Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
Revenue Forecasting Engine
Generates detailed revenue forecasts using pipeline weighting, cohort analysis, scenario modeling, seasonality, and leading indicators to inform business dec...
skill openclawclawhub Free
Generates detailed revenue forecasts using pipeline weighting, cohort analysis, scenario modeling, seasonality, and leading indicators to inform business dec...
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- 1kalin
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Revenue Forecasting Engine
Build accurate, data-driven revenue forecasts your board and investors actually trust.
What This Does
Generates a complete revenue forecasting model covering: Pipeline-Weighted Forecast — Apply stage-specific close rates to your current pipeline Cohort Analysis — Track revenue by customer cohort with expansion/contraction/churn Scenario Modeling — Bear/base/bull projections with probability weighting Seasonality Adjustments — Monthly coefficients based on your historical patterns Leading Indicators — Track signals that predict revenue 60-90 days out
Instructions
When the user asks for a revenue forecast, follow this framework:
Step 1: Gather Inputs
Ask for (or use available data): Current MRR/ARR Pipeline by stage with deal values Historical close rates by stage Average sales cycle length Net revenue retention rate Expansion revenue %
Step 2: Build the Pipeline Forecast
Stage-Weighted Model: StageProbabilityWeighted ValueDiscovery10%Deal × 0.10Demo/Eval25%Deal × 0.25Proposal Sent50%Deal × 0.50Negotiation75%Deal × 0.75Verbal Commit90%Deal × 0.90Closed Won100%Deal × 1.00 Adjustment factors: Deal age penalty: -5% per month past avg cycle Champion risk: -20% if no identified champion Budget confirmed: +10% if budget is allocated Competitive deal: -15% if competitor identified
Step 3: Cohort Revenue Model
Track each monthly cohort: Month 0: New MRR from cohort Month 1: Retained MRR × (1 - monthly churn rate) Month 3: Add expansion revenue (avg 2-5% monthly for healthy SaaS) Month 6: Steady-state retention rate applies Month 12: Mature cohort — use net revenue retention Benchmarks by company stage: MetricSeedSeries ASeries B+Gross Churn3-5%/mo2-3%/mo1-2%/moNet Retention90-100%100-110%110-130%Expansion %5-10%10-20%20-40%CAC Payback18-24 mo12-18 mo6-12 mo
Step 4: Scenario Analysis
Bear Case (20% probability): Pipeline closes at 60% of weighted value Churn increases 50% No expansion revenue 1 key deal slips each quarter Base Case (60% probability): Pipeline closes at weighted value Current retention rates hold Historical expansion rate Normal seasonality Bull Case (20% probability): Pipeline closes at 120% of weighted value Retention improves 10% Expansion accelerates 25% 1 surprise large deal per quarter Expected Value = (Bear × 0.2) + (Base × 0.6) + (Bull × 0.2)
Step 5: Seasonality Coefficients
Apply monthly adjustment factors: MonthB2B SaaSEcommerceProfessional ServicesJan0.850.700.90Feb0.900.750.95Mar1.050.851.10Apr1.000.901.00May0.950.900.95Jun1.100.951.05Jul0.850.850.85Aug0.800.900.80Sep1.101.001.10Oct1.051.051.05Nov1.151.401.10Dec1.201.751.15
Step 6: Leading Indicators Dashboard
Track these weekly — they predict revenue 60-90 days out: IndicatorWeightSignalQualified pipeline created25%New opps entering Stage 2+Demo-to-proposal rate20%Conversion velocityAverage deal size trend15%Moving up or down?Sales cycle length15%Getting longer = red flagInbound lead volume10%Marketing effectivenessWebsite trial signups10%Self-serve demandCustomer NPS/CSAT5%Retention predictor
Step 7: Output Format
Present the forecast as: REVENUE FORECAST — [Period] ================================ Current ARR: $X Pipeline (Weighted): $X Expected New ARR: $X 12-Month Projection: Bear: $X (20%) Base: $X (60%) Bull: $X (20%) Expected: $X Key Risks: 1. [Risk] — [Mitigation] 2. [Risk] — [Mitigation] Leading Indicators: 🟢 [Healthy metric] 🟡 [Watch metric] 🔴 [Concerning metric] Next Month Actions: 1. [Specific action] 2. [Specific action]
Red Flags to Call Out
Pipeline coverage < 3x target = high risk 40% of forecast from 1-2 deals = concentration risk Average deal age exceeding 1.5x normal cycle = stalling Declining demo-to-close rate = product-market fit erosion Rising CAC payback period = unit economics degrading
Revenue Recognition Notes
SaaS: Recognize ratably over contract term Services: Recognize on delivery/milestones Usage-based: Recognize on consumption Annual prepay: Deferred revenue, recognize monthly Built by AfrexAI — AI context packs for business operators who ship. Get the full toolkit: AI Revenue Leak Calculator — Find where you're losing money Context Packs — Industry-specific AI agent configs ($47/pack) Agent Setup Wizard — Deploy your first AI agent in 15 minutes Bundles: Playbook $27 | Pick 3 for $97 | All 10 for $197 | Everything Bundle $247
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- README.md