[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6Q4AD9QBNEB6Q7GDMDAJDQB":3,"skill-same:01M6Q4AD9QBNEB6Q7GDMDAJDQB":65},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":6,"ownerHtmlUrl":48,"ownerBlogUrl":6,"ownerDescription":49,"updatedAt":50,"install":51,"resources":64},"01M6Q4AD9QBNEB6Q7GDMDAJDQB","revnet-modeler",null,"Revnet simulation and planning tool for modeling token dynamics. Use when: (1) planning\nrevnet parameters before deployment, (2) visualizing treasury\u002Ftoken dynamics over time,\n(3) comparing different scenarios (loans, cash-outs, investments), (4) understanding\nchart outputs, (5) explaining simulation results. Covers stage configuration, event\nsequences, and all chart types.","Kernel8901\u002Fai-agent-skills-classification","Kernel8901","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F72647553?v=4","01M6KV388J2H5PNC8D8P940BJD","01M6KV38CS5B3AY63RKZB410YM",7,"MIT","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F视觉与设计\u002Fjuicy\u002Frevnet-modeler\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"revnet modeler","stage","outputs","for","treasury","event","types","dynamics","chart","modeling","deployment","token","time","configuration","use","results","tool","simulation","loans","planning","2026-11-10 10:12:30",false,"---\nname: revnet-modeler\ndescription: |\n  Revnet simulation and planning tool for modeling token dynamics. Use when: (1) planning\n  revnet parameters before deployment, (2) visualizing treasury\u002Ftoken dynamics over time,\n  (3) comparing different scenarios (loans, cash-outs, investments), (4) understanding\n  chart outputs, (5) explaining simulation results. Covers stage configuration, event\n  sequences, and all chart types.\n---\n\n# Revnet Modeler: Simulation Tool\n\n## Problem\n\nPlanning revnet parameters requires understanding how different configurations affect\ntreasury dynamics, token distribution, and participant outcomes over time. The modeler\nsimulates these dynamics before deployment.\n\n## Context \u002F Trigger Conditions\n\n- Planning a new revnet deployment\n- Comparing different parameter configurations\n- Understanding how events (investments, loans, cash-outs) affect the system\n- Visualizing treasury and token dynamics\n- Explaining chart outputs to users\n\n## Solution\n\n### Tool Location\n\n```\nhttps:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Findex.html\n```\n\nOpen in browser to use the interactive modeler.\n\n### Seven Economic Levers (Per Stage)\n\nEach stage can configure:\n\n| Lever | Description | Effect |\n|-------|-------------|--------|\n| **Stage Start Day** | When this stage begins | Defines stage transitions |\n| **Initial Issuance Rate** | Tokens minted per $ | Higher = more tokens per payment |\n| **Issuance Cut %** | % reduction per period | Creates supply scarcity over time |\n| **Issuance Cut Frequency** | Days between cuts | Controls cut rate (7, 14, 28 days) |\n| **Split %** | % of minted tokens to splits | Team\u002Freserved allocation |\n| **Cash-Out Tax Rate** | Bonding curve tax (0-100%) | Higher = more treasury retention |\n| **Auto-Issuances** | Automatic token mints | Pre-scheduled distributions |\n\n### Event Types\n\nThe modeler supports these event types:\n\n| Event | Description | Treasury Effect |\n|-------|-------------|-----------------|\n| `investment` | External payment | + backing, + supply |\n| `revenue` | Operating revenue | + backing, + supply |\n| `loan` | Take loan against tokens | - backing (net of fees) |\n| `payback-loan` | Repay loan | + backing |\n| `cashout` | Redeem tokens | - backing, - supply |\n\nEvents are labeled by participant (e.g., \"Team\", \"Investor A\", \"Customer\").\n\n### Available Charts\n\n#### Treasury & Value Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Treasury Backing** | Total backing over time | Overall treasury health |\n| **Cash Out Value** | Per-token redemption value | Floor price dynamics |\n| **Issuance Price** | Token mint cost | Ceiling price with cuts |\n| **Cash Flows** | Inflows\u002Foutflows by day | Event impact on treasury |\n\n#### Token Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Token Distribution** | Tokens by holder (liquid + locked) | Who holds what |\n| **Ownership %** | Percentage ownership over time | Dilution visualization |\n| **Token Valuations** | Dollar value of holdings | Participant wealth |\n| **Token Performance** | ROI % by participant | Investment returns |\n\n#### Loan Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Loan Potential** | Max borrowable by holder | Available liquidity |\n| **Loan Status** | Outstanding loan amounts | Current debt |\n| **Outstanding Loans** | Loan values over time | Debt trajectory |\n| **Tokens Backing Loans %** | % of tokens as collateral | Leverage exposure |\n\n#### Fee Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Fee Flows** | Internal vs external fees | Fee destination breakdown |\n\n### State Machine Calculations\n\nThe modeler uses a state machine (`StateMachine.getStateAtDay(day)`) that tracks:\n\n```javascript\n{\n  day: number,\n  revnetBacking: number,      \u002F\u002F Treasury balance\n  totalSupply: number,        \u002F\u002F Total token supply\n  tokensByLabel: {            \u002F\u002F Tokens held by each participant\n    \"Team\": 1000,\n    \"Investor A\": 500,\n    ...\n  },\n  dayLabeledInvestorLoans: {  \u002F\u002F Outstanding loan amounts by participant\n    \"Team\": 50000,\n    ...\n  },\n  loanHistory: {              \u002F\u002F Detailed loan records\n    \"Team\": [\n      { amount: 50000, remainingTokens: 100, ... }\n    ]\n  }\n}\n```\n\n### Key Formulas\n\n#### Cash-Out Value (Bonding Curve)\n\n```javascript\ncalculateCashOutValueForEvent(tokensToCash, totalSupply, backing, cashOutTax) {\n  const proportionalShare = backing * tokensToCash \u002F totalSupply\n  const taxMultiplier = (1 - cashOutTax) + (tokensToCash * cashOutTax \u002F totalSupply)\n  return proportionalShare * taxMultiplier\n}\n```\n\n#### Loan Fees\n\n```javascript\n\u002F\u002F Internal fee (to treasury)\nconst internalFee = loanAmount * 0.025  \u002F\u002F 2.5%\n\n\u002F\u002F External fee (to protocol)\nconst externalFee = loanAmount * 0.035  \u002F\u002F 3.5%\n\n\u002F\u002F Interest (after grace period)\nconst annualInterest = 0.05  \u002F\u002F 5% after 6-month grace period\n```\n\n### Pre-Built Scenarios\n\nThe modeler includes pre-configured scenarios:\n\n| Scenario | Description |\n|----------|-------------|\n| `conservative-growth` | Steady investment, gradual expansion |\n| `hypergrowth` | Rapid investment, high volatility |\n| `bootstrap-scale` | Small start, then scale-up |\n| `vc-fueled` | Large early investment, then revenue |\n| `community-driven` | Many small investments |\n| `boom-bust` | Growth followed by cash-outs |\n\nEach has variants: `-with-loans`, `-with-exits`\n\n### Interpreting Results\n\n#### Treasury Health\n- **Healthy:** Backing grows over time, floor price increases\n- **Warning:** Backing flat or declining, many cash-outs\n- **Critical:** Large loan defaults, negative treasury trajectory\n\n#### Token Distribution\n- **Balanced:** No single holder > 50%\n- **Concentrated:** Few holders control majority\n- **Diluted:** Early holders significantly diluted\n\n#### Loan Exposure\n- **Safe:** \u003C 20% of tokens backing loans\n- **Moderate:** 20-50% collateralized\n- **High:** > 50% collateralized (systemic risk)\n\n### Using for Planning\n\n1. **Set stages** matching your fundraising\u002Fgrowth plan\n2. **Add events** representing expected investments, revenue, exits\n3. **Run simulation** and review charts\n4. **Iterate** on parameters until dynamics match goals\n5. **Compare** multiple scenarios to stress-test\n\n## Verification\n\n1. Verify cash-out calculations match bonding curve formula\n2. Check loan fees sum to expected percentages\n3. Confirm token distribution adds to total supply\n4. Validate treasury balance equals sum of inflows - outflows\n\n## Example\n\nPlanning a revnet with team allocation and investor entry:\n\n```\nStage 1 (Days 0-90):\n  - Issuance: 1,000,000 tokens\u002F$\n  - Split: 30% to Team\n  - Cash-out tax: 10%\n\nEvents:\n  Day 1: Team invests $10,000\n  Day 30: Investor A invests $50,000\n  Day 60: Revenue $20,000\n  Day 90: Team takes loan (50% of tokens)\n\nRun simulation → Review:\n  - Token Distribution: Team 30%, Investor A 50%, Revenue recipients 20%\n  - Team's loan potential and actual loan\n  - Treasury backing trajectory\n  - Cash-out value for each participant\n```\n\n## Notes\n\n- Modeler uses simplified fee model (may differ from exact contract implementation)\n- Simulations are deterministic given same inputs\n- Charts update automatically when parameters change\n- Export scenarios for comparison and documentation\n- The modeler runs entirely client-side (no data sent externally)\n\n## References\n\n- Tool: `https:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Findex.html`\n- State machine: `https:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Fjs\u002Fstate.js`\n- Charts: `https:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Fjs\u002FchartManager.js`\n- Academic validation: `\u002Frevnet-economics` skill\n","# Revnet Modeler: Simulation Tool\n\n## Problem\n\nPlanning revnet parameters requires understanding how different configurations affect\ntreasury dynamics, token distribution, and participant outcomes over time. The modeler\nsimulates these dynamics before deployment.\n\n## Context \u002F Trigger Conditions\n\n- Planning a new revnet deployment\n- Comparing different parameter configurations\n- Understanding how events (investments, loans, cash-outs) affect the system\n- Visualizing treasury and token dynamics\n- Explaining chart outputs to users\n\n## Solution\n\n### Tool Location\n\n```\nhttps:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Findex.html\n```\n\nOpen in browser to use the interactive modeler.\n\n### Seven Economic Levers (Per Stage)\n\nEach stage can configure:\n\n| Lever | Description | Effect |\n|-------|-------------|--------|\n| **Stage Start Day** | When this stage begins | Defines stage transitions |\n| **Initial Issuance Rate** | Tokens minted per $ | Higher = more tokens per payment |\n| **Issuance Cut %** | % reduction per period | Creates supply scarcity over time |\n| **Issuance Cut Frequency** | Days between cuts | Controls cut rate (7, 14, 28 days) |\n| **Split %** | % of minted tokens to splits | Team\u002Freserved allocation |\n| **Cash-Out Tax Rate** | Bonding curve tax (0-100%) | Higher = more treasury retention |\n| **Auto-Issuances** | Automatic token mints | Pre-scheduled distributions |\n\n### Event Types\n\nThe modeler supports these event types:\n\n| Event | Description | Treasury Effect |\n|-------|-------------|-----------------|\n| `investment` | External payment | + backing, + supply |\n| `revenue` | Operating revenue | + backing, + supply |\n| `loan` | Take loan against tokens | - backing (net of fees) |\n| `payback-loan` | Repay loan | + backing |\n| `cashout` | Redeem tokens | - backing, - supply |\n\nEvents are labeled by participant (e.g., \"Team\", \"Investor A\", \"Customer\").\n\n### Available Charts\n\n#### Treasury & Value Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Treasury Backing** | Total backing over time | Overall treasury health |\n| **Cash Out Value** | Per-token redemption value | Floor price dynamics |\n| **Issuance Price** | Token mint cost | Ceiling price with cuts |\n| **Cash Flows** | Inflows\u002Foutflows by day | Event impact on treasury |\n\n#### Token Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Token Distribution** | Tokens by holder (liquid + locked) | Who holds what |\n| **Ownership %** | Percentage ownership over time | Dilution visualization |\n| **Token Valuations** | Dollar value of holdings | Participant wealth |\n| **Token Performance** | ROI % by participant | Investment returns |\n\n#### Loan Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Loan Potential** | Max borrowable by holder | Available liquidity |\n| **Loan Status** | Outstanding loan amounts | Current debt |\n| **Outstanding Loans** | Loan values over time | Debt trajectory |\n| **Tokens Backing Loans %** | % of tokens as collateral | Leverage exposure |\n\n#### Fee Charts\n\n| Chart | Shows | Key Insight |\n|-------|-------|-------------|\n| **Fee Flows** | Internal vs external fees | Fee destination breakdown |\n\n### State Machine Calculations\n\nThe modeler uses a state machine (`StateMachine.getStateAtDay(day)`) that tracks:\n\n```javascript\n{\n  day: number,\n  revnetBacking: number,      \u002F\u002F Treasury balance\n  totalSupply: number,        \u002F\u002F Total token supply\n  tokensByLabel: {            \u002F\u002F Tokens held by each participant\n    \"Team\": 1000,\n    \"Investor A\": 500,\n    ...\n  },\n  dayLabeledInvestorLoans: {  \u002F\u002F Outstanding loan amounts by participant\n    \"Team\": 50000,\n    ...\n  },\n  loanHistory: {              \u002F\u002F Detailed loan records\n    \"Team\": [\n      { amount: 50000, remainingTokens: 100, ... }\n    ]\n  }\n}\n```\n\n### Key Formulas\n\n#### Cash-Out Value (Bonding Curve)\n\n```javascript\ncalculateCashOutValueForEvent(tokensToCash, totalSupply, backing, cashOutTax) {\n  const proportionalShare = backing * tokensToCash \u002F totalSupply\n  const taxMultiplier = (1 - cashOutTax) + (tokensToCash * cashOutTax \u002F totalSupply)\n  return proportionalShare * taxMultiplier\n}\n```\n\n#### Loan Fees\n\n```javascript\n\u002F\u002F Internal fee (to treasury)\nconst internalFee = loanAmount * 0.025  \u002F\u002F 2.5%\n\n\u002F\u002F External fee (to protocol)\nconst externalFee = loanAmount * 0.035  \u002F\u002F 3.5%\n\n\u002F\u002F Interest (after grace period)\nconst annualInterest = 0.05  \u002F\u002F 5% after 6-month grace period\n```\n\n### Pre-Built Scenarios\n\nThe modeler includes pre-configured scenarios:\n\n| Scenario | Description |\n|----------|-------------|\n| `conservative-growth` | Steady investment, gradual expansion |\n| `hypergrowth` | Rapid investment, high volatility |\n| `bootstrap-scale` | Small start, then scale-up |\n| `vc-fueled` | Large early investment, then revenue |\n| `community-driven` | Many small investments |\n| `boom-bust` | Growth followed by cash-outs |\n\nEach has variants: `-with-loans`, `-with-exits`\n\n### Interpreting Results\n\n#### Treasury Health\n- **Healthy:** Backing grows over time, floor price increases\n- **Warning:** Backing flat or declining, many cash-outs\n- **Critical:** Large loan defaults, negative treasury trajectory\n\n#### Token Distribution\n- **Balanced:** No single holder > 50%\n- **Concentrated:** Few holders control majority\n- **Diluted:** Early holders significantly diluted\n\n#### Loan Exposure\n- **Safe:** \u003C 20% of tokens backing loans\n- **Moderate:** 20-50% collateralized\n- **High:** > 50% collateralized (systemic risk)\n\n### Using for Planning\n\n1. **Set stages** matching your fundraising\u002Fgrowth plan\n2. **Add events** representing expected investments, revenue, exits\n3. **Run simulation** and review charts\n4. **Iterate** on parameters until dynamics match goals\n5. **Compare** multiple scenarios to stress-test\n\n## Verification\n\n1. Verify cash-out calculations match bonding curve formula\n2. Check loan fees sum to expected percentages\n3. Confirm token distribution adds to total supply\n4. Validate treasury balance equals sum of inflows - outflows\n\n## Example\n\nPlanning a revnet with team allocation and investor entry:\n\n```\nStage 1 (Days 0-90):\n  - Issuance: 1,000,000 tokens\u002F$\n  - Split: 30% to Team\n  - Cash-out tax: 10%\n\nEvents:\n  Day 1: Team invests $10,000\n  Day 30: Investor A invests $50,000\n  Day 60: Revenue $20,000\n  Day 90: Team takes loan (50% of tokens)\n\nRun simulation → Review:\n  - Token Distribution: Team 30%, Investor A 50%, Revenue recipients 20%\n  - Team's loan potential and actual loan\n  - Treasury backing trajectory\n  - Cash-out value for each participant\n```\n\n## Notes\n\n- Modeler uses simplified fee model (may differ from exact contract implementation)\n- Simulations are deterministic given same inputs\n- Charts update automatically when parameters change\n- Export scenarios for comparison and documentation\n- The modeler runs entirely client-side (no data sent externally)\n\n## References\n\n- Tool: `https:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Findex.html`\n- State machine: `https:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Fjs\u002Fstate.js`\n- Charts: `https:\u002F\u002Fgithub.com\u002Fmejango\u002Frev-sim\u002Fjs\u002FchartManager.js`\n- Academic validation: `\u002Frevnet-economics` skill\n",{"name":5,"description":7},"main","f4cb2d49f7667e79ef7804f50396d5aaffdf1f56","视觉与设计\u002Fjuicy\u002Frevnet-modeler",1,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification","https:\u002F\u002Fgithub.com\u002FKernel8901","a little little little dobe in life but science geek","2026-04-05 16:43:56",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add Kernel8901\u002Fai-agent-skills-classification --skill revnet-modeler",{"tool":57,"command":58},"bunx","bunx skills add Kernel8901\u002Fai-agent-skills-classification --skill revnet-modeler",{"tool":60,"command":61},"pnpm","pnpm dlx skills add Kernel8901\u002Fai-agent-skills-classification --skill revnet-modeler","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F视觉与设计\u002Fjuicy\u002Frevnet-modeler\u002FSKILL.md",true,[],[66,89,124,135,145,173],{"skillNo":67,"name":68,"nameZh":6,"description":69,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":70,"categories":71,"keywords":72,"publishedAt":38},"01M6Q5R6WZ06RRB9RQTW54B34B","zyfai","Earn yield on any Ethereum wallet on Base, Arbitrum, and Plasma. 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