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complex-reasoning

complex-reasoning

github.com/thelobbiAgent 工作流21167 次安装1 天前更新
代码仓库

关于 complex-reasoning

Complex Reasoning Skill 为需要系统分析问题的用户提供结构化推理框架,适用于调试、架构决策和根因分析等任务。它包含线性、分支式及假设驱动的方法,也提供依赖与影响分析模式。

主要功能

  1. 01提供 CoT、ToT 和 MECE 框架
  2. 02支持假设驱动的调试
  3. 03包含依赖关系分析模式
  4. 04提供变更影响分析模式
  5. 05给出推理过程的实践建议

适用场景

  1. 01分析复杂故障的可能原因
  2. 02比较架构方案的权衡
  3. 03调查生产事件的根本原因
  4. 04评估安全风险或重构影响

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/thelobbi/claude --skill complex-reasoning

安装后在 Claude Code 中输入/complex-reasoning确认已加载。

详细介绍

复杂推理技能

用于系统化解决问题的结构化推理框架,借助扩展思考能力进行深入分析。

使用场景

  • 调试复杂问题,涉及多种潜在原因
  • 架构决策,需要权衡分析
  • 生产事故的根因分析
  • 性能优化,涉及多个变量
  • 安全漏洞评估
  • 代码重构,涉及大量依赖项

推理框架

思维链(CoT)

针对顺序问题进行线性、逐步推理。

## Chain-of-Thought Analysis

**Problem**: [State the problem clearly]

**Step 1: Understand the Context**
- What do we know?
- What are the constraints?
- What is the expected outcome?

**Step 2: Identify Key Components**
- Component A: [description]
- Component B: [description]
- Interactions: [how they relate]

**Step 3: Analyze Each Component**
- Component A analysis...
- Component B analysis...

**Step 4: Synthesize Findings**
- Key insight 1
- Key insight 2

**Step 5: Formulate Solution**
- Recommended approach
- Rationale
- Trade-offs

**Conclusion**: [Final recommendation with confidence level]
思维树(ToT)

针对存在多种解决路径的问题进行分支探索。

## Tree-of-Thought Exploration

**Root Problem**: [Problem statement]

### Branch 1: Approach A
├── Pros: [List advantages]
├── Cons: [List disadvantages]
├── Feasibility: [High/Medium/Low]
├── Sub-branch 1.1: [Variation]
│   └── Outcome: [Expected result]
└── Sub-branch 1.2: [Variation]
    └── Outcome: [Expected result]

### Branch 2: Approach B
├── Pros: [List advantages]
├── Cons: [List disadvantages]
├── Feasibility: [High/Medium/Low]
└── Sub-branches: [...]

### Branch 3: Approach C
├── Pros: [...]
├── Cons: [...]
└── Feasibility: [...]

### Evaluation Matrix
| Approach | Feasibility | Impact | Risk | Score |
|----------|-------------|--------|------|-------|
| A        | High        | Medium | Low  | 8/10  |
| B        | Medium      | High   | Med  | 7/10  |
| C        | Low         | High   | High | 5/10  |

**Selected Path**: Branch [X] because [reasoning]
MECE 框架

相互独立、完全穷尽的分析。

## MECE Analysis

**Problem Space**: [Define the complete problem]

### Category 1: [Mutually exclusive category]
- Sub-element 1.1
- Sub-element 1.2
- Sub-element 1.3

### Category 2: [Mutually exclusive category]
- Sub-element 2.1
- Sub-element 2.2

### Category 3: [Mutually exclusive category]
- Sub-element 3.1
- Sub-element 3.2
- Sub-element 3.3

**Completeness Check**:
- [ ] Categories are mutually exclusive (no overlap)
- [ ] Categories are collectively exhaustive (cover all cases)
- [ ] Each sub-element belongs to exactly one category

**Priority Matrix**:
| Category | Urgency | Impact | Action |
|----------|---------|--------|--------|
| 1        | High    | High   | Now    |
| 2        | Medium  | High   | Next   |
| 3        | Low     | Medium | Later  |
假设驱动调试

系统化调试复杂问题的方法。

## Hypothesis-Driven Debug Session

**Symptom**: [Observed behavior]
**Expected**: [What should happen]
**Environment**: [Relevant context]

### Hypothesis 1: [Most likely cause]
**Evidence For**:
- [Supporting observation 1]
- [Supporting observation 2]

**Evidence Against**:
- [Contradicting observation]

**Test**: [How to validate]
**Result**: [Confirmed/Refuted]

### Hypothesis 2: [Second most likely]
**Evidence For**:
- [...]

**Evidence Against**:
- [...]

**Test**: [...]
**Result**: [...]

### Root Cause Identified
**Cause**: [Confirmed root cause]
**Evidence Chain**: [How we proved it]
**Fix**: [Remediation steps]
**Prevention**: [How to prevent recurrence]

代码分析模式

依赖分析
## Dependency Analysis: [Component Name]

### Direct Dependencies
| Dependency | Version | Purpose | Risk Level |
|------------|---------|---------|------------|
| dep-a      | 2.3.1   | Auth    | Low        |
| dep-b      | 1.0.0   | Data    | Medium     |

### Transitive Dependencies
- Total: [N] packages
- Security vulnerabilities: [N]
- Outdated: [N]

### Dependency Graph

[component] ├── dep-a │ ├── sub-dep-1 │ └── sub-dep-2 └── dep-b └── sub-dep-3


### Risk Assessment
1. **High Risk**: [Dependencies with known issues]
2. **Medium Risk**: [Outdated or unmaintained]
3. **Low Risk**: [Stable, well-maintained]

### Recommendations
1. [Action item 1]
2. [Action item 2]
影响分析
## Impact Analysis: [Proposed Change]

### Affected Components
| Component | Impact Type | Severity | Test Required |
|-----------|-------------|----------|---------------|
| Service A | Direct      | High     | Yes           |
| Service B | Indirect    | Medium   | Yes           |
| Client C  | Downstream  | Low      | Optional      |

### Risk Assessment
- **Breaking Changes**: [List any]
- **Performance Impact**: [Expected effect]
- **Data Migration**: [Required/Not required]

### Rollback Plan
1. [Step 1]
2. [Step 2]
3. [Verification]

### Recommendation
[Go/No-Go with reasoning]

与扩展思考结合使用

将这些框架与扩展思考结合使用时:

# Enable extended thinking for complex reasoning
response = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=16000,
    thinking={"type": "adaptive"},
    output_config={"effort": "high"},  # deeper reasoning for complex problems
    system="""You are a systematic problem solver. Use structured
    reasoning frameworks like Chain-of-Thought, Tree-of-Thought,
    or MECE analysis as appropriate for the problem.""",
    messages=[{
        "role": "user",
        "content": "Analyze this architecture decision using ToT..."
    }]
)

最佳实践

  1. 选择合适的框架:线性问题使用 CoT,分支决策使用 ToT
  2. 记录推理过程:便于审查和复用
  3. 验证假设:每个步骤都应建立在已验证的事实之上
  4. 考虑替代方案:始终至少探索 2–3 种方法
  5. 尽可能量化:使用指标比较选项
  6. 限制探索时间:为分析深度设定上限

另请参阅

  • [[extended-thinking]] - 启用深度推理能力
  • [[deep-analysis]] - 分析模板
  • [[debugging]] - 通用调试模式
  • [[testing]] - 验证策略

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