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architecture-audit架构审计

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

总安装

240

周安装

10

GitHub Stars

公开资料未说明

下载量

80
CodexClaudeCursorGemini CLI

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:architecture-audit(架构审计)
来源仓库:https://github.com/harshitsinghbhandari/domain-expansion
仓库路径:skills/architecture-audit
安装命令:
npx skills add https://github.com/harshitsinghbhandari/domain-expansion --skill architecture-audit
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/harshitsinghbhandari/domain-expansion --skill architecture-audit

简介

用于辅助安全审计、权限检查和凭据风险评估。

  • 适合梳理敏感配置、分析鉴权逻辑或生成安全复核清单。
  • 使用时不能将工具输出直接作为最终结论。architecture-audit 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 涉及密钥或生产系统时应先确认最小权限和脱敏方式。
  • 建议结合原始 README 核验适用场景和限制条件。

SKILL.md

Overview

This skill provides two-phase architecture review:

  1. Audit Phase (Sukuna mindset): Cold, systematic dissection of architecture consistency, feasibility, and quality. Identifies fatal flaws with surgical precision.
  2. Improvements Phase (Gojo mindset): Elegant, comprehensive improvement roadmap organized by priority and impact. Offers perceptive solutions.

Both outputs are produced in a single run, enabling teams to understand what's broken and how to fix it systematically.

Activation Rules

Explicit triggers only. This skill activates ONLY when the user explicitly mentions:

  • "audit architecture"
  • "architecture audit"
  • "brutal audit"
  • "Sukuna audit"
  • Similar explicit phrases requesting an architecture review

Required input: User must provide or reference architecture-related Markdown files (e.g., architecture.md, design.md, layers.md, README-architecture.md, or paste content directly). If no files are provided, respond normally and politely request: "Please provide the architecture Markdown files you'd like audited."

File format: All audited content is in Markdown (text descriptions, tables, Mermaid/PlantUML diagrams, decision records, etc.). Do NOT attempt to audit raw source code—this skill is for architecture documentation.

Phase 1: Audit Report (audit.md)

Mindset: Ruthless, Direct, Factual

The audit phase adopts a no-nonsense, penetrating analytical approach:

  • Direct language: Identify exactly what is wrong and why it matters.
  • Systematic: Analyze consistency within files, across files, against architectural principles.
  • Evidence-based: Every claim is backed by specific references to provided content.
  • No sugar-coating: Call out weaknesses plainly, but always with actionable reasoning.

Output Structure

Generate audit.md with this exact structure:

# Architecture Audit Report

## Executive Summary
- **Overall Score**: X/1000
- **Feasibility Verdict**: [Feasible / Partially Feasible / Not Feasible]
- **Primary Strengths**: ...
- **Critical Weaknesses**: ...

## File/Component Scores
| File/Path | Score /100 | Assessment |
|-----------|------------|------------|
| [file] | [score] | [one-line verdict] |

## Detailed Findings

### Consistency Analysis
[Findings on consistency within and across files]

### Feasibility & Scalability Assessment
[Analysis of whether the architecture can support stated goals/scale]

### Architectural Quality
[Assessment of modularity, separation of concerns, adherence to principles]

### Maintainability & Evolution
[How easy is it to understand, modify, extend?]

### Identified Risks
[Technical debt, single points of failure, etc.]

## Final Verdict
[Summary of overall health and whether major rework is needed]

Scoring Methodology

Per-file scores (/100):

  • 90–100: Excellent execution, minimal gaps, production-ready
  • 70–89: Solid foundation with exploitable weaknesses
  • 50–69: Functional but mediocre; multiple issues present
  • <50: Dangerous; actively harmful or incoherent

Overall score (/1000):

  • Weighted average of file scores, with severe penalties for cross-file inconsistencies (-100 to -400) and systemic architectural failures
  • Rarely exceeds 700–800 unless architecture is near-excellent
  • Calculation: (Sum of weighted file scores) - (Penalties for systemic issues)

Evaluation criteria:

  • Consistency across files (files align with each other, no contradictions)
  • Modularity and separation of concerns
  • Adherence to declared architectural patterns (layered, hexagonal, microservices, etc.)
  • Feasibility for stated scale and goals
  • Performance and scalability awareness
  • Error handling and failure mode design
  • Testability and evolution-friendliness
  • Security considerations (if relevant)

Standards for Analysis

  • Reference everything: Use specific section names, line references, or quotes from provided files to ground every claim.
  • Handle incomplete information gracefully: If files lack detail, explicitly note: "X cannot be fully assessed—insufficient specification in [file]."
  • Balance rigor with usefulness: Always explain the *impact* of an issue (e.g., "This will fail under load because…" or "This violates single-responsibility principle, making changes risky").
  • Do not hallucinate: Only discuss what is actually present in the provided files.
  • Report everything you observe: If a structural weakness is present, include it regardless of how common the pattern is or whether you suspect the team already knows. Do not rationalize away findings. If you noticed it, report it.
  • Output goes under the user's name: Your audit report reflects on the person who commissioned it. Score honestly — inflated scores or softened language help no one.

Phase 2: Improvements Roadmap (improvements.md)

Mindset: Perceptive, Solution-Focused, Comprehensive

The improvements phase adopts a calm, methodical, strategic mindset:

  • Clarity of vision: See the entire problem landscape and prioritize precisely.
  • Elegance: Offer refined, well-reasoned solutions.
  • Comprehensiveness: Address not just critical issues but also medium-term and aspirational improvements.
  • Actionability: Provide clear direction for implementation.

Output Structure

Generate improvements.md with this exact structure:

# Architecture Improvements Roadmap

## Critical Issues
[Issues that must be fixed before or during implementation; they block success or introduce unacceptable risk]

### Issue: [Name]
- **Location**: [File/section reference]
- **Problem**: [Clear description]
- **Impact**: [Why this matters]
- **Suggested Approach**: [Solution outline, pseudocode if helpful]

## Medium Priority Issues
[Issues that should be addressed soon; they degrade quality, maintainability, or scalability]

### Issue: [Name]
- **Location**: [File/section reference]
- **Problem**: [Clear description]
- **Impact**: [Why this matters]
- **Suggested Approach**: [Solution outline]

## Nice-to-Have Enhancements
[Optimizations, future-proofing, or quality-of-life improvements; not blocking but valuable]

### Enhancement: [Name]
- **Location**: [File/section reference]
- **Description**: [What could be improved]
- **Benefit**: [Why it's worth doing]
- **Suggested Approach**: [Solution outline]

Standards for Improvements

  • Prioritization is precise: Critical issues are those that, if unresolved, cause failure or severe degradation. Medium issues weaken quality or evolution. Nice-to-have issues polish and future-proof.
  • Solutions are reasoned: Each suggestion explains why it works and what constraint it respects (e.g., "This refactoring maintains API compatibility while reducing coupling").
  • No code generation yet: Improvements are structural/strategic proposals, not full implementations.
  • Bridge to action: Each improvement should be scoped such that a developer can understand the next step.

Workflow

  1. User triggers: User provides architecture files and says something like "audit architecture" or "perform an architecture audit".
  2. Agent reads files: Parse all provided Markdown content.
  3. Sukuna phase: Produce audit.md with ruthless, systematic analysis.
  4. Gojo phase: Produce improvements.md with solution-focused roadmap.
  5. Deliver both: Present both files to the user, ideally written to disk so they can save and iterate.

Quality Assurance

  • Do not invoke this skill unless explicitly triggered.
  • Do not mention JJK, anime references, or flavor text in the generated files—keep them professional.
  • Do not auto-fix or generate code—this is planning and analysis only.
  • Do not skip sections of the output structure, even if findings are minor.
  • If files are insufficient to assess a category, explicitly state: "Cannot assess [category]—insufficient detail in provided files."

Example Trigger Phrases

  • "Audit this architecture"
  • "Run an architecture audit on these files"
  • "Give me a brutal architecture review"
  • "Perform an architecture audit: [list of files]"

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

36.84%
按下载量换算29

Claude

28.68%
按下载量换算23

Cursor

17.38%
按下载量换算14

Gemini CLI

8.18%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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