DIAGNOSTICS_REPORT_20260410.md · 11.0 KB

mindX Diagnostics Report — 2026-04-10

48-Hour Autonomous Observation Period (April 8–10, 2026)

mindX was left running autonomously for 48 hours to observe whether it would self-repair, write scheduled chapters, and propagate restart signals. This report documents the findings.


Executive Summary

Result: mindX was dormant. Zero commits, zero file changes, zero new log entries since April 3. No autonomous chapters were written. No self-improvement cycles completed. No restart signals were propagated.


1. Git Activity

  • Last commit: 9d652772 — April 3, 2026 15:37 — "Self-aware resource limiter, font size controls, brighter doc colors"
  • Commits since April 8: 0
  • File modifications since April 8: 0
  • Author: codephreak (human) — no autonomous commits detected
  • 2. AuthorAgent Chapter Writing

    AuthorAgent is scheduled to write one chapter per day on a 28-day lunar cycle via run_periodic(interval_seconds=86400) in main_service.py:1381-1429.

    Finding: No new chapters or publications were created since April 3.

    Root cause: The _periodic_author() asyncio task only runs while main_service.py is active. If the backend process was not running or the task crashed silently, no chapters are produced. There is no watchdog or external scheduler (cron, systemd timer) to ensure chapter writing continues independently.

    Files checked:

  • docs/publications/ — no new files since April 3
  • docs/publications/daily/ — no new files since April 3
  • docs/BOOK_OF_MINDX.md — last modified April 3
  • 3. Restart Signal Propagation Failure

    Signal Generation (works)

    self_improve_agent.py:360:

    cycle_res.update({
        "promoted_to_main": True,
        "implementation_status": "SUCCESS_PROMOTED",
        "code_updated_requires_restart": True
    })
    

    When self-improvement code is promoted to main, the flag code_updated_requires_restart: True is set and a log warning "RESTART REQUIRED" is emitted.

    Signal Lost (broken)

    The signal never reaches the system because:

  • Data structure mismatch: ImprovementResult dataclass (mindXagent.py:106-114) has no restart field:
  •    @dataclass
       class ImprovementResult:
           goal: str
           success: bool
           agents_used: list
           improvements_made: list
           metrics: dict
           feedback: str
           next_steps: list
       

  • mindXagent never checks for it: _autonomous_improvement_loop() at line 2450 only checks for file_changes, never reads restart flags.
  • Autonomous mode ignores exit signals: Lines 2512-2515 explicitly skip exit conditions when autonomous_mode=True.
  • No restart propagation path: Neither CoordinatorAgent nor MastermindAgent has restart signal handling. StartupAgent has no restart receiver.
  • Signal Flow Diagram

    self_improve_agent.py
      └─ sets code_updated_requires_restart: True ✓
      └─ logs "RESTART REQUIRED" ✓
      └─ returns cycle_res dict ✓
          │
          ▼ (SIGNAL LOST HERE)
    mindXagent.orchestrate_self_improvement()
      └─ calls through BDI/Blueprint/StrategicEvolution
      └─ returns ImprovementResult (no restart field) ✗
          │
          ▼
    mindXagent._autonomous_improvement_loop()
      └─ checks result.success ✓
      └─ checks file_changes ✓
      └─ NEVER checks restart requirement ✗
      └─ logs to memory, continues loop
    

    4. Self-Repair Capability

    Finding: mindX has no active self-repair mechanism that monitors its own health and takes corrective action.

  • The circuit breaker in the autonomous improvement loop opens after 4 consecutive no-progress cycles, then auto-resets after 5 minutes — but it only pauses, it doesn't escalate.
  • The error recovery coordinator (monitoring/error_recovery_coordinator.py:299-320) has a restart_service strategy but it only simulates a component restart (2-second sleep).
  • No agent monitors whether AuthorAgent is producing chapters.
  • No agent monitors whether the improvement loop is making progress.
  • No external watchdog (systemd watchdog, cron health check) is configured.
  • 5. Runtime Logs

  • Last log entry: data/logs/mindx_runtime.log — last modified April 2, 21:46
  • No entries since April 8: The log file was not touched during the observation period.
  • Terminal startup log: data/logs/terminal_startup.log — also stale
  • 6. Memory System State

  • data/memory/stm/ — no new files since April 3
  • data/memory/ltm/ — no new files since April 3
  • data/memory/workspaces/ — no new files since April 3
  • 7. Known Bugs (Pre-existing)

    These bugs existed before the observation period and may have contributed to dormancy:

  • BDIAgent.add_goal AttributeError — BDI API mismatch prevents goal-driven cycles
  • blueprint_agent crash on None LLM response — TypeError on json.loads(None) when inference is unreachable
  • MemoryAgent.get_memories_by_agent missing — RAGE routes fallback fails
  • StrategicEvolutionAgent.__init__() unexpected kwargmastermind_agent parameter rejected
  • mindXagent ollama_chat_manager — uses 10.0.0.155:18080 directly with no automatic fallback to localhost

  • Recommendations

    Immediate (enable autonomous operation)

  • Wire restart signal propagation: Add restart_required: bool = False field to ImprovementResult. Check it in _autonomous_improvement_loop() and trigger graceful restart via os.execv() or systemd restart.
  • Add AuthorAgent health monitoring: A periodic check (every 6 hours) that verifies the last chapter timestamp and triggers a recovery if stale.
  • External watchdog: Configure systemd WatchdogSec= for the mindx.service, or add a cron job that checks /health and restarts the service if unresponsive.
  • Medium-term (self-repair)

  • Health auditor agent: A lightweight agent that periodically checks: is the improvement loop running? Is AuthorAgent writing? Are inference sources available? Are there stuck cycles? Escalates to restart if thresholds are exceeded.
  • --replicate from GitHub: Extend mindX.sh --replicate to clone from GitHub, verify integrity against a known commit hash, bootstrap from the cloned state, and persist current state as a rollback point for catastrophic recovery.
  • Long-term (machine learning augmentation)

  • Learning from failure patterns: Log failure types and recovery actions to pgvectorscale. Train a lightweight classifier to predict which recovery action will succeed for a given failure signature.
  • Autonomous improvement scheduling: Instead of relying on asyncio tasks that die with the process, use a durable task queue (Redis, PostgreSQL-backed) that survives restarts.

  • 8. Agent & Tool Inventory (66 agents, 45 tools)

    Key agents relevant to self-sustaining operation:

    AgentFileRole in Self-Loop MindXAgentagents/core/mindXagent.pyCentral orchestration, autonomous improvement loop StartupAgentagents/orchestration/startup_agent.pySystem initialization, DeltaVerse fileroom BackupAgentagents/backup_agent.pyGit + immutable blockchain backup before shutdown/rebuild ReplicationAgentagents/orchestration/replication_agent.pyMulti-system replication VLLMAgentagents/vllm_agent.pyvLLM CPU build, model serving, inference optimization ResourceGovernoragents/resource_governor.pyResource-aware policies: greedy/balanced/generous/minimal InferenceOptimizeragents/core/Model selection based on compute availability SelfImprovementAgentagents/learning/self_improve_agent.pyCode self-modification and promotion StrategicEvolutionAgentagents/learning/strategic_evolution_agent.pyStrategic improvement planning AuthorAgentagents/author_agent.pySelf-chronicling on 28-day lunar cycle ErrorRecoveryCoordinatoragents/monitoring/error_recovery_coordinator.pySystem-wide error recovery HealthAuditorTooltools/core/health_auditor_tool.pyNEW — Vital signs monitoring with recovery callbacks

    Underutilized: BackupAgent, ReplicationAgent, VLLMAgent, and ResourceGovernor all exist but are not wired into the autonomous self-sustaining loop. The HealthAuditorTool (newly created) now monitors vital signs and triggers recovery, but these agents should be integrated as recovery targets.

    9. Compute Resource Optimization

    The VPS at 168.231.126.58 has constrained resources. Key optimization points:

  • ResourceGovernor has 4 modes (greedy/balanced/generous/minimal) with auto-adjustment
  • VLLMAgent handles CPU-only builds (no GPU on this VPS)
  • InferenceOptimizer + HierarchicalModelScorer rank models by performance
  • Current autonomous model is qwen3:1.7b — small enough for constrained compute
  • vLLM should be configured to serve the smallest effective model for autonomous cycles
  • ResourceGovernor should auto-downshift to minimal mode under memory pressure
  • 10. Changes Made (2026-04-10)

    Pipeline Bug Fixes

  • BDIAgent.add_goal: Added async alias for set_goal() — unblocks BDI orchestration
  • BlueprintAgent: Guarded json.loads() against None LLM response — prevents crash when inference is down
  • StrategicEvolutionAgent init: Fixed kwargs mismatch — passes correct agent_id, belief_system, model_registry, memory_agent
  • ImprovementResult.restart_required: Added restart_required: bool = False field
  • Restart Signal Propagation

  • orchestrate_self_improvement: Detects code_updated_requires_restart and promoted_to_main flags from sub-agents
  • _autonomous_improvement_loop: Checks result.restart_required and triggers _graceful_restart()
  • _graceful_restart(): Creates rollback point, logs event, uses systemd restart (production) or os.execv (development)
  • Health Monitoring

  • HealthAuditorTool: New tool monitoring improvement loop, AuthorAgent, inference, and pgvector every 15 minutes
  • Recovery callbacks: Restarts dead improvement loop (max 1x/hour), restarts stale AuthorAgent (max 1x/hour)
  • health_monitor.py: Standalone script for systemd timer integration
  • GitHub Replication

  • --replicate-from-github: New mindX.sh flag for catastrophic recovery from GitHub
  • - Creates rollback point first, clones shallow, verifies critical files, copies source (preserves data/)

    Frontend & SEO

  • Dashboard fonts: Increased across all elements (body 11→13px, values 18→22px, nav 8→11px, etc.)
  • SEO meta tags: Full Open Graph + Twitter cards + JSON-LD on all pages (dashboard, docs, book, journal, automindx, thinking)
  • 503 thinking page: Info panels inviting users deeper, status labels, bigger fonts
  • Navigation expanded: 4-row nav covering all doc categories
  • Docs cross-linking: .md links auto-convert to /doc/ paths, back-link footers on all pages
  • Book cross-links: 12-item related docs grid
  • Autonomous diagnostics panel: Dashboard shows improvement loop, author agent, restart signal status
  • Report generated by diagnostics analysis on 2026-04-10. Filed as DIAGNOSTICS_REPORT_20260410.md in docs/.


    Referenced in this document
    BOOK_OF_MINDX

    All DocumentsDocument IndexThe Book of mindXImprovement JournalAPI Reference