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Roadmap

This document outlines the planned features and enhancements for the Statistics Agent Team project.

Orchestrator Comparison (ADK vs Eino)

The project supports two orchestration approaches for comparison:

Orchestrator Protocol Routing Style Status
ADK A2A (:900x) LLM-driven (Hybrid) ✅ Implemented
Eino HTTP (:800x) Code-driven (Graph) ✅ Implemented

Planned Comparison Metrics

  • 📊 Response time - ADK vs Eino orchestrator latency
  • 📊 Cost per query - LLM calls for orchestration decisions
  • 📊 Verification rate - Does routing strategy affect accuracy?
  • 📊 Predictability - Variance in execution paths and timing
  • 📊 Error recovery - How each handles failures

Why Both?

  • ADK (Hybrid): Code-defined agent structure, LLM-driven routing/delegation
  • Eino (Code-driven): Deterministic graph, predictable execution, lower cost

Current recommendation: Eino for production (faster, cheaper, reproducible)

Refined A2A Strategy: External Agent Services

Key insight: A2A is most valuable for external interoperability, not internal communication.

Agent Reusability Analysis

Agent Capability External Value
Verification Validate excerpt exists in URL ✅ High - Universal problem
Research Search web for topic ✅ Medium - Generic capability
Synthesis Extract statistics from pages ⚠️ Low - Specific to statistics
Orchestrator Coordinate pipeline ❌ None - Internal only 
┌─────────────────────────────────────────────────────────────┐
│  stats-agent-team (internal)                                │
│                                                             │
│  ┌─────────────────┐                                        │
│  │ Eino Orchestrator│──HTTP──→ Research, Synthesis          │
│  └────────┬────────┘          (internal, simple)            │
│           │                                                 │
│           │ HTTP or A2A                                     │
│           ▼                                                 │
│  ┌─────────────────┐                                        │
│  │ Verification    │←──A2A───── External A2A Clients        │
│  │ Agent           │           (other agent systems)        │
│  └─────────────────┘                                        │
└─────────────────────────────────────────────────────────────┘

Verification-as-a-Service

The Verification Agent solves a universal problem: LLMs hallucinate URLs and citations.

Any agent system that generates sourced content needs verification: - Research assistants - Content generators - Fact-checking tools - RAG systems

Proposed A2A Agent Card:

name: "Verification Agent"
description: "Verify that excerpts and statistics exist in source URLs"
skills:
  - name: "verify_excerpt"
    description: "Check if text excerpt exists in URL"
    input: { url: string, excerpt: string }
    output: { verified: boolean, reason: string }
  - name: "verify_statistic"
    description: "Verify numerical statistic with context"
    input: { url: string, value: number, excerpt: string }
    output: { verified: boolean, value_match: boolean, excerpt_match: boolean }

Protocol Strategy

Component Protocol Rationale
Eino → Internal agents HTTP Simple, no overhead
Verification Agent HTTP + A2A A2A for external clients
Research Agent HTTP + A2A Optional external exposure

Don't add A2A client to Eino unless there's a concrete need. HTTP is simpler for internal communication.

Q1 2026

  • ✨ Perplexity API integration - Built-in search without separate provider
  • ✨ Range statistics support - Add value_max field for ranges like "79-96%"
  • ✨ Response streaming - Faster perceived performance with streaming results
  • 📊 Orchestrator benchmarks - Publish ADK vs Eino comparison results
  • 🌐 Verification-as-a-Service - Document and promote Verification Agent as external A2A service

Q2 2026

  • ✨ Multi-language support - Spanish, French, German, Chinese sources
  • ✨ Caching layer - Reduce redundant searches and API costs
  • ✨ GraphQL API - Alternative query interface
  • 🌐 Research Agent external - Expose Research Agent via A2A if demand exists

Q3 2026

  • ✨ Browser extension - Real-time fact-checking while browsing
  • ✨ Notion/Confluence integrations - Embed verified statistics in docs
  • ✨ Advanced citation formats - APA, MLA, Chicago styles

Future Considerations

  • 🔮 Academic database integration (PubMed, arXiv, JSTOR)
  • 🔮 Paywall-aware fetching with institutional credentials
  • 🔮 Historical statistics tracking and trend analysis
  • 🔮 Confidence scoring based on source reputation

Contributing

This roadmap is community-driven. Submit feature requests on GitHub Issues!

To propose a new feature: 1. Check existing issues for duplicates 2. Open a new issue with the enhancement label 3. Describe the use case and proposed solution 4. Community feedback helps prioritize features