ab-test-plan
FreePlan an A/B test by script: sample size per variant, days to run, stopping rules. "how many visitors per variant"
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Build the agency dashboard across all client brands: health, pacing, risk. "how are all our clients doing"
The English summary is being prepared. Showing the original description.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Script location. If your host does not set
${CLAUDE_PLUGIN_ROOT}, the scripts are in this plugin'sscripts/folder, next toskills/. Run them with Python 3.10 or newer:python, orpython3wherepythonis not found (macOS, many Linux systems).
Generate a portfolio-level dashboard aggregating health metrics across ALL client brands. Shows campaign activity, budget pacing, KPI attainment, content pipeline, and team utilization at a glance — giving agency leadership a single view of operational health without opening each account individually. Designed for daily standups, weekly agency reviews, or on-demand health checks.
The user must provide (or will be prompted for):
~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.~/.claude-marketing/brands/ for all configured brand directories (excluding _active-brand.json). For each brand, load profile.json to get client name, industry, engagement type, contract dates, assigned team members, and KPI targetspython "${CLAUDE_PLUGIN_ROOT}/scripts/campaign-tracker.py" --brand {slug} --action list-campaigns to retrieve active campaigns, statuses, budgets, and objectives (use --action get-campaign --id {id} for a single campaign's detail)python "${CLAUDE_PLUGIN_ROOT}/scripts/execution-tracker.py" --brand {slug} --action get-history to get logged executions — completed deliverables, launches, and tasks — then derive pending / overdue status in analysisskills/context-engine/agency-operations-guide.md:
python "${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 /usage command (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 /usage output names — do not assume specific model IDs. Brand-per-directory workspaces (~/work/clients/{slug}) make the figures brand-attributable.A structured portfolio dashboard containing:
/usage data: aggregated per working directory mapped to brand, using whatever model tiers the user's /usage output reports, with token totals and USD cost for the reporting window. Flag any brand whose Claude Code spend is >2× the portfolio median for the same retainer tier as a candidate for engagement-pattern review or rate renegotiation. Omit this panel entirely if no usage data was provided./digital-marketing-pro:performance-report, /digital-marketing-pro:client-report, or /digital-marketing-pro:credential-switch to activate that brand's contextNo reviews yet. Tell others what you thought.
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Plan an A/B test by script: sample size per variant, days to run, stopping rules. "how many visitors per variant"
The English summary is being prepared. Showing the original description.
Write ad copy variants to each platform's specs, policy-checked and in brand voice. "write ad copy for Meta"
The English summary is being prepared. Showing the original description.
Add a custom MCP integration: scaffold the server, write .mcp.json, test it. "add a new MCP server"
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Run a one-time AEO audit of six AI answer engines, scored per surface. "check our AI search visibility"
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Plan AEO/GEO strategy to get cited by AI: content, entities, schema, 90-day plan. "how do we get cited by AI"
The English summary is being prepared. Showing the original description.
Audit agent readiness by script: AI-crawler rules, product schema, no-JS HTML, feeds. "can AI agents use our site"
The English summary is being prepared. Showing the original description.