Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add indranilbanerjee/digital-marketing-pro/plugin install 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/agency-dashboard)<a href="https://agentmods.dev/skills/indranilbanerjee/digital-marketing-pro/agency-dashboard"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/agency-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/agency-dashboard"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/digital-marketing-pro/agency-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 | $0.00147 | $0.02139 |
| Opus 5 | $0.00073 | $0.01069 |
| Sonnet 5 | $0.00029 | $0.00428 |
| Haiku 4.5 | $0.00015 | $0.00214 |
Grade A, and why
agency-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 13d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/digital-marketing-pro:agency-dashboard
Purpose
Generate a portfolio-level dashboard aggregating health metrics across ALL client brands. Shows campaign activity, budget pacing, KPI attainment, content pipeline, and team utilization at a glance — giving agency leadership a single view of operational health without opening each account individually. Designed for daily standups, weekly agency reviews, or on-demand health checks.
Input Required
The user must provide (or will be prompted for):
- Dashboard scope: All brands or a specific list of brand slugs to include in the portfolio view
- Time period: Current week, month, or quarter — determines the pacing calculations and comparison windows
- Detail level: Summary (top-line health scores per client) or detailed (campaign-level breakdowns per client with individual campaign metrics)
- Sort/filter preferences: Sort clients by health score, spend, revenue, or alphabetical — and optionally filter to only at-risk (amber/red) accounts
- Team filter (optional): Filter by account lead or team pod if the agency has multiple pods managing different client sets
- Comparison baseline (optional): Compare current period against prior period, same period last year, or plan/target — defaults to prior period
- Alert threshold overrides (optional): Custom thresholds for performance drop alerts or budget pacing tolerance — defaults to 20% performance drop and 10% pacing variance
- Export format (optional): Whether to output as markdown, Google Sheets, or Slack message — defaults to markdown
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. 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. - Enumerate all brands: Scan
~/.claude-marketing/brands/for all configured brand directories (excluding_active-brand.json). For each brand, loadprofile.jsonto get client name, industry, engagement type, contract dates, assigned team members, and KPI targets - Pull campaign data per brand: For each brand in scope, run
python "${CLAUDE_PLUGIN_ROOT}/scripts/campaign-tracker.py" --brand {slug} --action list-campaignsto retrieve active campaigns, statuses, budgets, and objectives (use--action get-campaign --id {id}for a single campaign's detail) - Pull execution status per brand: For each brand, run
python "${CLAUDE_PLUGIN_ROOT}/scripts/execution-tracker.py" --brand {slug} --action get-historyto get logged executions — completed deliverables, launches, and tasks — then derive pending / overdue status in analysis - Check budget pacing per brand: For each brand, compare actual spend-to-date against planned spend for the current period — calculate pacing percentage and project end-of-period spend at current run rate
- Calculate per-client health score: Apply the RAG scoring formula from
skills/context-engine/agency-operations-guide.md:- Green: On track across KPIs, budget on pace (within 10%), no overdue items, content pipeline flowing
- Amber: 1-2 KPIs at risk, minor pacing drift (10-20%), items approaching deadline, or pending approvals aging
- Red: Significant KPI misses, budget overspend (>20%), missed deadlines, stalled campaigns, or MCP disconnections
- Aggregate portfolio KPIs: Sum total active campaigns, total monthly spend, average ROAS across clients, total leads/conversions, total pending deliverables, and overall portfolio health distribution (count and percentage of green/amber/red)
- Check team utilization: Run
python "${CLAUDE_PLUGIN_ROOT}/scripts/team-manager.py" --action check-capacity --brand {slug}to assess current team workload — available capacity per team member, overloaded staff flagged, accounts at risk of under-service, and billable-hours tracking. Optionally add a Claude Code cost line — only if the user supplies the data. The plugin cannot read Claude Code usage itself. If the user pastes the output of their own/usagecommand (a Claude Code CLI slash command they run interactively), aggregate the per-model token/cost figures it reports into a "Claude Code consumption" line so leadership can see AI cost before the monthly invoice. Label models by whatever the user's/usageoutput names — do not assume specific model IDs. Brand-per-directory workspaces (~/work/clients/{slug}) make the figures brand-attributable. - Identify pending approvals: Scan execution logs across all brands for items awaiting client or internal approval — flag anything older than 48 hours as overdue, group by brand and urgency tier (routine, time-sensitive, blocking)
- Surface upcoming deadlines: Compile deadlines from all brands for the next 7 and 14 days — campaign launches, content due dates, reporting deadlines, contract milestones, renewal dates, and QBR schedules
- Detect alerts and anomalies: Flag any brand with sudden performance drops (>20% week-over-week on primary KPI), budget pacing issues (>10% ahead or behind plan), stalled campaigns (no activity in 5+ days), MCP connection failures, or expiring credentials
- Check content pipeline: Aggregate content status across all brands — items in draft, in review, approved, scheduled, and published — identify bottlenecks where content is stalling at a particular stage
- Generate trend comparison: Compare current portfolio health against the selected baseline period — show improving, stable, or declining trajectory for each client and the portfolio overall with directional arrows
- Compile portfolio dashboard: Assemble all data into a structured dashboard sorted by the user's preference, with drill-down detail available for any individual client
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.
- 13d ago First seen · 76 lines · 147 tokens per session scan A a539a9a973db
agency-dashboard is a skill published in the GitHub repository indranilbanerjee/digital-marketing-pro (812 stars, last pushed 5d ago), licensed MIT. It adds 147 tokens to every session and 2,139 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 2026-08-30.
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