Collaborative requirements discovery session optimized for AI coding workflows. Creates task directories, seeds PRDs, runs codebase research, proposes concrete implementation approaches with trade-offs, and converges on MVP scope through structured Q&A. Use when requirements are unclear, multiple implementation paths…
Interactive three-part onboarding for new team members to the Trellis AI-assisted workflow system. Covers core philosophy (AI memory, project-specific knowledge, context drift), system structure and command deep-dives, real-world workflow examples, and guideline customization. Use when a new developer joins the…
Initializes an AI development session by reading workflow guides, developer identity, git status, active tasks, and project guidelines from .trellis/. Classifies incoming tasks and routes to brainstorm, direct edit, or task workflow. Use when beginning a new coding session, resuming work, starting a new task, or…
Runs when a session starts on startup, clear and compact, executing session-start.py via python3 (3 commands). From lxyer/multi-agent-collaboration-system.
Runs before the agent uses a tool for Task and Agent tool calls, executing inject-subagent-context.py via python3 (2 commands). From lxyer/multi-agent-collaboration-system.
Gemini CLI instructions for lxyer/multi-agent-collaboration-system, a project described as: Terminal-native cockpit for AI-first software engineering — protocol-driven sidecar across Claude Code, Codex CLI, OMX, OMCC and beyond.
1 4mo agoA7 tokens
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