# Weekly Report > Monday morning full pipeline review with metrics, channel performance, and forecast. Reads all CRM tabs, calculates deltas vs previous week, and generates actionable recommendations. - Skill: `ekatasingh1107/weekly-report` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add ekatasingh1107/weekly-report` - Raw SKILL.md: https://api.skillmd.com/api/skills/ekatasingh1107/weekly-report/raw - Safety review: PASS (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: ekatasingh1107 (https://skillmd.com/u/ekatasingh1107) - Updated: 2026-08-19 - Page: https://skillmd.com/skills/ekatasingh1107/weekly-report --- # Weekly Report Full pipeline review designed to run every Monday morning. Pulls data from all CRM tabs, computes week-over-week deltas, and generates a structured report with metrics, channel performance, lead quality analysis, revenue forecasting, and concrete recommendations for the week ahead. ## Prerequisites - `agency.config.json` fully populated (run `/agency-setup` first) - CRM initialized with data from at least one week of pipeline activity - Tool stack configured (Apollo, email validator, email sender, LinkedIn tool) ## Composites & Capabilities Used 1. `crm-writer` -- read CRM data from all tabs 2. `pipeline-dashboard` -- pull aggregated metrics (if built) ## Phase 0: Data Collection Read from CRM all tabs: - **Pipeline tab**: all leads with stages, scores, dates, and ownership - **Outreach log**: all actions this week (emails, LinkedIn, Instagram, calls) - **Email drafts**: sent vs drafted counts, subject lines, reply tracking - **Calling tab**: calls made, outcomes (connected, voicemail, no answer, meeting booked) - **Dashboard tab**: previous week's numbers for comparison Pull the date range: Monday 00:00 through Sunday 23:59 of the reporting week. ## Phase 1: Pipeline Metrics Calculate and present: ``` WEEKLY PIPELINE REPORT -- Week of [Date] === PIPELINE SNAPSHOT: - Total active leads: N (delta vs last week: +/-N) - By stage: NEW: N RESEARCHED: N ENRICHED: N OUTREACH_READY: N CONTACTED: N REPLIED: N DEMO_BOOKED: N WON: N LOST: N NEW LEADS THIS WEEK: N - Signal scan: N - Platform scraper: N - Inbound: N - Referral: N ``` Include stage-by-stage delta vs previous week. Highlight any stage with > 20% change. ## Phase 2: Outreach Performance ``` OUTREACH METRICS (Last 7 Days): --- Emails: - Sent: N - Opens: N (X%) [if trackable] - Replies: N (X%) - Positive replies: N - Demo from email: N LinkedIn: - Connections sent: N - Accepted: N (X%) - DMs sent: N - Replies: N (X%) Instagram: - DMs sent: N - Replies: N (X%) Calls: - Made: N - Connected: N (X%) - Meetings booked: N BEST PERFORMING: - Best email subject: "[subject]" (X% reply rate) - Best channel: [channel] (X% response rate) - Best touch point: Touch N (X% response rate) ``` Break down by day of week if enough data exists to surface timing patterns. ## Phase 3: Lead Quality ``` LEAD QUALITY: --- HOT leads generated: N WARM leads generated: N COOL leads (filtered): N Conversion funnel: Signal -> Lead: X% Lead -> Enriched: X% Enriched -> Contacted: X% Contacted -> Replied: X% Replied -> Demo: X% Demo -> Won: X% Average lead score: N Top platforms by quality: [ranked list] ``` Flag any funnel stage with conversion below historical average. ## Phase 4: Revenue Impact ``` REVENUE PIPELINE: --- Demos booked this week: N Demos booked total: N Proposals sent: N Deals in negotiation: N Deals won this week: N Revenue won: $X Pipeline value (weighted): - HOT leads * close rate: $X - Demos scheduled: $X - Proposals out: $X Total pipeline value: $X ``` Use close rate estimates from `agency.config.json` if available, otherwise use industry defaults (HOT: 15%, Demo: 30%, Proposal: 50%). ## Phase 5: Credit Usage ``` TOOL CREDITS: --- Apollo credits used: N / N remaining ZeroBounce credits used: N / N remaining Email sends: N / N daily cap ``` Flag if any tool is below 20% remaining credits. Calculate projected depletion date at current burn rate. ## Phase 6: Insights & Recommendations Based on the data, generate 3-5 specific recommendations: - If reply rate < 3%: "Email copy needs revision. Consider testing new subject lines." - If LinkedIn outperforms email: "Shift more outreach to LinkedIn. Increase daily connection cap." - If HOT leads are low: "Expand signal scan to more platforms or broaden keywords." - If follow-ups are being missed: "N leads had overdue follow-ups. Catch up today." - If one segment outperforms: "India D2C segment has 2x reply rate. Prioritize." - If demo-to-won rate is dropping: "Review demo quality. Consider pre-qualifying harder." - If pipeline is top-heavy (many NEW, few CONTACTED): "Enrichment is the bottleneck. Allocate more time to Phase 2." Each recommendation includes: observation, impact estimate, and suggested action. ## Phase 7: Next Week Plan Suggest adjustments based on this week's data: - Target lead count for next week (increase if pipeline is thin, maintain if healthy) - Channels to prioritize (based on Phase 2 performance data) - Cadence adjustments (touch timing, sequence changes) - Content angles to test (new subject lines, new value props, new case studies) - Specific accounts to focus on (stalled deals, high-value prospects) ``` NEXT WEEK TARGETS: --- New leads: N Enrichments: N Outreach drafts: N Follow-ups: N Demos target: N Calls target: N PRIORITY ACTIONS: 1. [Specific action with owner and deadline] 2. [Specific action with owner and deadline] 3. [Specific action with owner and deadline] ``` ## Example Usage **Trigger phrases:** - "Run the weekly report" - "Monday pipeline review" - "How did we do this week?" - "Generate weekly sales metrics"