Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add indranilbanerjee/digital-marketing-pro --skill executive-dashboardgit clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-proWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/executive-dashboard)<a href="https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/executive-dashboard"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/executive-dashboard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/executive-dashboard"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/executive-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00132 | $0.01492 |
| Opus 5 | $0.00066 | $0.00746 |
| Sonnet 5 | $0.00026 | $0.00298 |
| Haiku 4.5 | $0.00013 | $0.00149 |
Grade A, and why
executive-dashboard scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/digital-marketing-pro:executive-dashboard
Purpose
Design a C-suite marketing dashboard that translates marketing metrics into business outcomes for executive decision-making. Bridges the gap between marketing activity data and business impact, giving senior leaders the clarity to make faster, better-informed strategic decisions without drowning in operational detail.
Input Required
The user must provide (or will be prompted for):
- Executive role: Primary audience — CEO, CMO, CFO, VP Marketing, or board — each requires different metric emphasis and abstraction level
- Business model and revenue drivers: How the company makes money — SaaS, e-commerce, lead gen, marketplace, subscription — and the key revenue levers marketing influences
- Strategic priorities this quarter: The 2-4 business priorities the executive team is focused on that marketing should ladder up to
- Reporting frequency: How often the dashboard will be reviewed — weekly executive standup, monthly leadership meeting, quarterly board review
- Current data sources and tools: Analytics platforms, CRM, ad platforms, attribution tools, and BI systems currently in use with data freshness and reliability notes
- Existing reports being replaced: Current reporting artifacts the dashboard will consolidate or replace — helps identify gaps and redundancies
- Key decisions the dashboard should inform: Specific decisions executives make that this dashboard should support — budget allocation, channel mix, hiring, campaign scaling, market expansion
- Stakeholder data literacy level: How comfortable the audience is with marketing metrics — determines labeling, context, and narrative density needed
Process
- Load brand context: Read
~/.claude-marketing/brands/_active-brand.jsonfor the active slug, then load~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at~/.claude-marketing/brands/{slug}/guidelines/_manifest.json— if present, load restrictions and relevant category files. Check for custom templates at~/.claude-marketing/brands/{slug}/templates/. Check for agency SOPs at~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults. - Identify north-star metrics: Select 5-7 metrics that directly tie marketing activity to business outcomes — revenue influenced, pipeline generated, customer acquisition cost, lifetime value, market share, brand equity indicators
- Design metric hierarchy: Organize metrics into three tiers — leading indicators (predict future performance), lagging indicators (confirm past results), and health metrics (signal system stability and sustainability)
- Select visualization type per metric: Choose the optimal chart type for each metric based on data shape and decision context — trend lines for trajectory, gauges for targets, bar charts for comparisons, sparklines for density
- Define alert thresholds and anomaly triggers: Set green/yellow/red thresholds for each metric with specific trigger values, and configure anomaly detection rules for unexpected spikes or drops
- Map data sources to each metric: Document which system provides each metric, how it is calculated, data freshness (real-time, daily, weekly), and known limitations or lag
- Design layout for scanning speed: Structure the dashboard for F-pattern or Z-pattern scanning — most critical metrics top-left, summary before detail, consistent visual hierarchy, minimal cognitive load
- Add narrative guidance: Write "how to read this" instructions for each section — what good looks like, what bad looks like, and what action to take in each scenario
- Build drill-down structure: Design three levels of depth — summary view (the dashboard itself), detail view (campaign or channel breakdowns), and root cause view (diagnostic data for investigating anomalies)
- Create mobile-friendly variant: Adapt the dashboard layout for mobile or tablet viewing — prioritize top 3-5 metrics, stack vertically, enlarge touch targets, and simplify visualizations
- Add comparison baselines: Define what each metric is compared against — plan/target, prior period (MoM, QoQ, YoY), industry benchmark, and competitive estimate — with comparison display format
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 60 lines · 132 tokens per session scan A fa98ba67e77d
executive-dashboard is a skill published in the GitHub repository indranilbanerjee/digital-marketing-pro (806 stars, last pushed 4d ago), licensed MIT. It adds 132 tokens to every session and 1,492 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-07.
Other skills, from other repositories
cf-style-guide
Import a brand voice profile from an existing style guide — a .docx/.pdf document, a URL, or manual input — extracting tone, formality, personality, approved/banned terminology, compliance guardrails, and author profiles into a structured brand-profile JSON at /.claude-marketing/{brand-slug}/Brand-Guidelines/, then…
marketing-expert
Build comprehensive marketing technology solutions including automation workflows, campaign management, analytics tracking, and multi-channel orchestration. Use when the user mentions marketing automation, campaign management, SEO, email or content marketing, attribution, or multi-channel orchestration.
cf-brief
Generate a research-backed content brief from a keyword or topic — keyword data with volume and difficulty, top-5 competitor and E-E-A-T analysis, search-intent classification, audience pain points, a section-by-section outline with word counts and citation targets, plus SEO and AEO/GEO strategy (AI Overview status…
cf-publish
Execute CMS publishing: push a finished, reviewed piece (Phase 8 complete, quality score >=7.0) to Webflow or WordPress via MCP connectors as draft, scheduled, or live — always showing a full publish preview and waiting for your explicit yes/no/edit confirmation before anything is pushed. Runs the EU AI Act Article 50…
cf-template
Create and manage custom content-type templates beyond the 8 built-ins (article, blog, whitepaper, faq, research-paper, video-script, case-study, newsletter) — defining section structure, word-count allocations, readability targets, citation minimums, and quality standards, then validating the template against every…
cf-variants
Generate 3-10 scored A/B test variations of a single content element — headline, hook, CTA, intro, or conclusion — each rated across 6 quality dimensions and ranked by your optimization goal (clicks, engagement, conversions, or readability), with top-3 recommendations and A/B test setup guidance (sample size…