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prod-fairflow-calculator(prod fairflow calculator 命令行)

prod-fairflow-calculator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

prod-fairflow-calculator 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 9,557。

总安装 238周安装 10GitHub Stars 2下载 83核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:prod-fairflow-calculator(prod fairflow calculator 命令行)
来源仓库:https://github.com/hungv47/agent-skills
仓库路径:skills/prod-fairflow-calculator
安装命令:
npx skills add https://github.com/hungv47/agent-skills --skill prod-fairflow-calculator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/hungv47/agent-skills --skill prod-fairflow-calculator

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于计算产品流动效率或生产节拍相关指标。prod-fairflow-calculator 属于待分类类 Skill,可作为该场景下的辅助能力补充。适合在生产排程、瓶颈识别或产能评估中使用。通过 GitHub 安装,支持 Codex、Claude、Cursor 和 Gemini CLI 等宿主环境。

使用时需提供时间、数量或工序参数作为输入。安装前建议确认权限范围,避免触发敏感计算或导出操作。

来源仓库内路径:skills/prod-fairflow-calculator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/hungv47/agent-skills --skill prod-fairflow-cal…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

prod-fairflow-calculator 怎么安装?

在终端执行 npx skills add https://github.com/hungv47/agent-skills --skill prod-fairflow-calculator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

prod-fairflow-calculator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

prod-fairflow-calculator 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

prod-fairflow-calculator 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

prod-fairflow-calculator 用的人多吗?

公开数据是累计安装 238 次,近一周安装 10 次,下载 83 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

prod-fairflow-calculator 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
prod-fairflow-calculator

prod fairflow calculator 命令行 · 本页

2382只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

FairFlow Campaign Calculator

Help users plan, calculate, and evaluate FairFlow liquidity mining campaigns with data-driven projections and efficiency metrics.

Philosophy

Sustainable yield beats speculation. Good liquidity mining campaigns have:

  • Data-driven projections - Calculations based on realistic assumptions, not hopium
  • Efficiency tracking - Cost per $1M volume, cost per $1 TVL matter more than raw spend
  • EG honesty - Equilibrium Gains are market-dependent and unpredictable; model scenarios, don't guess
  • Clear graduation path - Every campaign should have criteria for reducing LM dependency
  • ROI focus - Fee revenue vs LM spend determines long-term viability

This skill answers three questions:

  1. What to spend? - LM budget to achieve target APR
  2. What to expect? - Projected TVL, volume, and efficiency metrics
  3. When to adjust? - Decision rules for scaling, maintaining, or killing campaigns

Mode Detection

Determine the operating mode based on user input:

Plan Mode (Design a new campaign):

  • User says "plan a FairFlow campaign", "new campaign", "design a campaign"
  • User has a pair in mind but no projections yet
  • User wants help setting LM budget and targets

Analysis Mode (Calculate specific metrics):

  • User says "calculate LP APR", "what's the LM APR", "estimate break-even"
  • User has specific numbers and wants calculations
  • User wants to understand a single metric

Review Mode (Evaluate existing campaign):

  • User says "evaluate campaign", "review my campaign", "is my campaign efficient"
  • User has an active campaign with actual data
  • User wants to compare actuals vs projections

If unclear, ask: *"Do you want to (1) plan a new campaign, (2) calculate specific metrics, or (3) review an existing campaign?"*


Plan Mode

Use this when helping users design new FairFlow campaigns.

Plan Mode Overview

Inputs → APR Calculations → Efficiency Projections → EG Scenarios → Validation

Step 1: Gather Campaign Inputs

Ask (using AskUserQuestion):

Pool Configuration - What pair? (e.g., MON/USDC) - Which chain? - What fee tier? (0.01%, 0.05%, 0.30%) - Fee tier in bps? (1, 5, 30 — needed for EG adjustment calculation)
LM Configuration - What LM token? (KNC or partner token) - Current LM token price? - Campaign duration? (weeks)
Targets & Competition - What's your target TVL? - What's the competitor APR you're competing against? - What APR gap do you want to maintain? (+15%, +25%, etc.)
Current State - Current TVL (if any)? - Current daily volume (if any)?

Step 2: Calculate APR Components

Use the formulas to calculate each APR component.

See references/formulas.md for all calculation formulas.

LP Fee APR:

Daily Fee Revenue = Volume × bps
LP Fee APR = (Daily Fee Revenue / TVL) × 365

LM APR (solve for LM budget):

Required LM APR = Target Total APR - LP Fee APR - EG APR (estimated)
Daily LM Value = (LM APR × TVL) / 365
Daily LM Tokens = Daily LM Value / Token Price

Base APR (without EG):

Base APR = LP Fee APR + LM APR

Step 3: Model EG Scenarios

EG (Equilibrium Gains) cannot be predicted. Always present three scenarios. EG multipliers scale inversely with fee tier — lower-fee pools capture proportionally more EG relative to fees.

Fee-tier adjustment:

EG Multiplier = Scenario Base × (5 / pool_bps)
ScenarioBase (at 0.05%)AdjustmentWhen This Happens
Low0.50× (5 / bps)Low volatility, stable markets
Mid1.00× (5 / bps)Normal market conditions
High2.00× (5 / bps)High volatility, active arbitrage

Adjusted multipliers by fee tier:

Fee TierbpsLowMidHigh
0.01%12.505.0010.00
0.05%50.501.002.00
0.30%300.080.170.33

Example at 0.01% (1 bp): If LP Fee APR = 7.30%

  • Low EG: 18.25% (2.50 × 7.30%)
  • Mid EG: 36.50% (5.00 × 7.30%)
  • High EG: 73.00% (10.00 × 7.30%)

Example at 0.05% (5 bp): If LP Fee APR = 7.30%

  • Low EG: 3.65% (0.50 × 7.30%)
  • Mid EG: 7.30% (1.00 × 7.30%)
  • High EG: 14.60% (2.00 × 7.30%)

Total APR by scenario:

Total APR = LP Fee APR + EG APR + LM APR

Step 4: Project Weekly Metrics

Build a weekly projection table:

WeekTVL TargetVolume TargetVol/TVLLP Fee APRLM APRBase APREG LowEG MidEG HighTotal (Mid)Weekly LMCumulative LM
1
2
3
4

Step 5: Calculate Efficiency Metrics

For each week, calculate:

MetricFormulaTarget
LM Cost per $1M VolumeWeekly LM Spend / (Weekly Volume / 1M)< $1,000
LM Cost per $1K TVLMonthly LM Spend / (TVL / 1K)< $50
Cost per $1 TVL AcquiredCumulative LM / (Current TVL - Starting TVL)< $0.10
Fee Revenue RatioMonthly Fee Revenue / Monthly LM Spend> 50%

See references/benchmarks.md for efficiency targets.

Step 6: Validate Campaign

Run validation checks:

APR Gap Check:

  • Is APR gap sufficient? (> 15% minimum, > 25% strong)
  • Is gap maintained across all EG scenarios?

Efficiency Check:

  • LM cost per $1M volume < $1,000?
  • Cost per $1 TVL acquired < $0.10?

Sustainability Check:

  • What Vol/TVL is needed to self-sustain without LM?
  • Is that Vol/TVL realistic for this pair?

See references/decision-framework.md for decision rules.

Plan Mode Output

Produce a Campaign Plan document:

# FairFlow Campaign: [PAIR]

## Overview
| Field | Value |
|-------|-------|
| **Pair** | [TOKEN_A/TOKEN_B] |
| **Chain** | [Chain] |
| **Fee Tier** | [X%] ([X] bps) |
| **EG Adjustment** | 5 / [bps] = [X]× (Low: [X], Mid: [X], High: [X]) |
| **Duration** | [X weeks] |
| **Total Budget** | [X tokens] ($X USD) |
| **Target TVL** | $[X] |

## APR Breakdown

### By Week
| Week | TVL | Volume | Vol/TVL | Fee APR | LM APR | Base APR | EG (Low/Mid/High) | Total (Mid) |
|------|-----|--------|---------|---------|--------|----------|-------------------|-------------|
| 1 | | | | | | | | |
| ... | | | | | | | | |

### Competitive Positioning
| Scenario | Total APR | vs Competitor | Gap |
|----------|-----------|---------------|-----|
| Low EG | X% | X% | +X% |
| Mid EG | X% | X% | +X% |
| High EG | X% | X% | +X% |

## Efficiency Metrics
| Metric | Week 1 | Week 4 | Target | Status |
|--------|--------|--------|--------|--------|
| LM per $1M Volume | | | <$1,000 | |
| Cost per $1 TVL | | | <$0.10 | |
| Fee Revenue Ratio | | | >50% | |

## Graduation Path
- Break-even Vol/TVL: [X]
- Current projected Vol/TVL: [X]
- Path to reduce LM: [description]

## Success Criteria
| Criteria | Threshold | Action |
|----------|-----------|--------|
| Ship | [condition] | Scale up |
| Maintain | [condition] | Continue as-is |
| Kill | [condition] | Stop campaign |

## Weekly Review Checklist
- [ ] TVL vs target (within 20%?)
- [ ] Vol/TVL ratio (above 1.5?)
- [ ] APR gap still competitive?
- [ ] LM efficiency improving?
- [ ] External factors (competitor moves, market)?
- [ ] Decision: Scale / Maintain / Reduce / Kill

Analysis Mode

Use this when users need specific metric calculations.

Common Calculations

"What LM budget do I need for X% APR?"

Daily LM Value = (Target LM APR × TVL) / 365
Weekly LM USD = Daily LM Value × 7
Weekly LM Tokens = Weekly LM USD / Token Price

"What's my LP Fee APR?"

Daily Fee Revenue = Daily Volume × Fee Tier (as decimal)
LP Fee APR = (Daily Fee Revenue / TVL) × 365

"What Vol/TVL do I need to break even?"

Required Fee APR = Target APR - Expected EG APR
Vol/TVL = Required Fee APR / (Fee Tier × 365)

"Is my campaign efficient?"

LM Cost per $1M Volume = Weekly LM Spend / (Weekly Volume / 1,000,000)
< $1,000 = Good, < $500 = Excellent

See references/formulas.md for the complete formula reference.

Analysis Output

Provide calculations with work shown:

## Calculation: [Metric Name]

### Inputs
- [Input 1]: [Value]
- [Input 2]: [Value]

### Formula

[Formula here]

### Calculation

[Step-by-step calculation]

### Result
**[Metric Name]:** [Value]

### Interpretation
[What this means, whether it's good/bad, what to do about it]

Review Mode

Use this when evaluating active campaigns against projections.

Step 1: Gather Actual Data

Ask:

Current Campaign Status - Current TVL (actual)? - Current daily volume (actual)? - Weekly LM spend to date? - Campaign week number?
Projected vs Actual - What were your TVL projections? - What were your volume projections?

Step 2: Calculate Variance

MetricProjectedActualVariance
TVL$X$X+/- X%
Volume$X$X+/- X%
Vol/TVLXX+/- X%
LP Fee APRX%X%+/- X%

Step 3: Apply Decision Framework

Based on actuals, recommend action:

ConditionAction
TVL growth > 20% WoW AND Vol/TVL > 1.5Scale LM +25%
TVL growth > 10% WoW AND APR gap > 20%Maintain current LM
TVL flat AND Vol/TVL > 2.0Reduce LM -15%
TVL declining AND APR gap > 30%Diagnose external factors
TVL < 50% of target after 2 weeksKill campaign
Vol/TVL < 0.5 for 2 consecutive weeksKill campaign
LM Cost per $1M Volume > $2,000Kill campaign

See references/decision-framework.md for complete decision rules.

Step 4: Check Graduation Criteria

Graduation SignalStatus
Base APR (Fees + EG) > Competitor APRCan begin LM reduction
TVL stable for 4 weeks at reduced LMContinue reduction
Vol/TVL > 2.5 sustainedPool is self-sustaining

Review Output

## Campaign Review: [PAIR] - Week [X]

### Performance Summary
| Metric | Projected | Actual | Variance | Status |
|--------|-----------|--------|----------|--------|
| TVL | $X | $X | X% | ✅/⚠️/❌ |
| Volume | $X | $X | X% | ✅/⚠️/❌ |
| Vol/TVL | X | X | X% | ✅/⚠️/❌ |

### Efficiency
| Metric | Actual | Target | Status |
|--------|--------|--------|--------|
| LM per $1M Vol | $X | <$1,000 | ✅/❌ |
| Cost per $1 TVL | $X | <$0.10 | ✅/❌ |

### Decision
**Recommendation:** [Scale / Maintain / Reduce / Kill]
**Reasoning:** [Why this recommendation]

### Next Week Actions
1. [Action item]
2. [Action item]

Integration Points

SkillHow FairFlow Calculator Connects
mkt-funnel-plannerCampaign metrics feed into broader funnel tracking; LP retention is a funnel stage
mkt-initiative-plannerFairFlow campaigns become initiative proposals with defined hypotheses and success criteria

When working with these skills:

  • Campaign success criteria align with initiative KPIs
  • LP retention metrics connect to funnel D30/D90 tracking
  • Campaign budgets inform initiative resource planning

How to Work

  • Show your math: Always display calculations step-by-step, not just final answers
  • EG is unpredictable: Never present EG as a single number; always show Low/Mid/High scenarios
  • Efficiency > raw spend: A $50K campaign that's inefficient is worse than a $10K efficient one
  • Challenge unrealistic targets: If Vol/TVL assumptions are aggressive, say so
  • Kill criteria matter: Every campaign needs clear conditions for stopping
  • Graduation path: Always define how the campaign becomes self-sustaining
  • Weekly reviews: Recommend actual vs projected comparison weekly

Anti-Patterns to Avoid

Don'tDo
Present single EG projectionAlways show Low/Mid/High scenarios
Ignore efficiency metricsCalculate cost per $1M volume and cost per $1 TVL
Skip break-even analysisAlways show what Vol/TVL is needed to self-sustain
Set targets without kill criteriaDefine stop conditions upfront
Assume LM continues foreverPlan graduation path from day one

平台分布

Codex

35.69%
按下载量换算30

Claude

31.36%
按下载量换算26

Cursor

18.79%
按下载量换算16

Gemini CLI

8.58%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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