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Code Communities

  • 74 installs
  • 325 repo stars
  • Updated August 2, 2026
  • athola/claude-night-market

Map real module clusters and coupling boundaries before a refactor or service split.

About

Code Community Detection is an agent skill that turns your repository into actionable architecture insight by finding natural code clusters and coupling boundaries. Solo builders use it when a monolith feels tangled, before extracting a package, or when planning which folders should not import each other. With the gauntlet plugin, the skill runs community detection on the built code graph; without gauntlet it still delivers value by grouping files by directory and ranking cross-directory imports. Outputs orient refactoring: which areas move together, where boundaries are violated, and what to decouple first. It pairs well with graph-aware skills in the same night-market family and keeps analysis local via shell commands rather than shipping code to a third party.

  • Runs gauntlet graph_query communities action when graph.db exists
  • Falls back to directory grouping plus import frequency without gauntlet
  • Emits Mermaid-friendly module relationship views from directory-level edges
  • Targets Python imports via ripgrep or grep with node_modules excluded
  • Prerequisite gate: /gauntlet-graph build when plugin is installed but graph is missing

Code Communities by the numbers

  • 74 all-time installs (skills.sh)
  • Ranked #508 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/athola/claude-night-market --skill code-communities

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Listed on Skillselion
Installs74
repo stars325
Security audit2 / 3 scanners passed
Last updatedAugust 2, 2026
Repositoryathola/claude-night-market

What it does

Map real module clusters and coupling boundaries before a refactor or service split.

Files

SKILL.mdMarkdownGitHub ↗

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

1. Run community detection (requires gauntlet):

   python3 "$GRAPH_QUERY" --action communities

Fallback (no gauntlet): Analyze directory structure and cross-directory imports:

   # 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:

   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 TypeWeight
CALLS1.0
INHERITS0.8
IMPLEMENTS0.7
IMPORTS_FROM0.5
TESTED_BY0.4
CONTAINS0.3

Exit Criteria

  • [ ] Community table rendered with columns Community, Nodes, Cohesion,

and Description for each detected cluster

  • [ ] Coupling warning surfaced for any pair of communities with more

than 10 cross-boundary edges, labelled with severity

  • [ ] Mermaid flowchart TB generated with one subgraph per community

showing cohesion score in the subgraph label

  • [ ] Improvement suggestions provided for any community with cohesion

< 0.5 or coupling > 20 cross-community edges

  • [ ] If gauntlet is not installed, directory-structure fallback runs and

absence of graph data is stated to the user

Related skills

FAQ

Is Code Communities safe to install?

skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

Code Review & Qualitybackendtesting

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