What problem does it solve? After running trellis init, AI assistants often lack a map of the generated .trellis/ directory and platform integration files, leading to edits in the wrong place (such as node_modules or upstream source) or broken workflow semantics. This Skill gives the AI a complete model of the local Trellis architecture and the correct entry point for every customization request. ## Core Features & Use Cases - Architecture Reference: Explains the three-layer local model (workflow, persistence, platform integration) covering .trellis/workflow.md, config.yaml, tasks, specs, workspace journals, and runtime state. - Platform File Map: Documents where hooks, settings, agents, skills, commands, and prompts live for Claude Code, Cursor, Codex, Copilot, Kiro, Gemini, Windsurf, and other platforms. - Customization Playbooks: Step-by-step guides for changing workflow phases, task lifecycle hooks, context injection, agent behavior, spec structure, and adding project-local skills. - Use Case: A user says "the implement agent never reads my backend spec." The AI reads the context-loading reference, checks the task's implement.jsonl, and fixes the JSONL manifest or the inject-subagent-context hook instead of guessing. ## Quick Start Ask the AI to use the trellis-meta skill to change the no-task workflow rule in .trellis/workflow.md so task creation is skipped for one-reply questions.