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crypto_project_analyst/financial_analyst_structure.md

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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.