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Agent Skill · 研究检索

hurricane-problem-solver(飓风问题解决者)

hurricane-problem-solver 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。

hurricane-problem-solver 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 25,257。

总安装 3,810周安装 162GitHub Stars 公开资料未说明下载 1,335核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:hurricane-problem-solver(飓风问题解决者)
来源仓库:https://github.com/maryambahri/hurricane-problem-solver
安装命令:
openclaw skills install hurricane-problem-solver
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。

ClawHubOpenClaw
openclaw skills install hurricane-problem-solver

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

针对混乱、高风险或复杂问题提供根本原因分析与解决方案。适用于需要系统性拆解深层矛盾的场景。通过结构化方法识别关键节点并提出可执行改进路径。安装命令:openclaw skills install hurricane-problem-solver。建议在明确问题边界后调用,以提高分析效率与准确性。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install hurricane-problem-solver;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

hurricane-problem-solver 怎么安装?

在终端执行 openclaw skills install hurricane-problem-solver。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

hurricane-problem-solver 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

hurricane-problem-solver 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

hurricane-problem-solver 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

hurricane-problem-solver 用的人多吗?

公开数据是累计安装 3,810 次,近一周安装 162 次,下载 1,335 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

hurricane-problem-solver 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
hurricane-problem-solver

飓风问题解决者 · 本页

3,810—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
hurricane-problem-solver
description
Deep root-cause problem solving for messy, high-stakes, or deceptively complex problems in any domain. Use when a problem feels bigger than it should, when symptoms are multiplying, when the user asks for problem solving or root-cause analysis, or when the visible issue may be downstream of hidden structural causes. Follow clues without premature judgment, open multiple hypotheses in parallel, test and eliminate, pull distant-looking threads, and reduce the mess into one core cause or a tightly connected cluster of causes plus the highest-leverage fix.

Hurricane Problem Solver

Overview

Use this skill like a forensic storm, not a tidy corporate checklist. Walk in, take the complaint as it is, and start listening for the thing underneath the thing. In the background, begin forming a clean problem statement, because a badly defined problem is basically a hostage situation. Keep that statement flexible and keep sharpening it as new information appears.

Do not start by marrying a theory. Start with symptoms, disturbances, inconsistencies, traces, pressure points, and weird little details that keep refusing to die. Pull threads, shake the ground, surface hidden links, eliminate weak explanations, and keep going until the real engine shows itself.

This skill is domain-agnostic. Use it for technical failures, product issues, behavioral patterns, business messes, strategy problems, interpersonal dynamics, operations, or anything else that looks tangled.

If the problem is still fuzzy or the investigation needs more pressure from unusual angles, read references/questioning-patterns.md and pull from it selectively.

Operating posture

  • Suspend judgment at the start.
  • Refuse the first neat answer. It is often the decoy.
  • Treat every symptom as a clue, not a conclusion.
  • Let distant causes stay in play if they explain the pattern.
  • Open multiple live hypotheses at once.
  • Test by elimination, not by attachment.
  • Prefer truth and elegant solutions over rapid easy ones.
  • Stay critical, unsentimental, and unbiased.
  • Be sharp when needed.
  • Use humor lightly when something absurd, obvious, or painfully human is exposed. A small laugh can help reveal the truth, but never let humor blur the analysis.
  • Keep pushing until further digging stops changing the explanation.

Core workflow

1. Take in the complaint and draft the problem statement

Start with the complaint in the user's own language. In parallel, draft a plain-language problem statement in the background. Treat that statement as provisional and keep refining it as new evidence appears.

Capture:

  • visible symptoms
  • when and where the problem appears
  • when and where it does not
  • what changed before it showed up
  • why it matters now
  • why it is painful now
  • when the pain really started, even if it went unnoticed
  • what started the pain
  • whether the pain is a sudden event or the result of a cumulative chain of events
  • what that chain of events looks like so far

Do not compress too early. Messy inputs are useful. A better-defined problem usually produces a better root-cause path.

2. Build the symptom map

List symptoms separately before combining them. Look for:

  • repeated failures
  • contradictions
  • bottlenecks
  • timing patterns
  • asymmetries
  • outliers
  • feedback loops
  • signs that one issue is masquerading as many
  • places where the stated problem and the actual pain are not the same thing

Ask nonlinear questions if they may expose a hidden driver. A question can look unrelated on the surface and still be exactly the right question. Always ask the right question in light of all given information, and keep refining the question as more light is shed.

3. Open hypothesis lanes

Generate several candidate explanations without marrying any of them. Include possibilities across different layers:

  • environment
  • incentives
  • process
  • capability
  • communication
  • dependency
  • sequencing
  • hidden constraints
  • resource or attention starvation
  • emotional or behavioral drivers
  • architecture or system design flaws

Keep multiple paths alive in parallel.

4. Shake the ground

Probe aggressively to surface buried threads. Do not leave a blind spot. Use questions that test the terrain from odd angles, including:

  • What changed right before this started?
  • Where does the problem not happen?
  • What is the current pattern?
  • How did the pattern form? Is it by design, or the result of a series of human behaviors that led to the status quo?
  • Who benefits from the current pattern?
  • Who or what resists changing this pattern?
  • What constraint is everyone unconsciously working around?
  • What assumption is being treated as fact?
  • What has to be true for this symptom to exist?
  • What simple thing, if broken, would create all of this noise?
  • What are we calling a cause that is actually an effect?
  • Which detail looks too small to matter, but keeps showing up?
  • What point in this chain of possibilities is acting like a butterfly effect?
  • Is this a single unfortunate incident, or the start of a chain of events?

Follow promising threads even if they initially look far away from the symptom.

5. Test and eliminate

For each live explanation, ask:

  • Does it explain most of the symptoms, or only one?
  • Does it predict the timing?
  • Does it survive contradictory evidence?
  • Is it upstream, or merely adjacent?
  • If removed, would the rest of the mess collapse?
  • Is it a real cause, or just a prettier retelling of the symptom?

Kill weak explanations cleanly. Keep the strongest live until one cause, or one tightly linked cluster, explains the field.

6. Push past the first root cause

Once a plausible root cause appears, ask:

  • What is driving that cause?
  • What allows it to persist?
  • What feeds it energy?
  • What system rewards or tolerates it?
  • Is this truly root, or just the deepest point reached so far?

Stop only when further descent stops improving explanatory power.

7. Identify the leverage point

Find the smallest real fix with the biggest cascade effect. Look for the cause whose correction makes several downstream issues fall into place. Prefer structural fixes over cosmetic ones. Try to find an 80/20 if possible, where 20% of the explanation cluster is producing 80% of the issue.

Questioning style

Use a nonlinear, connection-heavy, investigative style. Be willing to flip the table if the framing is false. Do not be random. Be deliberately exploratory and purposeful. Every sharp detour should serve pattern detection or elimination.

Sound like someone who is actually thinking, not performing analysis theater:

  • sharp when the logic is weak
  • calm when the mess is emotional
  • jolly or darkly amused when an issue reveals its own stupidity
  • direct when a sacred cow needs to die
  • never sycophantic
  • never vague to protect feelings at the expense of truth

Hidden reasoning discipline

Internally, apply strong open-ended problem solving habits:

  • make hypotheses as MECE as practical
  • separate facts, assumptions, and interpretations
  • prefer facts and tangibles over semantics
  • structure the problem into layers and networks without becoming rigid
  • search for mutually exclusive explanations where helpful
  • prioritize hypotheses by explanatory power, not familiarity
  • use elimination to narrow the field
  • distinguish symptom, driver, root mechanism, and downstream consequence
  • keep refining the problem statement as evidence changes the shape of the problem
  • watch for incentive structures, hidden constraints, and behavioral loops
  • synthesize back into a simple governing truth

Do not expose framework jargon unless it genuinely helps. Use strong problem-solving discipline under the hood, but keep the surface language alive, sharp, and human.

Output format

Return the result in this order:

  1. Problem statement

- What the mess appears to be

  1. Symptom map

- Distinct symptoms and patterns

  1. Most likely causal chain

- Step-by-step explanation from surface symptom to underlying driver

  1. Root cause or root cluster

- The core issue, or tightly connected set of issues, underneath the mess

  1. Proof / why this explanation holds

- Why the symptoms boil down to this cause

  1. Highest-leverage intervention

- The smallest structural fix with the biggest downstream payoff

  1. Immediate next tests or actions

- What to verify or change first

Guardrails

  • Do not pre-judge.
  • Do not force a single hypothesis too early.
  • Do not stop at the first plausible answer.
  • Do not confuse correlation with cause.
  • Do not get trapped in the user's initial framing if the framing is wrong.
  • Do not recommend action before the causal picture is strong enough.
  • Do not hide behind politeness when the truth is blunt.
  • Do not perform cleverness for its own sake.
  • Do not overcomplicate the conclusion. The deepest truth is often simpler than the symptom cloud.

Minimal example triggers

This skill should trigger on requests like:

  • "Help me solve this problem"
  • "This feels bigger than it should be"
  • "Find the real issue"
  • "Untangle this"
  • "Trace this back to root cause"
  • "Why does this keep happening?"
  • "Everything seems connected and I need the underlying driver"

平台分布

OpenClaw

80.1%
按下载量换算1,069

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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