pplate
87e0b9359e
Add 4 new custom modes with BigMind guidance: - rules-bigmind/: Introspective Patrick mode (BigMind development) - rules-homelab/: Tinkerer Patrick mode (TrueNAS, Docker, infra) - rules-mcp-builder/: Craftsman Patrick mode (pi_mcps MCP servers) - rules-paisy/: Professional Patrick mode (ADP Germany payroll) Add reusable skills: - skills/assessment-first/: structured assessment.md before implementation - skills/bigmind-session-ritual/: mandatory session start/end ritual - skills/gitea-push/: conventional commit + Gitea push workflow - skills/new-mcp-server/: FastMCP scaffold procedure - skills-bigmind/, skills-homelab/, skills-mcp-builder/, skills-paisy/: mode-specific skill dirs Update existing rules: - rules-architect, rules-ask, rules-code, rules-debug, rules-orchestrator: add BigMind session guidance (search before task, announce focus, hypotheses) Add plans/MODES_AND_SKILLS_PLAN.md: full architecture document
1.8 KiB
1.8 KiB
Architect Mode Behavior — Roo Code
Persona Context — Which Patrick is planning?
Before starting, identify the active context from the conversation:
- Homelab Patrick → plan for TrueNAS Docker services, local hardware constraints, Gitea as source of truth
- ADP/Paisy Patrick → plan with compliance mindset, assessment-first, German ticket language, PR-only workflow
- MCP Builder Patrick → plan for FastMCP conventions, pi_mcps structure, pytest coverage expectations
- BigMind Patrick → plan with DB migration safety, test-first, Flask/SQLite constraints in mind
Adapt planning depth and output format to match the active persona.
Planning Process
- Search Context:
memory_search_facts("similar project")+memory_list_sessions(topics_filter="architecture") - Form Hypothesis:
memory_add_hypothesis(session_id, "This architecture will scale to X users with confidence 0.7") - Create Assessment: Write markdown assessment.md with requirements, risks, alternatives
- Announce Focus:
memory_announce_focus(session_id, "Planning Y system", files=["plan.md"], ide_hint="VS Code")
Best Practices
- Break Down: Large tasks → subtasks with MCP servers (Docker, Gitea, Ollama)
- Homelab Focus: Leverage TrueNAS Docker for services, 1.2TB SSD for VMs/DBs
- Token Efficiency: Reference past architectures from memory, log savings
- Assessment First: For any Paisy/ADP task, always produce an assessment markdown before proposing code
After Planning
- Store Decision:
memory_store_fact("architecture-decision", "Chose Z architecture for reasons A B C") - Flag Plan:
memory_flag_important(session_id, "Architecture plan for Y", role="assistant") - Resolve Hypothesis: Update based on plan validation