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Deep Discuss

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zhu1090093659
deep-discuss

结构化深度讨论 Skill,用于与用户进行多轮问题分析和方案设计。当用户描述一个问题现象、故障表现、 技术困惑、方案选择困难,或明确说"讨论一下"、"帮我分析"、"我遇到一个问题"、"你觉得怎么样"、 "帮我想想"、"我在纠结"时,必须使用本 skill。当用户提供了一段描述(可能附带截图)并期望深入分析 而非直接给答案时,也应触发本 skill。即使用户只是抛出一个现象描述没有明确提问,也要使用本 skill 来引导结构化思考。不要在简单的事实查询("X是什么")或明确的执行指令("帮我写个脚本")上触发。

Overview

Publisherzhu1090093659
Repositoryspec_driven_develop
Skill namedeep-discuss
Stars
987
Forks
101
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by zhu1090093659 on GitHub. Read the source before you install it.

Installation

Install the Deep Discuss AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zhu1090093659/spec_driven_develop/tree/main/plugins/spec-driven-develop/skills/deep-discuss
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zhu1090093659/spec_driven_develop.git /tmp/spec_driven_develop
mkdir -p .claude/skills
cp -r /tmp/spec_driven_develop/plugins/spec-driven-develop/skills/deep-discuss .claude/skills/deep-discuss
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deep Discuss in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deep Discuss on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deep Discuss is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Deep Discuss — 结构化深度讨论

你正在执行 Deep Discuss 工作流:不急于给答案,先把问题想透。用户描述的"问题"和真正的问题之间常有鸿沟——这个流程用分阶段的纪律保证讨论的质量和深度。

通用规则

  • 标注阶段:每次回复开头标注当前阶段(如 Phase 2 → 问题审查;转换时 Phase 2 done → Phase 3:深度分析),回复末尾简要说明下一步。
  • 不要跳阶段:至少过一遍 Phase 1-4;Phase 5/6 可按问题复杂度合并,但不能完全跳过。用户中途提供新信息时,评估是否回到更早阶段。
  • 信息不足即停:Phase 2 发现信息不足时,先问再等,不要带着未验证的假设往下走。
  • 直接坦诚:用户判断有误就直说并给理由;不确定的事用置信度表述,不用模棱两可的"可能"。

Phase 1:接收信息

只接收,不分析。完整理解用户提供的全部信息(文字、截图、用户的初步判断),用自己的话复述关键点(≤3-5 句)确认理解无误。描述明显模糊时,复述后只提 1-2 个最关键的澄清问题。

Phase 2:问题审查(质量门控)

三层审查:

  1. 问题是否成立:现象是否真构成问题?用户归因是否合理?有无需验证的前提假设?
  2. 信息是否充足:缺什么关键信息(标注:必须有 / 最好有 / 锦上添花)?信息不足时明确说明"能分析到什么程度,还差什么",然后暂停等用户补充。
  3. 是否有隐藏问题:用户没注意到的其他问题?表面现象之下有无更深根因?

建议输出格式(可灵活调整):

## Phase 2:问题审查
### 问题成立性
[判断 + 理由]
### 信息充足度
[已有信息 / 缺失信息 / 对分析的影响]
### 潜在隐藏问题
[发现 / 或"暂未发现"]

Phase 3:深度分析

信息确认足够后展开分析:全面(考虑多种可能性)、有深度(追到 root cause)、有层次(分维度而非线性罗列)、诚实(标注置信度)。总结核心发现后等待用户反馈:补充信息 → 回 Phase 2;认可 → 进 Phase 4;有分歧 → 讨论并调整。

Phase 4:方案设计

  • 优先给 2-3 个可选方案(除非只有唯一合理解法)。
  • 每个方案明确:做什么、为什么、代价、适用场景;方案间有 trade-off 要明确对比。
  • 给出推荐方案及理由,最终选择权留给用户。

Phase 5:方案自检

主动自查:遗漏的场景或边界条件?前提假设是否都成立?复杂度是否被低估?有无更简单的替代?是否覆盖了 Phase 2 识别的所有问题(含隐藏问题)?发现问题当场修正。

Phase 6:最终确认

用户确认方向后做最后一轮检查:步骤完整性、意外情况预案、执行后如何验证问题真解决了、补充建议。目标是从"可以做"提升到"做得好"。

Phase 7:执行(可选)

仅在用户明确说"开始执行"等指令时进入。按确认的方案逐步执行,每个关键步骤简要汇报,遇意外暂停并回到讨论模式。

Frequently asked questions

What does the Deep Discuss AI skill do?

结构化深度讨论 Skill,用于与用户进行多轮问题分析和方案设计。当用户描述一个问题现象、故障表现、 技术困惑、方案选择困难,或明确说"讨论一下"、"帮我分析"、"我遇到一个问题"、"你觉得怎么样"、 "帮我想想"、"我在纠结"时,必须使用本 skill。当用户提供了一段描述(可能附带截图)并期望深入分析 而非直接给答案时,也应触发本 skill。即使用户只是抛出一个现象描述没有明确提问,也要使用本 skill 来引导结构化思考。不要在简单的事实查询("X是什么")或明确的执行指令("帮我写个脚本")上触发。

Why use Deep Discuss on TypingMind?

Because you install it once and use it with any model. Deep Discuss is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deep Discuss in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhu1090093659/spec_driven_develop/tree/main/plugins/spec-driven-develop/skills/deep-discuss. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Deep Discuss?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deep Discuss?

As many as you like. As long as a model supports skills, you can use Deep Discuss with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deep Discuss AI skill free?

Yes. It is published on GitHub by zhu1090093659 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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