Skill: athola/nm-cartograph-code-communities (version 1.0.2)

--- name: code-communities description: | Detect architectural clusters in the codebase using community detection on the code knowledge graph. Shows module boundaries, cohesion, and coupling warnings version: 1.9.5 metadata: {"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/cartograph", "emoji": "\ud83e\udd9e"}} source: claude-night-market source_plugin: cartograph --- > **Night Market Skill** — ported from [claude-night-market/cartograph](https://github.com/athola/claude-night-market/tree/master/plugins/cartograph). For the full experience with agents, hooks, and commands, install the Claude Code plugin. # Code Community Detection Identify architectural clusters and module boundaries in the codebase. ## Prerequisites This skill requires the **gauntlet** plugin for graph data. Discover it: ```bash GRAPH_QUERY=$(find ~/.claude/plugins -name "graph_query.py" -path "*/gauntlet/*" 2>/dev/null | head -1) ``` **If gauntlet is not installed**: Fall back to directory structure analysis. Group files by directory and use import statements to identify module boundaries. Generate a Mermaid diagram from directory-level relationships. **If installed but no graph.db**: Tell the user to run `/gauntlet-graph build`. ## Steps 1. **Run community detection** (requires gauntlet): ```bash python3 "$GRAPH_QUERY" --action communities ``` **Fallback (no gauntlet)**: Analyze directory structure and cross-directory imports: ```bash # Directory-level grouping find . -name "*.py" -not -path "*/node_modules/*" | \ sed 's|/[^/]*$||' | sort | uniq -c | sort -rn # Cross-directory imports (rg preferred, grep fallback) if command -v rg &>/dev/null; then rg "^from |^import " --type py -l . | \ xargs -I{} rg "^from \w+ import|^import \w+" {} --no-filename else grep -rh "^from \|^import " --include="*.py" . fi | sort | uniq -c | sort -rn | head -20 ``` Group by top-level directories and count cross-directory imports to estimate coupling. 2. **Display clusters**: ``` Community | Nodes | Cohesion | Description auth | 12 | 0.85 | Authentication module db | 8 | 0.92 | Database access layer api/handlers | 15 | 0.71 | API request handlers utils | 6 | 0.45 | Shared utilities ``` 3. **Show coupling warnings**: If communities have >10 cross-boundary edges, highlight them: ``` WARNING: High coupling between 'auth' and 'api/handlers' (23 cross-community edges, severity: high) ``` 4. **Generate Mermaid diagram**: ```mermaid flowchart TB subgraph auth[Auth Module - cohesion 0.85] verify_token check_permissions end subgraph db[DB Layer - cohesion 0.92] execute_query connection_pool end auth -->|"23 edges"| api db -->|"5 edges"| api ``` 5. **Suggest improvements**: - Low cohesion (<0.5): "Consider splitting this module into more focused components" - High coupling (>20 edges): "Consider introducing an interface to reduce direct dependencies" ## Algorithm Uses the Leiden algorithm (when igraph is available) with edge-type-specific weights. Falls back to file-based grouping otherwise. | Edge Type | Weight | |-----------|--------| | CALLS | 1.0 | | INHERITS | 0.8 | | IMPLEMENTS | 0.7 | | IMPORTS_FROM | 0.5 | | TESTED_BY | 0.4 | | CONTAINS | 0.3 |


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