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inversion-protocol反演协议

Agent Skill

inversion-protocol 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

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周安装

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下载量

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:inversion-protocol(反演协议)
来源仓库:https://github.com/jcools1977/inversion-protocol
安装命令:
openclaw skills install inversion-protocol
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install inversion-protocol

简介

inversion-protocol 采用逆向思维框架提升 AI Agent 的决策质量与风险控制能力。

  • 适用于复杂问题分析,通过预想失败路径反向推导最优行动方案。
  • 借鉴芒格多元思维模型,整合多学科视角评估潜在陷阱。
  • 不直接提供答案,而是引导提问方式与推理结构设计。
  • 需配合具体任务上下文使用,抽象程度较高,初学者建议分步练习。

SKILL.md

name
inversion-protocol
description
>
version
1.0.0
author
J. DeVere Cooley
metadata
openclaw
emoji
\F500
homepage
https://github.com/jcools1977/Opensaw
tags
os

Inversion Protocol

"All I want to know is where I'm going to die, so I'll never go there." — Charlie Munger

What This Skill Does

The Inversion Protocol is a meta-cognitive reasoning layer that improves the quality of every decision an AI agent makes. It works by inserting a rapid backwards-thinking checkpoint before significant actions.

Most skills give bots new capabilities. This skill makes all existing capabilities work better by catching errors, hallucinations, wrong assumptions, and overengineered solutions before they happen.

This skill has zero dependencies and zero runtime cost. It is pure reasoning enhancement — no APIs, no binaries, no environment variables, no external services.

When to Activate

Apply the Inversion Protocol before any action where being wrong matters:

  • Writing or modifying code
  • Running destructive or irreversible commands
  • Debugging a problem (especially when stuck)
  • Making architectural or design decisions
  • Answering questions where accuracy is critical
  • Performing multi-step workflows
  • Any situation where the user has corrected you before

Do NOT apply to trivial actions like reading files, listing directories, or responding to greetings. The protocol is for moments of consequence.

The Three Lenses

When the protocol activates, apply these three lenses in order. Each takes only seconds but catches entirely different classes of errors.

Lens 1: Inversion (The Reverse Engineer)

Ask: "How would I deliberately CREATE this problem?"

Instead of asking "how do I fix this?", ask "how would I break this on purpose?" The answers reveal root causes that forward-thinking misses entirely.

Mechanics:

  1. State the problem or goal clearly in one sentence
  2. Invert it: describe 3 specific ways you would cause this exact failure
  3. Check: are any of those failure patterns present in the current situation?
  4. If yes — you've found your root cause. Address it directly.

Example — Debugging slow code:

  • Forward thinking: "Let me profile and optimize hot paths"
  • Inversion: "How would I make code slow on purpose?"

- Add unnecessary nested loops over large datasets - Make redundant database/API calls inside loops - Block the main thread with synchronous operations - Skip caching and recompute everything every time

  • Check the codebase for these exact anti-patterns
  • Result: finds the N+1 query problem in 30 seconds instead of 30 minutes

Example — Writing an API endpoint:

  • Forward thinking: "Let me implement the happy path"
  • Inversion: "How would I make this API as insecure as possible?"

- Accept unsanitized input directly into queries - Return full error stack traces to the client - Skip authentication and rate limiting - Log sensitive data in plaintext

  • Check: am I accidentally doing any of these?
  • Result: catches security issues during development, not in production

Lens 2: Premortem (The Time Traveler)

Ask: "It's tomorrow and this completely failed. What went wrong?"

The premortem technique (created by psychologist Gary Klein) exploits a cognitive bias: people are better at explaining past events than predicting future ones. By framing the failure as already having happened, you unlock failure modes your brain would otherwise suppress.

Mechanics:

  1. Assume your planned action has already been executed and it failed
  2. Generate the 3 most likely reasons for the failure
  3. For each reason, determine: can I verify this won't happen BEFORE acting?
  4. If verifiable — verify it. If not — add a safeguard.

Example — Refactoring a function:

  • Planned action: Extract shared logic into a helper function
  • Premortem: "The refactor shipped and broke production. Why?"

- The function had hidden side effects I didn't notice (most likely) - Other code depended on the exact return shape, not just the value - The test suite doesn't cover the edge case this function handles

  • Verify: Read all callers. Run the tests. Check for side effects.
  • Result: Discovers the function mutates a global config object — would have

caused a subtle production bug

Example — Answering a technical question:

  • Planned action: Provide a solution using library X
  • Premortem: "The user tried my solution and it didn't work. Why?"

- Library X's API changed in a recent version I'm not aware of - The user's environment has constraints I didn't ask about - My solution works in isolation but conflicts with their existing code

  • Verify: Acknowledge version uncertainty. Ask about constraints. Caveat the

answer.

  • Result: Provides a robust answer instead of a confident-but-wrong one

Lens 3: Via Negativa (The Razor)

Ask: "What is the ONE thing I absolutely must NOT do here?"

Inspired by Nassim Taleb's principle that removing harm is more powerful than adding good. In complex systems, avoiding the worst mistake matters more than finding the best solution. This lens prevents catastrophic errors.

Mechanics:

  1. Identify the single most damaging mistake possible in this situation
  2. Explicitly confirm you are not about to make that mistake
  3. If you are — stop and reconsider your entire approach

Example — Database migration:

  • Via Negativa: "The ONE thing I must NOT do?"

- Drop or alter a column that other services depend on without coordination

  • Check: Am I about to do this? → Yes, the users.email column is referenced

by the auth service

  • Result: Prevents a cascading multi-service outage

Example — Responding to a frustrated user:

  • Via Negativa: "The ONE thing I must NOT do?"

- Give the same answer they've already rejected, reworded

  • Check: Is my new response materially different? → No, it's basically the same

approach with different syntax

  • Result: Forces a genuinely new approach instead of rephrasing failure

Integration Patterns

Pattern A: Full Protocol (Complex Decisions)

For architectural choices, multi-file refactors, debugging sessions where you're stuck, or high-stakes operations:

[INVERSION PROTOCOL — FULL]
Goal: {one-sentence description of what I'm about to do}

INVERT: How would I cause this problem?
1. {failure pattern 1}
2. {failure pattern 2}
3. {failure pattern 3}
Present in current situation? {yes/no + details}

PREMORTEM: It failed. Why?
1. {most likely cause}
2. {second most likely}
3. {third most likely}
Verifiable before acting? {verification steps}

VIA NEGATIVA: The ONE thing I must NOT do?
→ {the catastrophic mistake to avoid}
Am I about to do it? {yes/no}

DECISION: {proceed / adjust approach / stop and rethink}

Pattern B: Quick Check (Routine Actions)

For writing functions, running commands, or standard responses — a 5-second mental check:

[INVERSION — QUICK]
Inverse: {one way I'd cause this to fail}
Premortem: {one reason this could go wrong}
Razor: {the one thing NOT to do}
→ {proceed / adjust}

Pattern C: Stuck Mode (When Progress Has Stalled)

When the agent has tried multiple approaches and none work, or the user has corrected the same type of mistake more than once:

[INVERSION PROTOCOL — STUCK MODE]
I've been trying to: {description}
My approaches so far: {list what's been tried}

FULL INVERSION: How would I guarantee this NEVER works?
1. {anti-approach 1}
2. {anti-approach 2}
3. {anti-approach 3}

Am I accidentally doing any of these? {analysis}

REFRAME: What if the problem isn't {what I think it is}
but actually {inverted framing}?

What This Skill Does NOT Do

  • It does not add tools or API integrations
  • It does not require any environment variables, config, or dependencies
  • It does not slow down the agent perceptibly (seconds per check)
  • It does not override the user's instructions
  • It does not apply to trivial actions
  • It is not a safety filter or content policy — it improves decision QUALITY

Why This Works (The Cognitive Science)

  1. Confirmation bias countermeasure: Humans and LLMs naturally seek evidence

that confirms their first instinct. Inversion forces consideration of disconfirming evidence.

  1. Prospective hindsight: Klein's research showed that premortems increase

the ability to identify failure reasons by 30% compared to standard "what could go wrong?" thinking.

  1. Subtraction over addition: Taleb's Via Negativa recognizes that in

complex systems, avoiding the worst outcome (robustness) is more valuable than optimizing for the best outcome.

  1. Second-order thinking: The protocol naturally produces second-order

consequences that first-pass reasoning misses.

Composability

The Inversion Protocol enhances every other skill in the ecosystem:

  • Code skills → catch bugs before they're written
  • DevOps skills → prevent misconfigured deployments
  • Research skills → avoid confirmation-biased searches
  • Communication skills → prevent tone-deaf responses
  • Financial skills → catch risky trades before execution
  • Automation skills → prevent runaway processes

It is a force multiplier, not a replacement for any existing capability.

适合场景

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用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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