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ln-641-pattern-analyzerln 641 模式分析仪

Agent Skill

ln-641-pattern-analyzer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

6,030

周安装

259

GitHub Stars

437

下载量

2,113
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ln-641-pattern-analyzer(ln 641 模式分析仪)
来源仓库:https://github.com/levnikolaevich/claude-code-skills
仓库路径:skills/ln-641-pattern-analyzer
安装命令:
npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-641-pattern-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-641-pattern-analyzer

简介

用于查找、检索和筛选相关信息,适合根据关键词快速定位候选结果。

  • 适用于需要结合来源仓库、安装命令和原始 README 核验具体用法的场景。
  • 使用时需确认权限范围和维护状态,避免触发不必要的联网或文件读写。
  • 安装前建议评估是否会执行命令或访问外部资源,确保符合安全策略。
  • 适用于 Codex、Claude、Cursor、Gemini CLI 等宿主环境中的研究检索任务。

SKILL.md

Paths: File paths (shared/, references/, ../ln-*) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. If shared/ is missing, fetch files via WebFetch from https://raw.githubusercontent.com/levnikolaevich/claude-code-skills/master/skills/{path}.

Pattern Analyzer

Type: L3 Worker

L3 Worker that analyzes a single architectural pattern against best practices and calculates 4 scores.

Purpose & Scope

  • Analyze ONE pattern per invocation (receives pattern name, locations, best practices from coordinator)
  • 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 to coordinator

Out of Scope (owned by ln-624-code-quality-auditor):

  • 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: All patterns arrive pre-verified (passed ln-640 Phase 1d applicability gate with >= 2 structural components confirmed).

Workflow

MANDATORY READ: Load shared/references/two_layer_detection.md for detection methodology. MANDATORY READ: Load shared/references/mcp_tool_preferences.md and shared/references/mcp_integration_patterns.md

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 ../ln-640-pattern-evolution-auditor/references/pattern_library.md -- use "Pattern Detection (Grep)" table for detection keywords per pattern.

IF pattern.source == "adaptive":
  # Pattern discovered by coordinator Phase 1b -- evidence already provided
  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 ../ln-640-pattern-evolution-auditor/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 shared/references/audit_worker_core_contract.md and shared/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 shared/references/audit_worker_core_contract.md and shared/templates/audit_worker_report_template.md.

Write JSON summary per shared/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

MANDATORY READ: Load shared/references/audit_worker_core_contract.md.

  • One pattern only: Analyze only the pattern passed by coordinator
  • 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

Definition of Done

MANDATORY READ: Load shared/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: ../ln-640-pattern-evolution-auditor/references/scoring_rules.md
  • Pattern library: ../ln-640-pattern-evolution-auditor/references/pattern_library.md
  • MANDATORY READ: Load shared/references/research_tool_fallback.md

Version: 2.0.0 Last Updated: 2026-02-08

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.09%
按下载量换算763

Claude

29.94%
按下载量换算633

Cursor

19.04%
按下载量换算402

Gemini CLI

10.06%
按下载量换算213

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

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来源信息

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