Dao agent #12
Dao agent #12
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Summary of ChangesHello @SidharthK2, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request integrates a new sample project, the "DAO Proposal Analyzer," into the repository. This system leverages a multi-agent architecture built with ADK-TS to connect with real-world blockchain data. Its primary function is to fetch, analyze, and provide voting recommendations for governance proposals from various Ethereum mainnet DAOs, aiming to empower users with informed decision-making in decentralized autonomous organizations. Highlights
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Code Review
This pull request introduces an impressive new sample project, the DAO Proposal Analyzer. The multi-agent architecture is well-structured, and the use of on-chain data from various DAOs provides a great real-world example. My review focuses on a few key areas to improve correctness, efficiency, and maintainability. I've identified a critical issue with environment variable configuration that would prevent the application from starting, as well as several opportunities to optimize data fetching and improve code clarity and type safety. Addressing these points will make the sample project more robust and easier for other developers to use.
| config(); | ||
| export const envSchema = z.object({ | ||
| ADK_DEBUG: z.coerce.boolean().default(false), | ||
| GOOGLE_API_KEY: z.string(), |
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The environment schema requires GOOGLE_API_KEY, but the .env.example file and the default model (gpt-4o-mini) indicate that OPENAI_API_KEY is what's actually needed. This will cause the application to fail at startup for anyone following the setup instructions. Please correct the schema to expect OPENAI_API_KEY.
| GOOGLE_API_KEY: z.string(), | |
| OPENAI_API_KEY: z.string(), |
| } catch { | ||
| // Silently fail | ||
| } |
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The catch block for fetching proposal description logs is empty and fails silently. If the RPC call fails for any reason (e.g., rate limiting, network issues), the error is completely ignored. This leads to the function returning a generic, unhelpful description like "Proposal #123", which will result in a very poor analysis from the LLM. You should at least log the error to aid in debugging.
} catch (error) {
// Log error but continue, so a partial proposal can be returned.
console.error(
`[governanceService] Failed to fetch description for proposal ${proposalId}:`,
error,
);
}| for (let id = count; id >= startId; id--) { | ||
| try { | ||
| const proposal = await getProposal(daoKey, id); | ||
| proposals.push(proposal); | ||
| } catch (error) { | ||
| console.error(`Failed to fetch proposal ${id}:`, error); | ||
| } | ||
| } |
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The getRecentProposals function fetches proposals sequentially in a for loop. This is inefficient as each await getProposal() call blocks until the previous one is complete. You can significantly improve performance by fetching the proposals in parallel using Promise.allSettled.
const proposalIds = Array.from({ length: count - startId + 1 }, (_, i) => count - i);
const results = await Promise.allSettled(
proposalIds.map((id) => getProposal(daoKey, id)),
);
results.forEach((result, i) => {
if (result.status === "fulfilled") {
proposals.push(result.value);
} else {
console.error(`Failed to fetch proposal ${proposalIds[i]}:`, result.reason);
}
});| { | ||
| "name": "dao-proposal-analyzer", | ||
| "version": "1.0.0", | ||
| "description": "Multi-agent DAO governance system that analyzes proposals, simulates outcomes, and recommends votes for DAO members using ADK-TS", |
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The package description mentions that the system "simulates outcomes". However, based on the current implementation, the agents analyze proposals and provide recommendations, but do not perform any outcome simulation. To avoid confusion, I suggest updating the description to more accurately reflect the project's capabilities.
| "description": "Multi-agent DAO governance system that analyzes proposals, simulates outcomes, and recommends votes for DAO members using ADK-TS", | |
| "description": "Multi-agent DAO governance system that analyzes on-chain proposals and provides voting recommendations for DAO members using ADK-TS", |
| import * as dotenv from "dotenv"; | ||
| import { getRootAgent } from "./agents/agent"; | ||
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| dotenv.config(); |
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The dotenv import and dotenv.config() call are redundant here. The environment variables are already loaded and parsed within src/env.ts when it's first imported by any module. To centralize environment handling and avoid redundant operations, you should remove these lines.
| import * as dotenv from "dotenv"; | |
| import { getRootAgent } from "./agents/agent"; | |
| dotenv.config(); | |
| import { getRootAgent } from "./agents/agent"; | |
| function getClient(): PublicClient { | ||
| return createPublicClient({ | ||
| chain: mainnet, | ||
| transport: http(env.ETHEREUM_RPC_URL || "https://eth.drpc.org"), |
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The fallback URL || "https://eth.drpc.org" is effectively dead code. The env.ts file defines a default value for ETHEREUM_RPC_URL, so env.ETHEREUM_RPC_URL will never be falsy. You can simplify this by removing the fallback.
| transport: http(env.ETHEREUM_RPC_URL || "https://eth.drpc.org"), | |
| transport: http(env.ETHEREUM_RPC_URL), |
| export interface DAOConfig { | ||
| name: string; | ||
| governor: string; | ||
| token: string; | ||
| } |
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The DAOConfig interface is missing the chain property. The getSupportedDAOs function in governanceService.ts returns an array of objects that include a chain property, but its return type is DAOConfig[]. This creates a type inconsistency. Please add the chain property to the DAOConfig interface.
| export interface DAOConfig { | |
| name: string; | |
| governor: string; | |
| token: string; | |
| } | |
| export interface DAOConfig { | |
| name: string; | |
| governor: string; | |
| token: string; | |
| chain: string; | |
| } |
Add DAO Proposal Analyzer: Multi-Agent Governance Analysis System
Description
Introducing the DAO Proposal Analyzer - a comprehensive multi-agent system that analyzes on-chain DAO governance proposals and provides voting recommendations. This project showcases advanced agent orchestration using the ADK-TS framework with real blockchain data integration.
Type of Change
Key Features
Multi-Agent Architecture:
Real On-Chain Integration:
Comprehensive Analysis Pipeline:
Technical Implementation
Core Components:
governanceService.ts- viem-based on-chain data fetchingfetchProposalTool.ts- Agent tools for proposal accessSupported DAOs (Ethereum Mainnet):
0xc0Da02939E1441F497fd74F78cE7Decb17B665290x408ED6354d4973f66138C91495F2f2FCbd8724C30x323A76393544d5ecca80cd6ef2A560C6a395b7E30x9AEE0B04504CeF83A65AC3f0e838D0593BCb2BC7Demo Experience
The interactive demo showcases:
Usage Examples
Architecture Highlights
State Management: Uses ADK-TS shared state for agent coordination
Error Handling: Graceful fallbacks for RPC failures and missing data
Modular Design: Each agent has clear responsibilities and interfaces
Extensible: Easy to add new DAOs and analysis dimensions
Project Structure
Related Issue
closes IQAIcom/adk-ts#453
Checklist