Agent skill
deep-analysis
Execute high-density architectural analysis on user ideas. Move from 'Vague' to 'Verified' using a 5-step logic chain: Calibration → Decomposition → Excavation → Re-Architecting → Inversion. This skill should be used when analyzing system architecture, validating technical ideas, or performing pre-mortems on solutions.
Install this agent skill to your Project
npx add-skill https://github.com/bamecho/my-claude-skills/tree/main/deep-analysis
SKILL.md
Architectural Analysis
Overview
Execute high-density architectural analysis to transform vague ideas into verified, actionable architectures through a rigorous 5-phase logic chain.
Style: Code-like, Concise, No "AI explaining itself". Pure signal.
Critical Rules
- NO FLUFF - Output must be dense, actionable, and structured
- VISUALIZE - Use Mermaid.js for all structural mappings
- RUTHLESSNESS - Challenge assumptions at every step. Never confirm user biases
The Process
PHASE 0: CALIBRATION (The Anchor)
Evaluate if user has provided concrete constraints before generating solutions:
- IF YES: Bind constraints strictly
- IF NO: Assume context = "MVP/Prototype Stage" (Low Cost, High Iteration, Small Scale) and PROCEED
PHASE 1: DECOMPOSITION (The Pareto Slice)
- Smash the problem/system into its smallest indivisible units ("The LEGO Bricks").
- Group atomic units into independent "Black Boxes" (Modules). Modules must be Decoupled. Analyzing Module A should not require holding Module B in memory.
- Identify top 20% of modules carrying 80% of functional weight or risk
- Label the rest as "Trivial/Later"
- Output: List CORE modules only. Discard noise
PHASE 2: EXCAVATION (First Principles)
For CORE modules identified in Phase 1:
- Strip away all "best practices" and "industry standards"
- Identify Irreducible Truths (Physical limits, Logic gates, Bandwidth laws)
- Ask: "Why can't we do it 10x greater/faster?" to find fundamental bottleneck
- Output: A "Fact vs. Assumption" table for each core module
PHASE 3: RE-ARCHITECTING (Structural Evolution)
Reassemble components based on First Principles findings, NOT original assumptions:
- Optimize path: Remove redundant hops/processes found in Phase 2
- Output: Generate a Mermaid.js Flowchart
- Show data flow, dependencies, and critical paths
- Structure must be simpler and more direct than initial decomposition
PHASE 4: OSCILLATION (Zoom In/Out)
- Action: Oscillate between the texture and the landscape.
- Zoom In: Look at the "Code/Texture" of the Key Driver. (The implementation detail).
- Zoom Out: Look at the "Time/Cycle" of the system. (Where is this in the historical lifecycle?).
- Output: A synthesis of how the micro-detail affects the macro-destiny.
PHASE 5: INVERSION (The Pre-Mortem)
Assume solution has FAILED CATASTROPHICALLY 6 months post-launch:
- Do not ask "Will it work?"
- Ask "How exactly did it break?" (Race conditions, cost explosion, user rejection)
- Attack solution using Phase 0 constraints
- Output: List of "Kill Shots" (Fatal Flaws) and required "Patches" (Mitigation strategies)
Output Format
### 0.约束条件 (假设/给定)
...
### 1.核心模块 (帕累托Top 20%)
[模块名]: [一句话说明为何这是核心]
[模块名]: [一句话说明为何这是核心]
### 2.第一性原理真相
[模块A] [根本限制/真相]
[模块B] [根本限制/真相]
### 3.逻辑流程图
[Mermaid Code]
### 4.对齐检查
宏观: [简要生态系统适配检查]
微观: [最高风险组件的机制检查]
### 5.事前验尸 (失败检查)
* 最薄弱环节: [具体组件]
* 失败模式: [如何崩溃] -> 修复: [具体补丁]
Key Principles
- Pareto Focus - 20% modules carry 80% weight, ignore the rest initially
- First Principles - Strip away conventions to find irreducible truths
- Inversion Thinking - Assume failure first, then work backwards
- Visual Architecture - Always produce Mermaid diagrams for structural clarity
- Constraint Binding - No constraints means MVP mode, proceed anyway
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