What problem does it solve? Agents starting non-trivial work in a repository often lack grounding: they miss committed docs, repeat past mistakes, and re-derive knowledge that already exists. This Skill grounds the session by reading project context, recalling memory, mapping the codebase, and capturing durable learnings. ## Core Features & Use Cases - Context Stack Loop: Reads CLAUDE.md/AGENTS.md, domain glossaries, ADRs, and context maps before asking the user to repeat information. - Memory & Graph Recall: Runs targeted memory recall and optional graph ingestion to surface prior decisions, gotchas, and structural relationships. - LLM Wiki & Self-Improvement: Queries a project wiki for durable knowledge, stores durable lessons, and inspects skill telemetry for curation signals. - Use Case: Before implementing a large feature in an unfamiliar monorepo, run this Skill to orient from ADRs, recall prior decisions, zoom out on module boundaries, and report a grounded context posture before writing code. ## Quick Start Ask the agent to get context and onboard to this repository before planning the upcoming change.