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Unity Agent Team v2: Adaptive Multi-Agent Development Framework for Unity DOTS

Unity Agent Team v2 is an adaptive multi-agent AI framework designed for Unity DOTS. It addresses issues in version 1 such as fixed team structures, premature parallel execution, and weak constraint mechanisms through task classification, dynamic team formation, and strict phase gating.

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Published 2026-05-26 11:45Recent activity 2026-05-26 11:53Estimated read 5 min
Unity Agent Team v2: Adaptive Multi-Agent Development Framework for Unity DOTS
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Section 01

Unity Agent Team v2: Core Overview

Unity Agent Team v2 is an adaptive multi-agent AI framework designed for Unity DOTS (Data-Oriented Technology Stack). It addresses key limitations of v1, including fixed team structures, unenforced rules, premature parallel execution, and tmux dependency. Core improvements include task classification, dynamic team formation, stage gating, adaptive pipelines, and a skill pack system to enhance flexibility and control.

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Section 02

Background: Limitations of Unity Agent Team v1

v1 had several critical flaws: fixed 4-agent structure (architect, Unity dev, data tool, tester) leading to resource waste; rules as unenforced Markdown docs; premature parallel execution causing conflict edits; tmux as a hard dependency; and nested sub-agents increasing architectural complexity.

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Section 03

Adaptive Pipeline Architecture

v2's pipeline consists of 5 steps:

  1. Bootstrap: Run orchestrate.py preflight for environment checks and state reset.
  2. Triage: Generate triage.json (complexity, domain, confidence) via CRG and fingerprint analysis.
  3. Plan: Create pipeline.json (phases, parallel strategy, product list) from triage data.
  4. Execute Phases: Gate check → generate agents → write products → verify/retry (max 2 times).
  5. Finalize: Generate report or return exit 4 for validation failure.
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Section 04

Complexity-Driven Pipeline Configuration

v2 adjusts pipeline based on task complexity:

  • Tiny: Unity dev + deterministic bundle
  • Small: Unity dev + verifier
  • Medium: Architect + Unity dev + verifier
  • Large/Critical: Full team + tester Intent modifiers (bug/refactor/explore) override defaults; depth modifiers (quick/normal/deep) adjust complexity level (e.g., quick reduces complexity, deep increases it).
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Section 05

Runtime Enforcement & Skill Pack System

Enforcement: Exit codes ensure rule compliance (0=success,2=gate violation,3=ownership issue,4=validation failure,10=retry limit). Schema validation for products (stored in .claude/schemas/). Skill packs replace nested agents: e.g., burst-safety for Unity devs, ownership-partitioning for parallel writers.

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Section 06

Key Products & Schema Validation

Key products:

  • triage.json (owner: triage)
  • pipeline.json (owner: orchestrate.py plan)
  • root_cause.json (owner: bug-investigation/refactor-agent)
  • approved_plan.json (owner: architect for medium+ tasks)
  • impl_result.json (owner: Unity dev/data tool)
  • verification_result.json (owner: verifier/tester)
  • ownership.lock.json (owner: architect/triage) Each product is validated against its schema before next phase.
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Section 07

Conclusion & Practical Significance

v2 balances flexibility and control in multi-agent systems. For Unity DOTS devs: it provides DOTS-specific skills (ECS/Jobs/Burst) missing in general AI tools. For AI researchers: it offers a reference for task classification, dynamic planning, and stage gating in multi-agent collaboration. It's an important evolution of AI-assisted software development frameworks.