client-report
Generate a white-labeled client report in agency voice — weekly pulse, monthly review, or QBR — with a KPI scorecard vs targets and comparison period, channel breakdowns, top wins with attribution, root-cause analysis of misses, 3-5 strategic recommendations, and budget efficiency.
Install / Use
npx skills add indranilbanerjee/digital-marketing-pro --skill client-reportInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
CommunicationSupported Platforms
Our assessment of client-report
client-report scores 82/100 on our quality scale, 375th of 440 Communication skills we index.
Its SKILL.md is 9.3 KB long, split into 6 sections and no code examples: a thorough specification that gives an agent plenty to work with.
It has 832 GitHub stars, a meaningful sign that others use it.
Maintenance, license and trust
- The repository was last updated 26 days ago, so client-report is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
client-report compared with similar skills
All 4 of these similar skills score higher than client-report; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| client-report (this skill)by indranilbanerjee | 82 | 832 | 26d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 90.1k | 18d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.4k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.2k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 85.6k | today | MCP Server |
Frequently asked questions
- How do I install client-report?
- Run
npx skills add indranilbanerjee/digital-marketing-pro --skill client-report. The install tabs above show the steps for each supported agent. - Which AI agents does client-report work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is client-report safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is client-report still maintained?
- The repository was last updated 26 days ago, so client-report is actively maintained.
Skill content
View source on GitHubname: client-report description: "Generate a white-labeled client report in agency voice — weekly pulse, monthly review, or QBR — with a KPI scorecard vs targets and comparison period, channel breakdowns, top wins with attribution, root-cause analysis of misses, 3-5 strategic recommendations, and budget efficiency. Requires explicit approval before any external send; only then can it deliver via connected Slack, email, or Google Sheets MCPs and log the delivery. Triggers on "/digital-marketing-pro:client-report", "prepare the monthly report for the client", "build the QBR for this account", "send the weekly performance pulse", "white-labeled performance report". Reads the brand profile and pulls data via campaign-tracker.py, execution-tracker.py, and connected platform MCPs; formats via report-generator.py."
/digital-marketing-pro:client-report
Purpose
Generate a professional, white-labeled client report for a specific brand. Uses agency voice (not brand voice), includes KPI performance, channel breakdowns, strategic recommendations, and next steps. Designed for external client delivery via Slack, email, Google Sheets, or markdown — with approval gating before any external send to prevent accidental disclosure or premature delivery of draft findings.
Input Required
The user must provide (or will be prompted for):
- Brand slug: The brand this report covers — must match a configured brand in
~/.claude-marketing/brands/ - Report type: One of:
- Weekly pulse: Quick KPI snapshot with 3-5 key metrics and brief commentary
- Monthly review: Full performance analysis with channel breakdowns and recommendations
- QBR: Quarterly deep-dive with strategic roadmap and forward plan
- Date range: Specific start and end dates for the reporting period — defines what data is pulled and analyzed
- Delivery channel: Where the report should be sent — slack, email, google-sheets, or markdown-only (no external delivery, just generate the artifact)
- Custom sections (optional): Any additional sections the client has requested — competitive update, creative performance breakdown, audience insights, attribution deep-dive, or ad-hoc investigation topic
- Comparison period: What to compare against — prior period, same period last year, plan/target, or all three simultaneously
- Recipient list (optional): Specific client contacts who should receive the report if delivering via email or Slack — names and handles/addresses
- Narrative emphasis (optional): What the client cares most about this period — growth, efficiency, brand awareness, pipeline generation, or revenue — influences which metrics are highlighted first and how insights are framed
- Include appendix: Whether to attach raw data tables and campaign-level detail as an appendix — defaults to yes for monthly and QBR, no for weekly pulse
- White-label settings (optional): Agency logo placement, color scheme, and disclaimer text — pulled from agency profile if configured, otherwise uses clean defaults
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. - Pull all metrics for the brand: Query connected MCP servers and run
python "${CLAUDE_PLUGIN_ROOT}/scripts/campaign-tracker.py" --brand {slug} --action list-campaigns(then--action get-campaign --id {id}per campaign) to gather performance data across all active channels; filter to the specified date range during analysis - Gather campaign history and execution log: Run
python "${CLAUDE_PLUGIN_ROOT}/scripts/execution-tracker.py" --brand {slug} --action get-historyto compile all deliverables completed, campaigns launched, optimizations made, and tests concluded, then filter to the reporting period during analysis - Calculate KPIs vs targets and vs comparison period: Compute actuals against the brand's stated KPI targets from
profile.jsonand against the selected comparison period — calculate deltas, percentage changes, trend direction, and statistical significance where sample sizes allow - Break down performance by channel: Segment metrics by channel (paid search, paid social, organic search, email, display, video, affiliate, etc.) with per-channel KPIs, spend, efficiency metrics (CPC, CPA, ROAS, CTR), and contribution percentage to overall goals
- Identify top wins and attribution: Select the 3-5 best-performing campaigns or initiatives from the period — document what was done, what drove the result, audience and creative insights, and how it connects to business outcomes
- Analyze underperformance with root causes: For any KPI that missed target, identify root causes:
- External factors: market shifts, seasonality, competitive moves, platform algorithm changes
- Internal factors: budget constraints, creative fatigue, audience saturation, timing misalignment
- Corrective actions: what was already done and what is recommended for next period
- Generate strategic recommendations: Based on performance data, formulate 3-5 actionable recommendations — what to scale, what to pause, what to test next, where budget should shift, and what new opportunities to explore
- Write report in agency voice: Draft the full report using professional, third-person agency voice — NOT the brand's personality. Focus on clarity, data-backed insights, actionable next steps, and a confident but honest tone that builds client trust
- Format for delivery channel: Run
python "${CLAUDE_PLUGIN_ROOT}/scripts/report-generator.py" --brand {slug} --action format-slack(orformat-email/format-sheets), passing the report JSON via--data '{report_json}'; for a clean markdown artifact use--action generate-report --data '{report_json}' - Create approval checkpoint: Present the full report preview for review. Risk level: low. Require explicit approval before any external delivery — highlight any sensitive data, unexpected results, or negative findings that may need pre-briefing with the client
- Deliver via MCP if approved: On approval, send via the appropriate MCP integration (Slack MCP, email MCP, Google Sheets MCP) if a delivery channel was specified. Handle delivery errors gracefully with retry guidance
- Log delivery and archive: Record the report delivery in the execution log with timestamp, recipients, delivery confirmation status, report version, and a reference to the archived report for future comparison
Output
A structured client report containing:
- Executive summary: 3-5 sentence overview of the period — headline result, key wins, areas of focus, outlook for next period, and one recommended action for the client
- KPI scorecard: Actuals vs targets vs comparison period in a scannable table with color-coded status indicators (exceeded, on track, at risk, missed) and trend arrows showing directional momentum
- Channel performance breakdown: Per-channel metrics with spend, results, efficiency metrics (CPC, CPA, ROAS, CTR), contribution percentage to overall goals, and channel health assessment
- Campaign highlights with attribution: Top-performing campaigns with what drove success, creative and audience insights, measured impact, and replication recommendations for future campaigns
- Underperformance analysis: Honest assessment of any misses with root cause categorization (external vs internal), impact quantification, corrective actions taken, and preventive measures for next period
- Strategic recommendations (3-5): Data-backed next steps with expected impact, investment required, implementation timeline, priority ranking, and connection to the client's stated business objectives
- Budget efficiency analysis: Spend vs return summary by channel, cost trend lines over the period, budget utilization rate, and efficiency comparison to prior periods with improvement/decline indicators
- Upcoming deliverables and timeline: What the agency will deliver next period with dates, milestones, dependencies, and any client actions required to keep the plan on track
- Appendix (if requested): Raw data tables, campaign-level breakdowns, full metric exports, creative performance data, and supporting calculations for detailed review
- Delivery confirmation: Channel, timestamp, recipients, delivery status, and report version — or markdown artifact if no external delivery was requested
Agents Used
- agency-operations — Report voice and tone (agency professional, not brand personality), client context awareness, approval workflow management, white-label formatting, and delivery coordination
- analytics-analyst — Metrics analysis, KPI calculations, channel breakdowns, trend analysis, comparison computations, attribution modeling, statistical significance checks, and recommendation data support
- execution-coordinator — Report formatting for delivery channels, MCP integration delivery, execution logging, delivery error handling, and archival
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
