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.
npx agentmods add skills/peterfei/forge-skill/inversion-thinking-skillnpx skills add peterfei/forge-skill --skill inversion-thinking-skillgit clone --depth 1 https://github.com/peterfei/forge-skillWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00078 | $0.04481 |
| Opus 5 | $0.00039 | $0.02240 |
| Sonnet 5 | $0.00016 | $0.00896 |
| Haiku 4.5 | $0.00008 | $0.00448 |
Grade A, and why
inversion-thinking-skill 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
逆向思维(Inversion Thinking)思维工具
"Invert, always invert"(逆向,总是逆向)—— Carl Gustav Jacob Jacobi
"我只想知道将来我会死在什么地方,这样我就可以永远不去那里"—— Charlie Munger
激活条件与触发词
直接使用触发词
- 「用逆向思维分析...」
- 「帮我做事前验尸」
- 「从反面角度思考」
- 「如何避免失败」
- 「inversion」「premortem」
诊断推荐触发词
- 「想提前识别风险」
- 「担心项目失败」
- 「不知道哪里会出错」
- 「需要预防性分析」
方法框架概览
逆向思维是一种通过翻转问题视角来获得新洞察的认知工具。它不直接问"如何成功",而是问"如何避免失败",通过系统性地考虑失败模式、风险因素和反面情景,发现正向思维容易忽略的问题。其核心价值在于避免灾难性错误,特别适合复杂系统、风险管理和重大决策场景。
核心原理
原理1:问题翻转原理(Problem Inversion)
一句话定义: 通过将问题倒置(从"如何成功"转向"如何避免失败")获得新的洞察视角。
跨域证据1: [数学领域] 德国数学家 Carl Gustav Jacobi(1804-1851)使用德语短语"man muss immer umkehren"(必须总是逆转)来解决复杂的数学问题。他相信通过逆转已知结果可以开辟新的研究领域。这一数学方法论成为了逆向思维的经典起源。
跨域证据2: [投资领域] Charlie Munger 推广"逆向,总是逆向"作为投资决策的核心方法。Munger 认为:"很多问题无法正向解决,但可以从反面解决。"在 Berkshire Hathaway 的投资实践中,他通过问"什么会导致投资失败"而非"什么会导致投资成功",成功避开了无数陷阱。
应用方式: 将正面问题翻转("如何让项目成功"→"如何让项目失败"),头脑风暴所有可能的失败方式,针对每个失败模式制定预防措施。适用于投资决策、项目管理、软件工程、产品设计等多个领域。
局限: 过度关注负面可能导致焦虑和损失厌恶,需要与正向思维和创新精神平衡。
原理2:避免愚蠢而非追求聪明(Avoiding Stupidity Over Seeking Brilliance)
一句话定义: 防止错误的关注点往往比追求成功更有效,因为"避免愚蠢"比"变得聪明"更容易。
跨域证据1: [投资哲学] Munger 的名言:"我只想知道将来我会死在什么地方,这样我就可以永远不去那里。"这一哲学的核心是:识别并避开明显的错误,比试图预测或创造成功更加可靠。
跨域证据2: [软件工程] 现代软件开发通过考虑失败模式,提前添加断路器、重试机制、故障转移策略,而非试图构建"完美无bug"的系统。Stackademic 报告显示,采用逆向思维的团队在6个月内生产环境bug减少60-80%。
应用方式: 在投资中识别并避开"能力圈"之外的决策;在软件开发中提前考虑bug场景并添加防护;在商业决策中识别"什么会摧毁业务"而非"如何增长业务"。
局限: 仅靠避免错误不足以达到卓越,需要主动创新和机会导向的思维配合。
原理3:前瞻性回溯原理(Prospective Hindsight)
一句话定义: 在事件发生前就假设其已经失败,通过"事后分析"提前识别风险因素。
跨域证据1: [决策科学研究] Gary Klein(2007)在 Harvard Business Review 提出"事前验尸"(Premortem)技术,基于前瞻性回溯概念。Klein 的研究表明,这种方法能让团队在项目开始前识别出80%的潜在失败原因。
跨域证据2: [绩效研究] Wharton、Cornell 和科罗拉多大学的联合研究表明,前瞻性回溯能将团队正确识别项目失败原因的能力提高30%。该方法被广泛应用于医疗保健、研究论文撰写、项目合作等领域。
应用方式: (1) 项目启动前假设"项目已经失败";(2) 团队成员各自写下导致失败的可能原因;(3) 分析原因的合理性和预防措施;(4) 制定具体行动计划预防这些失败。
局限: 需要团队坦诚文化和心理安全感才能有效;在等级森严的组织中,下属可能不敢说出真正的风险。
原理4:能力圈边界原理(Circle of Competence)
一句话定义: 明确自己的知识边界,只在这个范围内做决策,避免在能力圈外犯错。
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.
- 2d ago First seen · 273 lines · 78 tokens per session scan A 3d4e516da1f4
inversion-thinking-skill is a skill published in the GitHub repository peterfei/forge-skill (13 stars, last pushed 2mo ago), licensed MIT. It adds 78 tokens to every session and 4,481 once invoked, about $0.0004 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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