/performance-report
Generate performance reports. Use when: tracking KPIs, trend analysis, anomaly detection, and actionable recommendations.
$ npx -y skills add indranilbanerjee/digital-marketing-pro --skill performance-report --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/performance-report
Context preview
The summary Claude sees to decide when to auto-load this skill.
Generate performance reports. Use when: tracking KPIs, trend analysis, anomaly detection, and actionable recommendations.
SKILL.md
performance-report.SKILL.mdname: performance-report
description: "Generate performance reports. Use when: tracking KPIs, trend analysis, anomaly detection, and actionable recommendations."
argument-hint: "[time-period]"
/digital-marketing-pro:performance-report
Purpose
Generate a structured marketing performance report that transforms raw data into insights. Covers KPI tracking, trend analysis, anomaly detection, and prioritized recommendations for optimization.
**Scope (vs `/digital-marketing-pro:performance-check`):** this skill is the **narrative formatting layer** — it turns metrics into a stakeholder-ready deliverable (executive summary, channel commentary, trend narrative, prioritized recommendations, audience-appropriate formatting). It consumes the live pulls and persisted snapshots that `/digital-marketing-pro:performance-check` produces rather than re-pulling from the platforms itself. Use `performance-check` to *see the numbers now*; use `performance-report` to *tell the story*. For deeper anomaly diagnosis, hand off to `/digital-marketing-pro:anomaly-scan`.
Input Required
The user must provide (or will be prompted for):
- **Reporting period**: Date range for the report
- **Channels to cover**: Which marketing channels to include (all, or specific ones)
- **Data source**: Raw data (paste, CSV, or connected platform)
- **KPIs of interest**: Specific metrics to focus on (or use defaults for the channel)
- **Comparison period**: Previous period, YoY, or custom benchmark
- **Audience**: Who will read the report (executive summary vs. tactical detail)
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. Ingest and validate the provided performance data 3. Calculate core KPIs per channel: traffic, conversions, revenue, ROAS, CPA, engagement, growth. Break out GA4's **"AI Assistant"** default channel (referrals from ChatGPT, Gemini, Copilot, Perplexity, etc.) as its own line so AI-sourced traffic and conversions are visible rather than folded into Referral/Direct 4. Run trend analysis: period-over-period changes, trajectory, seasonality adjustments 5. Detect anomalies: significant spikes or drops with likely root causes 6. Benchmark against industry averages and brand targets 7. Generate insights: what worked, what underperformed, and why 8. Produce prioritized recommendations for the next period 9. Format report for the specified audience (executive vs. tactical)
Output
A structured performance report containing:
- Executive summary with headline metrics and overall assessment
- Channel-by-channel KPI dashboard with period-over-period comparison
- Trend analysis with visualizable data points
- Anomaly alerts with root cause hypotheses
- Top wins and underperformers with context
- Actionable recommendations ranked by expected impact
- Next period goals and focus areas
Agents Used
- **analytics-analyst** — Data analysis, KPI calculation, trend detection, anomaly identification, recommendations
Read more
name: performance-report description: "Generate performance reports. Use when: tracking KPIs, trend analysis, anomaly detection, and actionable recommendations." argument-hint: "[time-period]"
/digital-marketing-pro:performance-report
Purpose
Generate a structured marketing performance report that transforms raw data into insights. Covers KPI tracking, trend analysis, anomaly detection, and prioritized recommendations for optimization.
**Scope (vs `/digital-marketing-pro:performance-check`):** this skill is the **narrative formatting layer** — it turns metrics into a stakeholder-ready deliverable (executive summary, channel commentary, trend narrative, prioritized recommendations, audience-appropriate formatting). It consumes the live pulls and persisted snapshots that `/digital-marketing-pro:performance-check` produces rather than re-pulling from the platforms itself. Use `performance-check` to *see the numbers now*; use `performance-report` to *tell the story*. For deeper anomaly diagnosis, hand off to `/digital-marketing-pro:anomaly-scan`.
Input Required
The user must provide (or will be prompted for):
- **Reporting period**: Date range for the report
- **Channels to cover**: Which marketing channels to include (all, or specific ones)
- **Data source**: Raw data (paste, CSV, or connected platform)
- **KPIs of interest**: Specific metrics to focus on (or use defaults for the channel)
- **Comparison period**: Previous period, YoY, or custom benchmark
- **Audience**: Who will read the report (executive summary vs. tactical detail)
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. Ingest and validate the provided performance data 3. Calculate core KPIs per channel: traffic, conversions, revenue, ROAS, CPA, engagement, growth. Break out GA4's **"AI Assistant"** default channel (referrals from ChatGPT, Gemini, Copilot, Perplexity, etc.) as its own line so AI-sourced traffic and conversions are visible rather than folded into Referral/Direct 4. Run trend analysis: period-over-period changes, trajectory, seasonality adjustments 5. Detect anomalies: significant spikes or drops with likely root causes 6. Benchmark against industry averages and brand targets 7. Generate insights: what worked, what underperformed, and why 8. Produce prioritized recommendations for the next period 9. Format report for the specified audience (executive vs. tactical)
Output
A structured performance report containing:
- Executive summary with headline metrics and overall assessment
- Channel-by-channel KPI dashboard with period-over-period comparison
- Trend analysis with visualizable data points
- Anomaly alerts with root cause hypotheses
- Top wins and underperformers with context
- Actionable recommendations ranked by expected impact
- Next period goals and focus areas
Agents Used
- **analytics-analyst** — Data analysis, KPI calculation, trend detection, anomaly identification, recommendations
Your agency just signed a 50-brand client. The previous agency left no playbook. Three brands are bleeding budget, two have stale positioning, one is launching in a regulated jurisdiction next month. Where do you start?
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