# Pipeline Dashboard > Weekly pipeline metrics, forecast, and trend dashboard in structured markdown - Skill: `ekatasingh1107/pipeline-dashboard` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds add ekatasingh1107/pipeline-dashboard` - Raw SKILL.md: https://api.skillmd.com/api/skills/ekatasingh1107/pipeline-dashboard/raw - Safety review: pending (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/pipeline-dashboard --- # Pipeline Dashboard Generates a weekly pipeline metrics and forecast dashboard. Pulls CRM data, calculates key metrics (pipeline value, new leads, conversion rates, velocity, forecast vs target, channel attribution), compares week-over-week trends, and outputs a structured markdown dashboard. Designed to run every Monday as part of a weekly review cadence. ## Prerequisites - `agency.config.json` in the project root - CRM data accessible via `crm-writer` - Optional: previous week's dashboard for trend comparison - Optional: `revenue-forecaster` output for forecast integration ## Capabilities Used 1. `revenue-forecaster` -- for stage-weighted pipeline forecast and sensitivity analysis 2. `attribution-analyzer` -- for channel attribution on new leads 3. `crm-auditor` -- for data quality score inclusion 4. `crm-writer` -- for reading pipeline data ## Phase 0: Read Config 1. Read `agency.config.json` from the project root. 2. Extract targets: - `targets.revenue.monthly` -- monthly revenue target - `targets.leads_per_week` -- weekly lead generation target - `targets.demos_per_week` -- weekly demo booking target - `targets.deals_per_month` -- monthly close target 3. Extract `crm.stages[]` for pipeline stage definitions. 4. Extract `crm.stage_probabilities` for weighted calculations. 5. Check for previous dashboard: look for `pipeline-dashboard-YYYY-MM-DD.md` in project root. ## Phase 1: Pull Pipeline Data Read all pipeline data from CRM: **Data to collect:** - All active deals with stage, value, owner, dates, and source - Leads added this week (by creation date) - Stage changes this week (leads that moved forward or backward) - Deals closed this week (won and lost) - Activities logged this week (emails sent, calls made, demos completed) ## Phase 2: Calculate Key Metrics ### Pipeline Overview ``` PIPELINE SNAPSHOT -- Week of [Date] === Total active deals: [N] Total pipeline value: $[X] Weighted pipeline value: $[Y] Average deal size: $[Z] Pipeline coverage ratio: [Y / monthly_target]x ``` ### New Activity This Week ``` THIS WEEK'S ACTIVITY === New leads added: [N] (target: [target]) Demos booked: [N] (target: [target]) Proposals sent: [N] Deals closed won: [N] ($[X]) Deals closed lost: [N] ($[X]) Win rate (this week): [%] ``` ### Conversion Rates by Stage ``` STAGE CONVERSION RATES === Stage | Deals | Value | Conversion to Next | Avg Days in Stage --------------------|-------|-----------|-------------------|------------------ New Lead | 25 | $125,000 | 60% -> Qualified | 4 days Qualified | 15 | $112,500 | 67% -> Discovery | 7 days Discovery Call | 10 | $100,000 | 70% -> Proposal | 5 days Proposal Sent | 7 | $87,500 | 57% -> Negotiation| 12 days Negotiation | 4 | $60,000 | 75% -> Won | 8 days ``` ### Velocity Metrics ``` PIPELINE VELOCITY === Average days lead-to-close: [N] days Average days per stage: [N] days Deals moving forward this week: [N] Deals stuck (no movement 14+ days): [N] Fastest close this quarter: [N] days ``` ### Forecast Integrate `revenue-forecaster` output: ``` REVENUE FORECAST === This month forecast: $[X] (target: $[T], gap: $[G]) Next month forecast: $[X] Quarter forecast: $[X] (target: $[T]) Sensitivity: Best case: $[X] Expected: $[Y] Worst case: $[Z] ``` ### Channel Attribution ``` LEAD SOURCES (this week) === Channel | New Leads | % of Total | Demos Booked -----------------|-----------|------------|------------- Cold Email | 8 | 40% | 3 LinkedIn | 5 | 25% | 2 Inbound/Organic | 4 | 20% | 1 Referral | 2 | 10% | 1 Other | 1 | 5% | 0 ``` ## Phase 3: Week-Over-Week Trends Compare current week to previous week: ``` WEEK-OVER-WEEK TRENDS === Metric | Last Week | This Week | Change | Status ------------------------|-----------|-----------|----------|-------- New leads | 15 | 20 | +33.3% | UP Demos booked | 4 | 7 | +75.0% | UP Pipeline value | $380K | $425K | +11.8% | UP Weighted pipeline | $145K | $168K | +15.9% | UP Deals closed won | 1 | 2 | +100.0% | UP Deals closed lost | 2 | 1 | -50.0% | IMPROVED Win rate | 33% | 67% | +100.0% | UP Avg deal cycle | 38 days | 34 days | -10.5% | FASTER Stale deals | 8 | 6 | -25.0% | IMPROVED CRM completeness | 78% | 82% | +5.1% | IMPROVED ``` Flag items that need attention: - Metrics trending wrong for 2+ consecutive weeks - Metrics significantly below target - New records (best week ever, worst metric, etc.) ## Phase 4: Action Items Generate specific action items based on the data: ``` PRIORITY ACTIONS THIS WEEK === 1. [URGENT] Close the $7,500 April gap -- accelerate Acme Corp (Proposal stage, $25K) 2. [HIGH] Follow up on 3 stale Discovery Call leads (12+ days without movement) 3. [MEDIUM] Book 3 more demos to hit weekly target (at 4/7 target) 4. [LOW] Clean up 6 CRM records flagged by crm-auditor DEALS TO WATCH: - Acme Corp ($75K, Proposal Sent, 15 days) -- budget decision expected this week - Beta Inc ($50K, Negotiation, 8 days) -- waiting on contract review - Gamma Ltd ($100K, Discovery, 3 days) -- demo scheduled Thursday ``` ## Phase 5: Output Generate the dashboard in markdown format and as structured JSON: **Markdown output** (saved as `pipeline-dashboard-YYYY-MM-DD.md`): ```markdown # Pipeline Dashboard -- Week of [Date] ## Executive Summary [2-3 sentences: pipeline health, target status, key wins/concerns] ## Pipeline Snapshot [Table from Phase 2] ## This Week's Activity [Activity metrics vs targets] ## Stage Conversion Funnel [Stage table with conversion rates] ## Revenue Forecast [Forecast with sensitivity range] ## Lead Sources [Channel attribution table] ## Trends [Week-over-week comparison table] ## Priority Actions [Ordered action items] ## Deals to Watch [Key deals with status and next steps] --- Generated by pipeline-dashboard | Data as of [timestamp] ``` **JSON output:** ```json { "pipeline_dashboard": { "week_of": "2024-03-11", "generated_at": "2024-03-11T09:00:00Z", "executive_summary": "", "pipeline_snapshot": { "total_deals": 61, "total_value": 425000, "weighted_value": 168000, "average_deal_size": 6967, "coverage_ratio": 2.8 }, "weekly_activity": { "new_leads": { "actual": 20, "target": 20, "status": "on_track" }, "demos_booked": { "actual": 7, "target": 7, "status": "on_track" }, "deals_won": { "count": 2, "value": 50000 }, "deals_lost": { "count": 1, "value": 15000 }, "win_rate": 0.67 }, "stage_funnel": [], "forecast": { "this_month": 52500, "target": 60000, "gap": -7500, "sensitivity": {} }, "lead_sources": [], "trends": {}, "action_items": [], "deals_to_watch": [], "data_quality_score": 82 } } ``` ## Example Usage **Trigger phrases:** - "Generate the weekly pipeline dashboard" - "Pipeline review for this week" - "Show me the pipeline metrics" - "Weekly sales dashboard" - "How's the pipeline looking?" - "Monday morning pipeline check" ``` User: Generate the weekly pipeline dashboard Assistant: [pulls CRM data, calculates all metrics, compares to last week, identifies 20 new leads (on target), $425K pipeline (+11.8%), flags $7.5K April gap and 3 stale deals, generates dashboard markdown and JSON] ``` ``` User: Are we on track this month? Assistant: [runs pipeline dashboard focused on monthly forecast, shows $52.5K weighted forecast vs $60K target, identifies deals that need to close to bridge the gap, lists specific actions] ```