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[CLAUDE] Docs: S124 adap-wave AI_INFRA + owner worker-tier-pin (14 agent opus+effort:max) + user-memory relocate R6 + H24 dogfood
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-15 23:17:45 +07:00

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name, description, metadata
name description metadata
feedback-7agent-split-upgrade SOLUTION_ERP S39 multi-agent 4→7 upgrade — BVAAU pattern adapted (backend/frontend split + test-specialist) + budget +50% + 5 RAG MCP + anti-truncation rules
node_type type tags phase originSessionId
memory project
decision
multi-agent
governance
infra
phase-10-to-11 2a3ce6e1-edc5-464d-a436-38c8ed876dde

Multi-agent 4→7 Upgrade (Session 39 — 2026-05-29)

Trigger: Anh main "tham khảo cấu hình 7 sub-agent BVAAU → tăng tốc + chất lượng → budget +50% + thêm 3 agent". Chốt qua AskUserQuestion 2 câu.

Decision chốt (AskUserQuestion S39)

  1. Implementer split = Backend / Frontend (KHÔNG domain/infra như BVAAU)
    • Lý do: SOLUTION_ERP có 2 React FE app riêng (admin + user) + FE mirror SHA256 là pain point chính (Pattern 16-bis 9×). Tách FE specialist → giảm gotcha #53 truncation khi BE+FE cùng spawn (đã gặp 5×). Mỗi spawn nhẹ hơn.
  2. test-specialist dedicated = full test layer (2 implementer KHÔNG viết test)

7-agent final (color-coded)

Agent Color Scope
investigator-codebase cyan INTERNAL SQL/EF/grep/reference mirror
investigator-api blue EXTERNAL docs/CVE/lib eval/cross-project
implementer-backend yellow .NET Domain+App+Infra+Api
implementer-frontend orange FE 2 app cookie-cutter SHA256 mirror
test-specialist purple tests/ dedicated xUnit
reviewer red adversarial pre-commit + live curl
cicd-monitor green post-deploy Gitea + bundle + smoke

Adapt KHÁC BVAAU (anh cho phép "không bắt buộc giống")

  • backend/frontend thay domain/infra (2-FE-app fit)
  • Giữ 6 skill proven (BVAAU Phase 0 = 0 skill, codebase rỗng). Investigator extract verdict: BVAAU config = aspirational template chưa battle-test (VIPIX guide reference không tồn tại) → SOLUTION_ERP port trục split CÓ CHỌN LỌC, giữ lợi thế 38-session battle-test.

Port TỪ BVAAU

  • Trục split research(2) + implement(2) + quality(3)
  • +3 RAG MCP all 7 agent: search_code (BM25, prefer over Read full file — tiết kiệm token) + store_memory + list_projects (2→5 tools). MCP server verified support.

Token budget +50%

  • Prior: ~700K opt / ~1.35M heavy → Now: ~1.05M opt / ~2M heavy ceiling
  • Justify: parallel BE+FE+test giảm wall-clock + split nhẹ giảm truncate + test-specialist clear coverage gap backlog
  • Max 20× plan absorbs ~5× comfortable

Anti-truncation rules (gotcha #53/#54/#55 codified README)

  • Brief WRITE agent ≤ 8K (heavy spec ~10K → truncate risk #55)
  • Curate MEMORY pre-spawn nếu > 25KB (#53)
  • Agent entry ≤ 1.5K chars (frontmatter rule mỗi agent)
  • 529 Overload (#54) → em main solo fallback, KHÔNG retry loop
  • Pre-supply reference snippet trong brief nếu cần > 4 reference file

How to apply (cross-session)

  • CLI restart BẮT BUỘC sau đổi agent definition (per S27 model:inherit lesson) → registry hot-reload. Verify smoke spawn 3 agent mới.
  • Memory folder rename: investigator→investigator-codebase + implementer→implementer-backend (giữ history). Khi SendMessage flush agent CŨ trước restart → ghi nhầm folder rename → conflict. Wrap session đổi config: em main proxy synthesize, KHÔNG SendMessage flush.
  • Decision tree split-routing: Read internal→codebase, Read external→api, WRITE .NET→backend, WRITE FE→frontend, test→test-specialist.

Reusable pattern cross-project: Khi scale multi-agent, split theo TRỤC WORKLOAD THỰC TẾ của project (SOLUTION_ERP = 2 FE app → backend/frontend) thay vì copy nguyên pattern reference project. Reference project có thể aspirational chưa battle-test → verify trước khi port.

Related: feedback-implementer-truncation-mitigation feedback-multi-agent-setup