find-arbitrage-opps

hummingbot/skills · updated Apr 8, 2026

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$npx skills add https://github.com/hummingbot/skills --skill find-arbitrage-opps
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summary

Find arbitrage opportunities across all Hummingbot-connected exchanges by comparing prices for a trading pair, accounting for fungible tokens (e.g., BTC = WBTC, USDT = USDC).

skill.md

find-arbitrage-opps

Find arbitrage opportunities across all Hummingbot-connected exchanges by comparing prices for a trading pair, accounting for fungible tokens (e.g., BTC = WBTC, USDT = USDC).

Prerequisites

Hummingbot API must be running with exchange connectors configured:

bash <(curl -s https://raw.githubusercontent.com/hummingbot/skills/main/skills/lp-agent/scripts/check_prerequisites.sh)

DEX Support

By default the script queries CEX connectors via the Hummingbot API. Add --dex to also fetch prices from:

DEX Chain Default Network
Jupiter Solana mainnet-beta
Uniswap Ethereum mainnet
PancakeSwap Ethereum (BSC) bsc

DEX prices are fetched directly via the Hummingbot Gateway. Make sure Gateway is running on http://localhost:15888 (or set GATEWAY_URL).

⚠️ BTC markets are only available to Australian residents on some exchanges. A warning is printed automatically when BTC/WBTC/cbBTC is included in the search.

Workflow

Step 1: Define Token Mappings

User specifies the base and quote tokens, including fungible equivalents:

  • Base tokens: BTC, WBTC, cbBTC (all represent Bitcoin)
  • Quote tokens: USDT, USDC, USD (all represent USD)

Step 2: Find Arbitrage Opportunities

# Basic - CEX only
python scripts/find_arb_opps.py --base BTC --quote USDT

# Include fungible tokens
python scripts/find_arb_opps.py --base BTC,WBTC --quote USDT,USDC

# Include DEX prices (Jupiter + Uniswap via Gateway)
python scripts/find_arb_opps.py --base SOL --quote USDC --dex
python scripts/find_arb_opps.py --base ETH,WETH --quote USDT,USDC --dex

# Minimum spread filter
python scripts/find_arb_opps.py --base SOL --quote USDC --dex --min-spread 0.1

# Filter to specific CEX connectors
python scripts/find_arb_opps.py --base BTC --quote USDT --connectors binance,kraken,coinbase

Step 3: Analyze Results

The script outputs:

  • Prices from each CEX and DEX source
  • Best bid/ask across all sources
  • Arbitrage spread (buy low, sell high)
  • Recommended pairs for arbitrage

Script Options

python scripts/find_arb_opps.py --help
Option Description
--base Base token(s), comma-separated (e.g., BTC,WBTC)
--quote Quote token(s), comma-separated (e.g., USDT,USDC)
--connectors Filter to specific CEX connectors (optional)
--dex Include DEX prices via Gateway (Jupiter + Uniswap)
--min-spread Minimum spread % to show (default: 0.0)
--json Output as JSON

Output Example

============================================================
  SOL / USDC Arbitrage Scanner
  DEX: Jupiter (Solana mainnet-beta), Uniswap (Ethereum mainnet)
============================================================

  Lowest:  binance                   $132.4500
  Highest: jupiter (DEX)             $132.8900
  Spread:  0.332% ($0.4400)
  Sources: 5 prices from 5 sources

  Top Arbitrage Opportunities:
  --------------------------------------------------------
  1. Buy  binance                   @ $132.4500
     Sell jupiter (DEX)             @ $132.8900
     Profit: 0.332% ($0.4400)

Environment Variables

export HUMMINGBOT_API_URL=http://localhost:8000
export API_USER=admin
export API_PASS=admin
export GATEWAY_URL=http://localhost:15888   # for DEX prices

Scripts check for .env in: ./hummingbot-api/.env~/.hummingbot/.env.env

Requirements

  • Hummingbot API running (for CEX prices)
  • Gateway running (for DEX prices with --dex flag)
  • Exchange connectors configured with API keys
how to use find-arbitrage-opps

How to use find-arbitrage-opps on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add find-arbitrage-opps
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/hummingbot/skills --skill find-arbitrage-opps

The skills CLI fetches find-arbitrage-opps from GitHub repository hummingbot/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/find-arbitrage-opps

Reload or restart Cursor to activate find-arbitrage-opps. Access the skill through slash commands (e.g., /find-arbitrage-opps) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.733 reviews
  • Dhruvi Jain· Dec 24, 2024

    find-arbitrage-opps reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Luis Khan· Dec 24, 2024

    I recommend find-arbitrage-opps for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sofia Gupta· Dec 16, 2024

    find-arbitrage-opps fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Kabir Malhotra· Dec 12, 2024

    Registry listing for find-arbitrage-opps matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sophia Park· Nov 19, 2024

    Solid pick for teams standardizing on skills: find-arbitrage-opps is focused, and the summary matches what you get after install.

  • Oshnikdeep· Nov 15, 2024

    I recommend find-arbitrage-opps for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Noah Sharma· Nov 15, 2024

    find-arbitrage-opps reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Mateo Park· Nov 7, 2024

    find-arbitrage-opps is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Noah Reddy· Nov 3, 2024

    Useful defaults in find-arbitrage-opps — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Mateo Patel· Oct 26, 2024

    Keeps context tight: find-arbitrage-opps is the kind of skill you can hand to a new teammate without a long onboarding doc.

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