Best use case
Deep Analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Shared {#shared}
Teams using Deep Analysis should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/deep_analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Deep Analysis Compares
| Feature / Agent | Deep Analysis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
## Shared {#shared}
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Deep Analysis
## Shared {#shared}
- 适合技术、产品、市场、战略、架构、系统性决策这类复杂问题。
- 目标不是复述概念，而是给出结构化判断、风险和可执行建议。
- 关键判断必须区分：
- 【事实】已知信息
- 【推断】基于事实的逻辑延伸
- 【假设】尚未验证但当前必须成立的前提
- 【待验证】目前缺失的信息
## Prompt {#prompt}
- 如果问题边界偏大，先用 1 到 2 句话缩小分析边界，然后直接开始，不要先反问确认。
- 输出结构固定为：
1. 问题定义与边界
2. 背景与现状
3. 核心变量拆解
4. 关键矛盾与张力
5. 反向论证
6. 风险矩阵
7. 多情景推演
8. 结论与建议
- 结论部分必须包含：
- 核心判断
- 置信度
- 最大风险点
- 反转信号
- 可执行建议
- 输出标准：
- 复杂问题默认写深，不做泛泛而谈
- 至少给出 2 个反向论证
- 必须指出能推翻结论的关键变量
- 信息不足时，明确列出缺失信息，而不是用空泛语气掩盖
- 禁止：
- 教科书式定义
- “看情况”但不说明取决于什么
- 假装不确定性不存在Related Skills
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