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 brainbytes-dev/everything-claude-marketing --skill analytics-dashboardsgit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-marketingWrote 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/brainbytes-dev/everything-claude-marketing/analytics-dashboards)<a href="https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/analytics-dashboards"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/analytics-dashboards/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/brainbytes-dev/everything-claude-marketing/analytics-dashboards"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/analytics-dashboards.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 | $0.00027 | $0.02577 |
| Opus 5.5 | $0.00011 | $0.01031 |
| Sonnet 5.5 | $0.00005 | $0.00515 |
| Haiku 4.5 | $0.00003 | $0.00258 |
Grade A, and why
analytics-dashboards 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 2mo 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Dashboard Design
When to Activate
- Building a new marketing dashboard or reporting system
- Redesigning existing dashboards that aren't driving decisions
- Preparing data visualizations for stakeholders
- Setting up automated reporting for marketing teams
- Choosing metrics to track for a campaign or channel
- Stakeholders complain they "don't know what's working"
First Questions
- Who is the primary audience for this dashboard? (CEO, CMO, channel manager, campaign team)
- What decisions should this dashboard help make?
- What is the reporting cadence? (Real-time, daily, weekly, monthly)
- What data sources are available? (GA4, CRM, ad platforms, email platform, billing system)
- What tool will you build this in? (Looker Studio, Tableau, Power BI, Databox, custom)
- What are the top 3 questions this dashboard must answer?
Dashboard Hierarchy
Dashboards should form a pyramid. Each level answers different questions for different audiences.
Level 1: Executive Dashboard
- Audience: CEO, CFO, board
- Cadence: Monthly or quarterly
- Purpose: "Is marketing contributing to business growth?"
- Metrics: Revenue influenced, CAC, LTV, LTV:CAC ratio, pipeline value, brand awareness trends
- Design: Maximum 6-8 metrics. Heavy on trends, light on granularity. Always include comparison period.
Level 2: Marketing Leadership Dashboard
- Audience: CMO, VP Marketing, Head of Growth
- Cadence: Weekly
- Purpose: "Which channels and programs are performing? Where should we adjust?"
- Metrics: Channel-level spend, CPA, ROAS, conversion volume, pipeline by source, funnel conversion rates
- Design: 10-15 metrics. Channel comparison views. Pacing against goals.
Level 3: Channel Dashboards
- Audience: Channel managers (paid, organic, email, content)
- Cadence: Daily to weekly
- Purpose: "How is my channel performing and where do I optimize?"
- Metrics: Channel-specific KPIs (CTR, CPC, impression share, open rate, domain authority, etc.)
- Design: Detailed, filterable, actionable. Campaign-level drill-down.
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.
- 2mo ago First seen · 234 lines · 27 tokens per session scan A b32582da6629
analytics-dashboards is a skill published in the GitHub repository brainbytes-dev/everything-claude-marketing (10 stars, last pushed 7mo ago), licensed MIT. It adds 27 tokens to every session and 2,577 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
analytics-dashboards compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| analytics-dashboardsbrainbytes-dev/everything-claude-marketing | Skill | 10 | 7mo ago | MIT | A | 27 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |