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ln-641-pattern-fitness-auditor

ln-641-pattern-fitness-auditor

github.com/levnikolaevichTesting & quality58471 installsUpdated 2d ago
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About ln-641-pattern-fitness-auditor

A codebase-audit skill that analyzes one specified architectural pattern per run. It checks implementations against best practices and project needs, with separate scores for compliance, completeness, quality, and implementation.

Key features

  1. 01Find implementations of a specified pattern
  2. 02Check patterns against best practices
  3. 03Calculate four diagnostic scores
  4. 04Record gaps, issues, and effort
  5. 05Produce structured analysis reports

Use cases

  1. 01Assess an implementation of a job-processing pattern
  2. 02Check a pattern against project requirements
  3. 03Identify missing pattern components and plan changes

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-641-pattern-fitness-auditor

After installing, type/ln-641-pattern-fitness-auditorin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
audit_scoring.md
audit_summary_contract.md
audit_worker_core_contract.md
mcp_integration_patterns.md
mcp_tool_preferences.md
pattern_library.md
scoring_rules.md
two_layer_detection.md
references/templates/
audit_worker_report_template.md

Details

From the project README

Paths: File paths (references/, ../ln-*) are relative to this skill directory.

Pattern Fitness Auditor

Type: L3 Worker

L3 Worker that analyzes a single architectural pattern against best practices and project needs.

Purpose & Scope

  • Analyze ONE pattern per invocation (receives pattern name, locations, best practices)
  • Find all implementations in codebase (Glob/Grep)
  • Validate implementation exists and works
  • Calculate 4 scores: compliance, completeness, quality, implementation
  • Identify gaps and issues with severity and effort estimates
  • Return structured analysis result
  • Emit KEEP_PATTERN, SIMPLIFY_PATTERN, COMPLETE_PATTERN, or REPLACE_PATTERN

Out of Scope:

  • Cyclomatic complexity thresholds (>10, >20)
  • Method/class length thresholds (>50, >100, >500 lines)
  • Quality Score focuses on pattern-specific quality (SOLID within pattern, pattern-level smells), not generic code metrics

Inputs

- pattern: string          # Pattern name (e.g., "Job Processing")
- locations: string[]      # Known file paths/directories
- bestPractices: object    # Best practices from MCP Ref/Context7/WebSearch
- output_dir: string       # e.g., ".hex-skills/runtime-artifacts/runs/{run_id}/audit-report"

Note: If pattern evidence is provided by a managed run, use that evidence instead of rediscovering the same pattern from scratch.

Workflow

MANDATORY READ: Load references/mcp_tool_preferences.md.

Detection policy: use two-layer detection (candidate scan, then context verification); load references/two_layer_detection.md only when the verification method is ambiguous. Tool policy: You may run as an isolated subagent where host AGENTS.md is not in scope, so default to hex-line MCP first for file reads, search, and edits. Load references/mcp_integration_patterns.md only when MCP behavior is unclear.

Use hex-graph first when implementation discovery materially improves confidence. Use hex-line first for local code reads when available. If MCP is unavailable, unsupported, or not indexed, continue with built-in Read/Grep/Glob/Bash and state the fallback in the report.

Phase 1: Find Implementations

MANDATORY READ: Load references/pattern_library.md -- use "Pattern Detection (Grep)" table for detection keywords per pattern.

IF pattern.source == "adaptive":
  # Pattern evidence was already provided by the caller
  files = pattern.evidence.files
  SKIP detection keyword search (already done in Phase 1b)
ELSE:
  # Baseline pattern -- use library detection keywords
  files = Glob(locations)
  additional = Grep("{pattern_keywords}", "**/*.{ts,js,py,rb,cs,java}")
  files = deduplicate(files + additional)
Phase 2: Read and Analyze Code
FOR EACH file IN files (limit: 10 key files):
  Read(file)
  Extract: components, patterns, error handling, logging, tests
Phase 3: Calculate 4 Scores

MANDATORY READ: Load references/scoring_rules.md -- follow Detection column for each criterion.

ScoreSource in scoring_rules.mdMax
Compliance"Compliance Score" section -- industry standard, naming, conventions, anti-patterns100
Completeness"Completeness Score" section -- required components table (per pattern), error handling, tests100
Quality"Quality Score" section -- method length, complexity, code smells, SOLID100
Implementation"Implementation Score" section -- compiles, production usage, integration, monitoring100

Scoring process for each criterion:

  1. Run the Detection Grep/Glob from scoring_rules.md
  2. If matches found -> add points per criterion
  3. If anti-pattern/smell detected -> subtract per deduction table
  4. Document evidence: file path + line for each score justification
Phase 4: Identify Issues and Gaps
FOR EACH bestPractice NOT implemented:
  issues.append({
    severity: "HIGH" | "MEDIUM" | "LOW",
    category: "compliance" | "completeness" | "quality" | "implementation",
    issue: description,
    suggestion: how to fix,
    effort: "S" | "M" | "L"
  })

# Layer 2 context check (MANDATORY):
# Deviation documented in code comment or ADR? -> downgrade to LOW
# Pattern intentionally simplified for project scale? -> skip


gaps = {
  missingComponents: required components not found in code,
  inconsistencies: conflicting or incomplete implementations
}
Phase 5: Calculate Score

MANDATORY READ: Load references/audit_worker_core_contract.md and references/audit_scoring.md.

Diagnostic sub-scores (0-100 each) are calculated separately and reported in AUDIT-META for diagnostic purposes only:

  • compliance, completeness, quality, implementation
Phase 6: Write Report

MANDATORY READ: Load references/templates/audit_worker_report_template.md.

Write JSON summary per references/audit_summary_contract.md. In managed mode the caller passes both runId and summaryArtifactPath; in standalone mode the worker generates its own run-scoped artifact path per shared contract.

# Build pattern name slug: "Job Processing" -> "job-processing"
slug = pattern.name.lower().replace(" ", "-")

# Build markdown report in memory with:
# - AUDIT-META (extended: score [penalty-based] + diagnostic score_compliance/completeness/quality/implementation)
# - Checks table (compliance_check, completeness_check, quality_check, implementation_check)
# - Findings table (issues sorted by severity)
# - DATA-EXTENDED: {pattern, codeReferences, gaps, recommendations}

Write to {output_dir}/ln-641--{slug}.md (atomic single Write call)
Phase 7: Return Summary
Report written: .hex-skills/runtime-artifacts/runs/{run_id}/audit-report/ln-641--job-processing.md
Score: 7.9/10 (C:72 K:85 Q:68 I:90) | Issues: 3 (H:1 M:2 L:0)

Critical Rules

Apply the already-loaded references/audit_worker_core_contract.md.

  • One pattern only: Analyze only the pattern provided in input
  • Read before score: Never score without reading actual code
  • Detection-based scoring: Use Grep/Glob patterns from scoring_rules.md, not assumptions
  • Effort estimates: Always provide S/M/L for each issue
  • Code references: Always include file paths for findings
  • Unique angle: Audit one pattern's architectural fitness only. Do not audit generic code quality, dependency topology, package health, or runtime operations.
  • Action required: Every finding uses KEEP_PATTERN, SIMPLIFY_PATTERN, COMPLETE_PATTERN, or REPLACE_PATTERN.

Definition of Done

Apply the already-loaded references/audit_worker_core_contract.md.

  • All implementations found via Glob/Grep (using pattern_library.md keywords or adaptive evidence)
  • Key files read and analyzed
  • 4 scores calculated using scoring_rules.md Detection patterns
  • Issues identified with severity, category, suggestion, effort
  • Gaps documented (missing components, inconsistencies)
  • Recommendations provided
  • Report written to {output_dir}/ln-641--{slug}.md (atomic single Write call)
  • Summary written per contract

Reference Files

  • Scoring rules: references/scoring_rules.md
  • Pattern library: references/pattern_library.md

Version: 2.0.0 Last Updated: 2026-02-08

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