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Description

This PR adds the Pond action provider integration to AgentKit (Typescript), enabling access to Pond's comprehensive on-chain analytics and data services. The integration includes:

  1. A new PondActionProvider class that provides the following actions:

    • get_wallet_risk_score (WalletRiskScoreSchema): Assesses wallet risk based on activity patterns

      • Example: "Is this wallet 0x123... safe to interact with?"
      • Provides risk scores and data completeness metrics
      • Available for Base chain wallets
    • get_wallet_summary (WalletSummarySchema): Provides detailed wallet activity analytics

      • Example: "Show me the trading activity of 0x123... in the last month"
      • Transaction counts, DEX trading volume, PNL, portfolio diversity
      • Available for Base, Ethereum, and Solana chains
    • get_sybil_prediction (SybilPredictionSchema): Detects potential Sybil wallet behavior

      • Example: "Is this wallet 0x123... likely a Sybil account?"
      • Provides Sybil likelihood scores and data completeness
      • Available for Base chain wallets
    • get_token_price_prediction (TokenPricePredictionSchema): Predicts token price movements

      • Example: "What's the price prediction for token 0x123... in the next 24h?"
      • Supports multiple timeframes (3h, 6h, 12h, 24h)
      • Available for Base chain tokens
    • get_token_risk_scores (TokenRiskScoreSchema): Comprehensive token risk assessment

      • Example: "How risky is token 0x123... according to different models?"
      • Uses multiple risk assessment models (THE_DAY, MR_HEOS, NILSSON_LIENE)
      • Available for Base chain tokens
    • get_top_solana_meme_coins (TopSolanaMemeCoinsSchema): Analyzes trending Solana meme coins

      • Example: "What are the top trending meme coins on Solana right now?"
      • Provides price changes, trading volumes, and market metrics
      • Supports multiple timeframes
    • get_base_data_analysis (BaseDataAnalystSchema): Advanced LLM-powered analysis of Base chain data

      • Example: "What tokens is this wallet 0x123... buying on Base?"
      • Answers complex questions about on-chain activities
      • Provides interpreted and user-friendly responses
    • get_eth_data_analysis (EthereumDataAnalystSchema): Advanced LLM-powered analysis of Ethereum chain data

      • Example: "What are the most popular NFTs on Eth today?"
      • Similar capabilities to Base data analysis
      • Focused on Ethereum-specific metrics
    • get_pump_fun_price_prediction (PumpFunPricePredictionSchema): Specialized price prediction model

      • Example: "What's the PumpFun prediction for token 0x123...?"
      • Focuses on potential price movements
      • Available for Base chain tokens
    • get_zora_nft_recommendations (ZoraNFTRecommendationSchema): Personalized NFT recommendations

      • Example: "What NFTs would you recommend for wallet 0x123... on Zora?"
      • Based on wallet's Zora activity and preferences
      • Provides similarity scores and recommendations
    • get_security_assessment (SecurityModelSchema): Comprehensive security analysis

      • Example: "Is this contract 0x123... safe to interact with?"
      • Evaluates wallet/contract security risks
      • Available for Base chain addresses
  2. Integration with the example chatbot to demonstrate usage

  3. Simplified error handling and date formatting for better maintainability

  4. Raw score outputs for LLM interpretation instead of hardcoded classifications

Tests

Chatbot: typescript/examples/langchain-cdp-chatbot/chatbot.ts
Network: Base/Ethereum
Setup: Using Pond API for on-chain analytics (ive put the general user API for testing, the number of request is limited)
for Eth and Base data analyst API setup, let me know if you need me to share via secure approaches.

Test Cases:

  1. Base Data Analysis (BaseDataAnalystSchema):
Prompt: What tokens is this wallet 0x32869721ef080442ec128fc1ddb6673006bc5aa9 buying on Base

Output: Successfully retrieved and displayed 10 tokens bought by the wallet through DEX swaps, including BOOMER, BUILD, CLIZA, DAI, EURC, USDC, USDS, USDbC, WETH, and axlUSDC.
  1. Token Risk Assessment (TokenRiskScoreSchema):
Prompt: is that token risky?

Output: Successfully retrieved risk assessment from three models:
- THE_DAY's Model: 90.41% risk score
- MR_HEOS's Model: 95.83% risk score
- NILSSON_LIENE's Model: 78.18% risk score
  1. Wallet Summary (WalletSummarySchema):
Prompt: give me the summary of that wallet in the last month

Output: Successfully retrieved detailed wallet activity summary including:
- Activity level and transaction counts
- DEX trading summary with volume and PNL
- Portfolio diversity metrics
- Gas usage statistics
  1. Sybil Detection (SybilPredictionSchema):
Prompt: is that wallet a sybil?

Output: Successfully retrieved Sybil detection analysis with confidence scores and data completeness metrics.
  1. Token Price Prediction (TokenPricePredictionSchema):
Prompt: what's the current price and trading volume of the first token according to pond base model?

Output: Successfully retrieved BOOMER token's price ($0.0026900864922844245 USD) and trading volume ($110,368,287.41 USD).
  1. Solana Meme Coins (TopSolanaMemeCoinsSchema):
Prompt: what are the top trending meme coins on Solana right now?

Output: Successfully retrieved list of trending meme coins with their price changes, trading volumes, and market metrics.
  1. Ethereum Data Analysis (EthereumDataAnalystSchema):
Prompt: what are the most popular NFTs on Eth today?

Output: Successfully retrieved and analyzed popular NFTs on Ethereum, including trading volumes and market trends.
  1. PumpFun Price Prediction (PumpFunPricePredictionSchema):
Prompt: what's the PumpFun prediction for token 0x123...?

Output: Successfully retrieved price prediction with confidence levels and data completeness metrics.
  1. Zora NFT Recommendations (ZoraNFTRecommendationSchema):
Prompt: what NFTs would you recommend for wallet 0x123... on Zora?

Output: Successfully retrieved personalized NFT recommendations based on wallet's activity and preferences.
  1. Security Assessment (SecurityModelSchema):
Prompt: is this contract 0x123... safe to interact with?

Output: Successfully retrieved security assessment with risk scores and detailed analysis.
  1. Wallet Risk Score (WalletRiskScoreSchema):
Prompt: is this wallet 0x123... safe to interact with?

Output: Successfully retrieved wallet risk assessment with risk scores and data completeness metrics.

Checklist

  • Added documentation to all relevant README.md files
  • Added a changelog entry

Theofilus Kharisma added 2 commits May 29, 2025 08:11
- Add wallet risk assessment functionality

- Add token analysis capabilities

- Add chain-specific data analysis

- Add comprehensive error handling

- Add API key configuration support
@cb-heimdall
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@github-actions github-actions bot added documentation Improvements or additions to documentation action provider New action provider example New example agent typescript labels May 29, 2025
@theo-pond theo-pond marked this pull request as ready for review May 30, 2025 01:34
@theo-pond theo-pond requested a review from murrlincoln as a code owner May 30, 2025 01:34
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You can ignore this .env changes, i just wanna adding Pond API key but it resulting merge conflict then i hit the resolve button

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