memtrace-codebase-exploration

## Overview Full codebase exploration workflow — from indexing through architectural understanding. Chains indexing, graph algorithms, community detection, and temporal analysis into a structured onboarding experience. Use this when someone is new to a codebase and needs to build a mental model. ## Steps ### 1. Index the codebase Call `list_indexed_repositories` first. If the repo is already indexed, skip to step 2. Otherwise, call `index_directory` with the project path, then poll `check_job_status` until completion. **Success criteria:** Repo appears in `list_indexed_repositories` with non-zero node/edge counts. ### 2. Get the lay of the land Call `get_repository_stats` to understand scale: - How many functions, classes, methods, interfaces? - How many relationships (calls, imports, extends)? - How many communities and processes were detected? Report these numbers to the user — they set expectations for the codebase's size and complexity. ### 3. Map the architecture (communities) Call `list_communities` to see how the codebase naturally clusters into logical modules. **Decision:** If >10 communities, summarize the top 5–7 by size and let the user ask about specific ones. Each community represents a cohesive module — these are the "areas" of the codebase. ### 4. Find the most important symbols Call `find_central_symbols` — PageRank over CALLS/REFERENCES edges (no `method` param): ```json { "repo_id": "<repo>", "limit": 15 } ``` These are the symbols that the...