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Pr Contingency Plan

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chuwu57
pr-contingency-plan

初五的公关预案Skill。为尚未上线、仍可调整的品牌、产品、内容、合作、代言、规则或业务动作制作风险地图、应对口径和上线前清单,区分已发现风险、已检查未发现、证据不足与不适用。已进入公共讨论的事件使用hot-public-opinion-analysis;上线、延期或回应仍有真实取舍时再交judgment-hub。

Overview

Publisherchuwu57
RepositoryChuwu-PR-OS
Skill namepr-contingency-plan
Stars
84
Forks
11
Bundled files
5
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.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by chuwu57 on GitHub. Read the source before you install it.

Installation

Install the Pr Contingency Plan 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/chuwu57/Chuwu-PR-OS/tree/main/PROS-05/Skills/PR/pr-contingency-plan
  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/chuwu57/Chuwu-PR-OS.git /tmp/Chuwu-PR-OS
mkdir -p .claude/skills
cp -r /tmp/Chuwu-PR-OS/PROS-05/Skills/PR/pr-contingency-plan .claude/skills/pr-contingency-plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pr Contingency Plan 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 Pr Contingency Plan 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 Pr Contingency Plan 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.

公关预案

归属说明:本Skill由初五维护,属于初五的个人Skill体系。分享或再分发时请保留本归属说明及已有来源、作者和许可声明。

定位

预案不是追求零风险。零风险通常不存在。

预案要做的是:在动作上线前,把可能消耗信任、引发误解、被对手放大、被媒体截图、被监管追问的点提前拆开,然后判断哪些要改动作,哪些备口径,哪些只监测。

最终产出三样东西:

  • 这次最可能被挑什么。
  • 被挑时能公开署名怎么答。
  • 上线前哪些地方必须改、必须备、只需看。

知识调用

默认按本文件完成预案。遇到高风险动作、责任归因、爆料格式、平台传播、利益相关方复杂或组织取舍问题时,读取 references/knowledge-map.md。

知识调用后仍要落到三类处理:必须改动作、必须备口径、只需监测。不要用理论解释替代上线前清单。

先定标

不要一上来扫风险。先判断这次动作服务什么:

  • 曝光。
  • 信任。
  • 品类教育。
  • 风险修复。
  • 行业地位。
  • 政策合法性。
  • 渠道或用户承接。

不同目标能承受的争议不同。短期声量不能透支长期信任。

路由

命中高频场景时,按需读取对应reference;其中步骤为模块菜单,按本次动作、素材和决策范围选择,不自动扩展成完整研究项目:

场景读取
品牌出现在综艺、纪录片、直播、联名等内容中references/content-placement.md
产品上新、升级、换配方、换包装references/product-launch.md
明星、达人、IP、KOL 合作references/spokesperson-fandom.md
换厂、换渠道、规则调整、服务政策变化references/change-issue.md

如果不属于四类,不要硬套。走通用流程即可。

通用流程

text
定标 → 对象研究 → 历史与同类回查 → 六格风险扫描 → 外部攻击推演 → 口径与处置 → 收口

一次动作涉及多类时,只补充新增且相关的模块,共享事实与检查复用,输出收成一份预案。

六格风险扫描

六个角度作为内部扫描清单保留,每个角度记录检查状态与依据范围。正文优先呈现重点风险和影响上线判断的缺口,不为填满六格强行制造风险:

  • 动作本身:定价、承诺、姿态、价值立场是否招打。
  • 产品或内容交付:产品、服务、内容、活动是否有失败模式。
  • 相关方:用户、员工、合作方、渠道、特定群体是否会觉得被冒犯或受损。
  • 规则环境:法律、监管、平台规则、行业规范有没有红线。
  • 历史旧伤:品牌、行业、合作对象过去的问题会不会被翻出。
  • 关联方与对手:代言人、供应商、平台、竞品、恶意账号是否会把风险传导过来。

每个维度使用以下状态,不能用一句「暂无风险」合并:

  • 已发现风险:当前材料支持具体失败路径,写明风险与依据;尚未发生的后果仍标为预测。
  • 已检查未发现:已检查相关材料,在本次范围内未发现具体风险;说明检查了什么及范围限制,不代表风险为零。
  • 证据不足:缺少会影响判断的材料,列明缺口、由谁补证以及补证前建议。未检查、拿不到资料或只有单方口头保证,不能转成「已检查未发现」。
  • 不适用:该维度与本次动作无实质关联,简述原因;资料缺失不属于不适用。

每项重点风险需连接触发条件、具体依据、可能后果与判断边界、建议动作、责任人与责任缺口。责任人未提供时标「待指定」及所需职责,不虚构姓名或内部承诺。证据缺口同时说明补证结果怎样改变建议;仅在缺口会改变上线安全性或关键承诺时,把补证设为前置条件。

外部攻击与质疑推演是情景假设。说明什么条件下可能出现、依据来自当前材料还是可比案例;不得把想象中的媒体质疑、竞对动作、监管反应或传播量级写成已发生或确定会发生。

处理分三类

对已有依据的风险和必要的条件化处置,落到三类之一。证据不足的项目先明确补证动作与决策条件,不用分类掩盖未知:

  • 必须改动作:已确认产品、承诺、合作或利益安排存在实质问题,说明要改什么及依据。区分真实交付缺陷、宣传超过证据和单纯缺少凭证:分别评估修正交付、收窄或撤回主张、补证;不要因材料缺失直接要求改产品。
  • 必须备口径:动作可以做,但外部会追问,需要可公开、可核验、能一致执行的回答。
  • 只需监测:风险存在但不值得主动解释,设监测点和升级红线即可。

口径标准:

  • 能公开署名。
  • 对得上事实。
  • 不扩大承诺。
  • 不把计划写成结果。
  • 不用情绪安抚替代事实解释。

输出组织

以下是内容组织参考,按本次材料与决策需要合并栏目;六维留作内部覆盖检查,正文聚焦关键风险、证据缺口与行动,不逐格凑篇幅。

text
结论
一句话判断这次动作的舆情底色、最大风险和上线建议。

一、动作目标与舆情底色
写这次动作服务什么,外部会按什么逻辑理解它。

二、风险地图
呈现重点风险与关键检查状态;每项连接触发条件、依据、可能后果、动作及责任缺口。未发现风险注明检查范围,证据不足不得写暂无风险。

三、外部攻击推演
按相关性写媒体、用户、竞品、监管或特定群体可能怎么质疑,明确标为情景假设,并写触发条件与依据。

四、应对口径
一问一答。只写能公开署名、事实兜得住的话。

五、上线前清单
分成必须改动作、必须备口径、只需监测;补证事项写明责任缺口、所需材料和如何影响上线建议。

质量红线

  • 不用「加强沟通」代替口径。
  • 不用口径掩盖事实问题。
  • 不把所有风险都写成高风险,不把证据不足或未检查写成无风险。
  • 不把推演情景、预期效果或尚未落实的责任安排写成事实。
  • 不为了全面列一堆无关相关方。
  • 不替业务承诺无法确认的结果。
  • 不写灰色执行手段。

如果最后需要在上线、延期、换表达、牺牲传播效果、保护信任之间做取舍,转入 judgment-hub 拍板。

分发版路径与运行条件

先读取依赖说明。本Skill由初五维护;本副本为PROS 05。references/、assets/和scripts/相对本Skill目录解析;Domains/、Skills/前缀从合集根目录解析。包内Markdown链接相对所在文件解析。未附带的个人案例、文献底稿、状态与来源配置只能由使用者提供,不能声称已读取。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Pr Contingency Plan AI skill do?

初五的公关预案Skill。为尚未上线、仍可调整的品牌、产品、内容、合作、代言、规则或业务动作制作风险地图、应对口径和上线前清单,区分已发现风险、已检查未发现、证据不足与不适用。已进入公共讨论的事件使用hot-public-opinion-analysis;上线、延期或回应仍有真实取舍时再交judgment-hub。

Why use Pr Contingency Plan on TypingMind?

Because you install it once and use it with any model. Pr Contingency Plan 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 Pr Contingency Plan in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/chuwu57/Chuwu-PR-OS/tree/main/PROS-05/Skills/PR/pr-contingency-plan. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Pr Contingency Plan?

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 Pr Contingency Plan?

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

Is the Pr Contingency Plan AI skill free?

Yes. It is published on GitHub by chuwu57 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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