbanerjee/digital-marketing-pro --skill context-engine -a codex`. Or copy the skill folder (skills/context-engine in indranilbanerjee/digital-marketing-pro) into .agents/skills/context-engine in your project. Codex loads it when a task matches its description.

Can I use Context Engine in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add indranilbanerjee/digital-marketing-pro --skill context-engine -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/context-engine, .gemini/skills/context-engine, .github/skills/context-engine and .opencode/skills/context-engine in your project.

What does Context Engine need to run?

Going by SKILL.md and its folder, Context Engine needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Context Engine access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Context Engine safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Context Engine use?

Context Engine is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Context Engine use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Context Engine?

Skills that share tags, products or a category with Context Engine: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 66k stars), Codebase to Course (zarazhangrui/codebase-to-course, 5.7k stars) and AI Engineering Phase Quiz (rohitg00/ai-engineering-from-scratch, 66k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Context Engine?

indranilbanerjee (a GitHub user) maintains it in indranilbanerjee/digital-marketing-pro, which has 855 GitHub stars. The repository holds 162 skills in this directory. The repository was last updated on October 4, 2026.

Source: indranilbanerjee/digital-marketing-pro on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.