Agent skill
code-communities
Detect architectural clusters in the codebase using community detection on the code knowledge graph. Shows module boundaries, cohesion, and coupling warnings.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/code-communities
SKILL.md
Code Community Detection
Identify architectural clusters and module boundaries in the codebase.
Prerequisites
This skill requires the gauntlet plugin for graph data. Discover it:
GRAPH_QUERY=$(find ~/.claude/plugins -name "graph_query.py" -path "*/gauntlet/*" 2>/dev/null | head -1)
If gauntlet is not installed: Fall back to directory structure analysis. Group files by directory and use import statements to identify module boundaries. Generate a Mermaid diagram from directory-level relationships.
If installed but no graph.db: Tell the user to run
/gauntlet-graph build.
Steps
-
Run community detection (requires gauntlet):
bashpython3 "$GRAPH_QUERY" --action communitiesFallback (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 -20Group by top-level directories and count cross-directory imports to estimate coupling.
-
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 -
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) -
Generate Mermaid diagram:
mermaidflowchart 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 -
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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