Task State Object v2

Version: 0.1.0
Status: ACTIVE DRAFT
Last Updated: 2026-03-20

Purpose

This draft extends the existing OmegA task-state model so that teleodynamic concepts can influence routing and gating without becoming prompt-only folklore.

Required Fields

FieldTypeMeaning
task_idstringStable identifier
objectivestringWhat success actually is
constraintsarray[string]Hard boundaries
success_criteriaarray[string]Observable completion conditions
declared_unknownsarray[string]Known knowledge gaps before action
urgencystringlow, normal, high, critical
intent_priority_scorenumberRelative task priority
goal_valence_vectorobjectStructured weighting across truth, speed, safety, continuity, and operator preference
authority_shrink_levelnumberReduction in allowed autonomy due to uncertainty or risk
canon_anchor_weightnumberInfluence of identity and canon anchors
predicted_failure_modesarray[string]Expected failure tags before execution
phase_statestringCurrent phase

Suggested goal_valence_vector

{
  "truth": 1.0,
  "speed": 0.4,
  "safety": 0.9,
  "continuity": 0.8,
  "operator_preference": 0.7
}

Required Behaviors

Authority Shrink

When uncertainty or risk rises:

  • reduce side-effectful autonomy
  • increase trace detail
  • prefer reversible actions
  • prefer explicit evidence citations

Failure Prediction

Before execution, the system should name likely failure tags from the canonical taxonomy.

Canon Weighting

High-identity or high-governance tasks should show increased canon_anchor_weight.

Initial Integration Points

  • Gateway request envelope
  • Brain orchestrator
  • ADCCL verifier input
  • consensus trigger checks

Success Condition

The TSO becomes the main carrier for:

  • teleo-affective logic
  • authority shrinkage
  • symbolic gravity
  • phase tracking

without requiring those ideas to live only in prompts.