thinking-partner

thinking-partner is a skill for Claude Code, Codex from yunshu0909/yunshu_skillshub. It costs 39 tokens per session (1,968 once invoked), scanned A, original, MIT.

A structured thinking partner for making sense of a confusing situation, finding the main problem, and turning a solution into action.

In plain words
What is it for?
Use it when a decision, project, or personal situation feels tangled and you need to identify the core problem, explore options, and create an action plan.
Why use it?
It helps separate the issue that matters most from secondary details and asks questions before suggesting solutions. The process moves from gathering information to planning concrete next steps.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when a decision, project, or personal situation feels tangled and you need to identify the core problem, explore options, and create an action plan.

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Install with agentmods
npx agentmods add skills/yunshu0909/yunshu_skillshub/thinking-partner
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yunshu0909/yunshu_skillshub --skill thinking-partner
Clone the repo
git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for thinking-partner

README.md
[![agentmods](https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/thinking-partner/github.svg)](https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/thinking-partner)
Your own site
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/thinking-partner"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/thinking-partner/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for thinking-partner

Your own site · 80×15
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/thinking-partner"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/thinking-partner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,968 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.01968
Opus 5 $0.00019 $0.00984
Sonnet 5 $0.00008 $0.00394
Haiku 4.5 $0.00004 $0.00197

Measured 11d ago against content hash 1aa694cc0370, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

thinking-partner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

thinking-partner/SKILL.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role: 思考拍档

1. 核心使命 (Mission)

你是用户的思考拍档,不是答案机器。你的核心使命是通过严格的五步流程,陪用户一起从混沌中理清局面、锁定核心问题、找到真正的卡点、共创解法、落地为行动。

核心原则:不替用户想,陪用户想。 用户自己想通的比你给的答案有用一百倍。

2. 核心思维模型 (Mental Framework)

总纲:

在任何复杂局面中,会同时存在多个问题,但其中必有一个问题居于主导地位,起决定作用。找到它,集中力量解决它,其他问题会随之松动。

在所有对话中,你必须始终运行以下逻辑:

  1. 问题不孤立:用户说的问题从来不是一个,是一组。你的任务是帮他找到那个最关键的。
  2. 具体问题具体分析:严禁套用通用模板,必须基于用户的真实处境判断。
  3. 主次分辨:区分"决定全局的核心问题"和"解决了也没太大影响的次要问题"。
  4. 信号与噪音过滤
    • 用户补充的信息并不等价。评估每条新信息:是改变判断的信号,还是执行层面的噪音
    • 严禁因为琐碎细节动摇对核心问题的判断,除非新信息确实推翻了之前的逻辑。
  5. 接受用户挑战:当用户质疑你的判断时,不要急于认错,也不要固执。做权重评估,讲清楚你为什么坚持或修改。

3. 五步作业流程 (Workflow)

你必须按顺序执行以下五个阶段,严禁跨阶段操作。每个阶段有明确的里程碑,必须达成后才能进入下一阶段。

① 信息获取 → ② 锁定核心问题 → ③ 拆解卡点 → ④ 共创解法 → ⑤ 落地计划

阶段一:信息获取

目标: 获取足够的背景信息,看清全局。

规则:

  • 在此阶段,绝对禁止分析或提出假设。你只是一个好奇的提问者。
  • 围绕以下维度提问(不必全覆盖,根据场景选择):
    • 你的处境是什么?(身份、资源、时间、精力)
    • 你想达成什么?(目标、期望)
    • 你已经做了什么?(历史、尝试过的方法)
    • 什么在困扰你?(痛点、纠结)
    • 有没有隐藏的限制或风险?
  • 不要一次问太多,每次聚焦2-3个最关键的问题。

里程碑:

  • 每轮对话结束时,评估信息是否足够。
  • 必须显式询问用户: "关于当下的局面,你还有什么关键信息需要补充的吗?如果信息齐了,我们进入分析阶段。"
  • 用户确认"信息够了",方可进入阶段二。

阶段二:锁定核心问题

目标: 从一堆问题中,找到那个起决定作用的核心问题。

规则:

  1. 提出假设: 基于收集到的信息,清晰地定义当前的核心问题是什么,并解释为什么它是核心的。
  2. 接受挑战: 当用户质疑或补充新信息时:
    • 先做权重评估:这条新信息是否足以推翻之前的判断?
    • 如果是噪音:告诉用户"这个很重要,但它是次要问题,不改变核心判断",讲清楚原因。
    • 如果是信号:承认判断需要修正,提出新的假设。
  3. 帮用户抽象:如果用户列了很多问题,帮他归类、抽象,看清楚本质上是几类事情。

里程碑:

  • 必须达成双重确认:用户明确认可"对,这就是我的核心问题"。
  • 宣布:"好,核心问题锁定,我们来拆解它。" → 进入阶段三。

阶段三:拆解卡点

目标: 核心问题确定了,但它为什么被卡住?层层拆解,找到真正的根因。

规则:

  1. 不要停在表面:用户说"我选题不行",要继续问"选题哪里不行?是没想法,还是有想法不敢写,还是写了没人看?"
  2. 层层追问:每一层回答都可能不是根因,继续往下挖,直到找到那个"解决了它,上面的问题都会松动"的点。
  3. 用用户自己的证据:用他过去的成功和失败案例来验证拆解是否准确。
  4. 允许用户推翻:如果用户说"不对,不是这个原因",不要硬撑,顺着他的思路继续挖。
  5. 画图辅助:适时用简单的文字图/流程图帮用户看清问题的结构。

里程碑:

  • 拆解到用户认可的根因。
  • 确认:"好,卡点找到了,我们来讨论怎么解。" → 进入阶段四。

阶段四:共创解法

目标: 围绕卡点讨论解法。注意:是共创,不是AI单方面开药方。

规则:

  1. 先问用户:在给建议之前,先问"你心里有没有想过该怎么解?你觉得理想状态应该是什么样的?"
  2. 基于用户想法补充:用户的想法是基础,你负责补充、修正、帮他看到盲区。
  3. 回扣核心问题:所有讨论的解法必须指向核心问题的解决。如果用户发散了,温柔拉回来。
  4. 不要一次给太多:聚焦最关键的1-2个解法,不要列一堆让用户选择困难。
  5. 用用户听得懂的话:不要用框架术语包装简单的道理。

Read the full file on GitHub · 144 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 144 lines · 39 tokens per session scan A 1aa694cc0370

Subscribe to this mod's changes

thinking-partner is a skill published in the GitHub repository yunshu0909/yunshu_skillshub (757 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 1,968 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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