# Multi-Agent Crypto Analysis System — Architecture Status Report ## Purpose This document summarizes the **current state of the system**, what has already been built, and what components remain to be implemented. It serves as a **quick re-orientation reference** for future development. --- # 1. System Objective Build a **fully local multi-agent system** capable of generating structured financial reports on crypto projects. Core goals: * Fully local inference * Modular agent design * Deterministic infrastructure layers * Heavy reasoning isolated to a larger model * Parallelizable agent architecture * Extensible data sources --- # 2. Hardware Layout ## Host A — Transformation Layer GPU: RTX 3070 Model: Qwen 3.5 9B Responsibilities: * Aggregation * Data normalization * Structural parsing * JSON output generation These agents perform **lightweight deterministic transformations**. --- ## Host B — Reasoning Layer GPU: RTX 3090 Model: OSS GPT 20B Responsibilities: * High-level reasoning * Cross-source synthesis * Narrative report generation * Strategic interpretation This is the **only reasoning layer**. --- ## Orchestration Node Platform: Proxmox VM CPU: 8 threads Responsibilities: * OpenClaw orchestration * Agent coordination * Workflow execution * Scheduling (future) No heavy inference runs here. --- ## Operators --- ### 1. url-operator (link discovery operator) Purpose: Retrieves a web page and returns a list of links and their respective categories in JSON format. Capabilities: * Fetch a single webpage * Extract hyperlinks * Normalize URLs * Deduplicate links * Link analysis * Normalize URLs * Categorizes the links Link categories: * GitHub * Twitter/X * Documentation * Website * Other Constraints: * No crawling * No following links Status: **Running** ### 2. twitter-operator Purpose: Access a local Twitter scraping service. Capabilities: * Retrieve tweets * Retrieve account data * Return raw JSON Constraints: * No tweet interpretation * No sentiment detection * No ranking or summarization Status: **Running** --- ### 3. rss-operator Purpose: Access the RSS scraping service. Capabilities: * List feeds * Add feeds * Remove feeds * Retrieve stored entries * Trigger manual fetch Constraints: * No news interpretation * No ranking * No topic filtering Status: **Running** --- ### 4. github-operator Purpose: Interface with the GitHub scraper service. Capabilities: * Extract repository metrics * Retrieve repository statistics Metrics returned include: * stars * forks * watchers * open issues * language * license * contributors * releases * latest commit date Constraints: * No evaluation of development activity * No repository ranking * No popularity inference Status: **Running** --- ### 5. web-operator Purpose: Analyzes the links and decides if they are relevant to the project. Capabilities: * Link analysis * Normalize URLs * Deduplicate links * Select links that are relevant to the project * Of those of relevancy, crawls them and returns a summary of the content Outputs: * JSON structure containing relevant links + content Status: **Not built** --- ## Orchestrator ### Data orchestrator Responsibilities: * Receives a categorized list of URLs * Spawns the operators and prompts them the relevant information * Awaits for their responses. * Aggregate the reponses of all the operators and passes them to the analyst. Constraints: * No evaluation of content * No summarization Outputs: * JSON structure of the responses of the operators Status: **Not built** # 6. Analysis layer ## crypto_analyst This is the **core reasoning agent**. Responsibilities: * consume the data orchestrator output * correlate signals across sources * evaluate engagement-weighted signals * produce structured reports Outputs: * narrative analysis * structured project reports * signal interpretation Capabilities: * interpret meaning * compare sources * draw conclusions * synthesize multi-source evidence Model used: OSS GPT 20B. Status: **Not built** --- # 7. Current Data Flow Expected pipeline: ``` user request ---------------> link_discovery_operator (url operator) | | V rss_operator <------> data_orchestrator <------> web_operator | | | twitter_operator <----------| | |----------> github_operator | V crypto_analyst | | V final report ``` Operators collect raw data. The analyst interprets it. --- # 8. Determinism Rules Operators and orchestration layers must satisfy: * identical output for identical input * no hidden loops * no narrative text * no random ordering * no autonomous actions This enables: * reproducibility * debugging * caching * parallel execution --- # 9. Current Implementation Status Infrastructure: ``` twitter_operator ✓ running rss_operator ✓ running github_operator ✓ running link_discovery_operator ✓ running web_operator ☐ not built ``` Orchestrators: ``` data_orchestrator ☐ not built ``` Analysis layer: ``` crypto_analyst ☐ not built ``` --- # 10. Immediate Next Steps Priority order: 1. Implement operators * web-operator 2. Implement orchestrators * data-orchestrator 3. Define analyst input strategy 4. Implement crypto-analyst 5. Run full pipeline tests --- # 12. Long-Term Extensions Possible future additions: * Discord operator * Governance forum operator * On-chain data operator * Sentiment analysis modules * Market data feeds The architecture is designed to **add sources without modifying the analyst core**. --- # Summary The **infrastructure layer is complete**, all four operators already running. The next development phase focuses on the **orchestrator layer** followed by the **analysis agent**. Once these components are implemented, the system will be capable of producing **fully local multi-source crypto project reports**.