executive-dashboard

executive-dashboard is a skill for Claude Code from indranilbanerjee/digital-marketing-pro. It costs 132 tokens per session (1,492 once invoked), scanned A, original, MIT.

A build-ready specification for an executive marketing dashboard, a concise view of the measures leaders use to make decisions. It defines key metrics, charts, alerts, data sources, drill-downs, and a mobile layout, but does not build or connect the dashboard.

In plain words
What is it for?
It is for choosing north-star metrics, planning dashboard screens, setting alert thresholds, mapping data sources, and preparing views for executives and mobile users.
Why use it?
It prevents executive reporting from becoming a collection of disconnected activity numbers. It links marketing measures to business outcomes and sets out what the dashboard should show before implementation begins.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths.

Part of the digital-marketing-pro plugin — 154 skills, 18 commands, 24 agents shipped together

Good fit It is for choosing north-star metrics, planning dashboard screens, setting alert thresholds, mapping data sources, and preparing views for executives and mobile users.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/indranilbanerjee/digital-marketing-pro/executive-dashboard
Install

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.

Any agent
npx skills add indranilbanerjee/digital-marketing-pro --skill executive-dashboard
Clone the repo
git clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-pro

Made for: Claude Code.

Or install digital-marketing-pro, the plugin that ships this one along with the rest of its 154 skills, 18 commands, 24 agents.

Wrote 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.

agentmods badge for executive-dashboard

README.md
[![agentmods](https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/executive-dashboard/github.svg)](https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/executive-dashboard)
Your own site
<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.

agentmods 80×15 button for executive-dashboard

Your own site · 80×15
<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>
Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,492 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 4d ago against content hash fa98ba67e77d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

skills/executive-dashboard/SKILL.md · 60 lines

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

  1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for 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.
  2. 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
  3. 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)
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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)
  10. 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
  11. 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

Read the full file on GitHub · 60 lines

Changes

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.

  1. 4d ago First seen · 60 lines · 132 tokens per session scan A fa98ba67e77d

Subscribe to this mod's changes

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.

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