Investigation: What is the actual end-to-end status of the Vitto sub-agent ...

Documentation for Sessions

📝 Investigation: What is the actual end-to-end status of the Vitto sub-agent ...

Date: 2026-03-12
Time: 16:39:09 UTC
Session: gspace1-208.5
Agent: angular
Confidence: 95%
Status: ✅ Documented


📋 Decision Context

Question:

What is the actual end-to-end status of the Vitto sub-agent pipeline (creation → training → execution → feedback)?

Task: S208: Agent pipeline e2e audit


🎯 Decision Made

Chosen:

Agent pipeline is 60% built. Working: definitions (4 seeded agents), context injection (patterns + rules into prompts), Command Center WebSocket (30+ events), decision capture (12K+ decisions). STUB: training pipeline (mock OpenAI calls in training-pipeline.service.ts lines 122-150), Platform Intelligence UI (hardcoded 0% success, not fetched from DB). MISSING: sub-agent self-execution (definitions are templates, tasks delegate via handoff to external agents).

Options Considered:

  1. Continue building on current partial pipeline
  2. Replace entire pipeline with new architecture
  3. Focus on completing the 40% gaps (training + self-execution)

💭 Reasoning

Deep audit traced 5 paths: (1) AgentSeedService creates 4 system agents on startup — WORKING. (2) Training pipeline accepts POST, creates job records, but runs fake OpenAI flow with TODO comment — STUB. (3) SubAgentService.findBestAgent() matches definitions by keywords/tags/performance, spawnFromDefinition() builds system prompt with learned patterns — WORKING for context injection. (4) DelegationManagerService.delegate() creates handoff to external agents — WORKING but agents don't self-execute. (5) CommandCenterGateway broadcasts 30+ event types via Socket.IO — WORKING, OFFLINE is config issue (API_BASE_URL mismatch or backend not running). Root cause of '0% Success': training-center.component.ts hardcodes status:'training' and successRate:0 instead of fetching from DB.


📁 Files Involved


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