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uukuguy

code-metrics

by uukuguy

A production-ready multi-agent orchestration framework built on Claude Agent SDK. Design, compose, and deploy complex AI workflows with pre-built architecture patterns.

0🍴 0📅 Dec 27, 2025

SKILL.md


name: code-metrics description: Code metrics calculation methodology for static analysis

Code Metrics Calculation

Objective

Calculate comprehensive code metrics for quality assessment.

Metrics Definitions

Complexity Metrics

  1. Cyclomatic Complexity

    • Count: decisions + 1
    • Decisions: if, else, for, while, case, catch, &&, ||, ?:
    • Thresholds: 1-10 (good), 11-20 (moderate), 21+ (high risk)
  2. Cognitive Complexity

    • Base: control flow structures
    • Nesting penalty: +1 per nesting level
    • Thresholds: 1-15 (good), 16-30 (moderate), 31+ (refactor)
  3. Nesting Depth

    • Maximum depth of nested structures
    • Thresholds: 1-3 (good), 4-5 (moderate), 6+ (refactor)

Size Metrics

  1. Lines of Code (LOC)

    • Physical lines (including blanks)
    • Logical lines (statements)
    • Comment lines
  2. Function Length

    • Lines per function/method
    • Thresholds: 1-30 (good), 31-50 (moderate), 51+ (long)
  3. File Length

    • Total lines per file
    • Thresholds: 1-300 (good), 301-500 (moderate), 501+ (large)

Coupling Metrics

  1. Afferent Coupling (Ca)

    • Number of modules depending on this module
    • High Ca = widely used, risky to change
  2. Efferent Coupling (Ce)

    • Number of modules this module depends on
    • High Ce = high dependency, harder to maintain
  3. Instability (I)

    • Formula: Ce / (Ca + Ce)
    • Range: 0 (stable) to 1 (unstable)

Duplication Metrics

  1. Duplicate Lines

    • Exact match blocks > 6 lines
    • Percentage of codebase
  2. Similar Blocks

    • Token-based similarity > 85%
    • Parameterized duplicates

Calculation Process

  1. Parse source files into AST
  2. Visit all nodes and calculate metrics
  3. Aggregate at function, class, file, module levels
  4. Compare against thresholds
  5. Generate scores (0-100)

Scoring Formula

Quality Score = 100 - (
  complexity_penalty * 0.3 +
  size_penalty * 0.2 +
  coupling_penalty * 0.2 +
  duplication_penalty * 0.3
)

Where penalties are percentage of violations.

Score

Total Score

60/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

0/10
説明文

100文字以上の説明がある

+10
人気

GitHub Stars 100以上

0/15
最近の活動

3ヶ月以内に更新がある

0/10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

0/5

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