Skill Post Scorer

Q: What does the Skill Post Scorer AI skill do?

对社媒帖子草稿进行互动潜力评分，基于历史表现数据输出结构化评分卡。 当用户说"帖子打分""评分""这条能火吗""发布前评估""内容质量分""评分卡""草稿评估"时使用。 和 skill-topic-evaluator 的区别：evaluator 评还没做的选题潜力，本 SKILL 评已写好的草稿质量； 和 skill-social-performance-review 的区别：本 SKILL 评单条草稿（发布前），review 做月度组合复盘（发布后）。

Q: Why use Skill Post Scorer on TypingMind?

Because you install it once and use it with any model. Skill Post Scorer 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.

Q: How do I install Skill Post Scorer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-post-scorer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Q: Which AI models can use Skill Post Scorer?

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.

Q: How many AI models can I use with Skill Post Scorer?

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

Q: Is the Skill Post Scorer AI skill free?

Yes. It is published on GitHub by ZJU-REAL under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

Q: 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.

Q: 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.

OrganizationPopular

ZJU-REAL

skill-post-scorer

对社媒帖子草稿进行互动潜力评分，基于历史表现数据输出结构化评分卡。当用户说"帖子打分""评分""这条能火吗""发布前评估""内容质量分""评分卡""草稿评估"时使用。和 skill-topic-evaluator 的区别：evaluator 评还没做的选题潜力，本 SKILL 评已写好的草稿质量；和 skill-social-performance-review 的区别：本 SKILL 评单条草稿（发布前），review 做月度组合复盘（发布后）。

Overview

Publisher	ZJU-REAL
Repository	`Easel`
Skill name	`skill-post-scorer`
Stars	3.5K
Forks	535
Bundled files	4
License	Apache-2.0
Links	Skill source Repository Homepage

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.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by ZJU-REAL on GitHub. Read the source before you install it.

Installation

Install the Skill Post Scorer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-post-scorer
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.

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/ZJU-REAL/Easel.git /tmp/Easel
mkdir -p .claude/skills
cp -r /tmp/Easel/skills/openclaw/skill-post-scorer .claude/skills/skill-post-scorer

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Post Scorer 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 Skill Post Scorer 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 Skill Post Scorer 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.

帖子表现评分

对社媒帖子草稿进行互动潜力评分，基于历史表现数据输出结构化评分卡。

加载后立即开始评分流程，不做摘要或等待确认。

输入

用户 prompt 中提供待评分的帖子草稿，支持以下形式：

文本内容：直接粘贴帖子文案
文件路径：指向 outputs/ 中的草稿文件
平台指定：可选，指定目标平台（小红书、抖音、微博、知乎、公众号、B站等）

示例 prompt：


Execute /skill-post-scorer
帖子：
我花了3年时间才明白一个道理：
最好的内容不是"写"出来的，而是"提炼"出来的。
以下是我总结的5个内容提炼方法...

输出

输出代码块格式的评分卡：


━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
帖子表现评分卡
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
钩子强度        ██████████  8/10
声音匹配度      ███████░░░  7/10
价值密度        ████████░░  8/10
结构与格式      ███████░░░  7/10
发布就绪度      ██████░░░░  6/10
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
总分            36/50
判定            值得发布，建议优化钩子
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

改进建议：
1. [最弱维度] 具体修改建议
2. ...

执行步骤

第一步：获取帖子

读取用户粘贴的帖子内容。如果 prompt 中没有帖子文本，主动询问用户提供。

第二步：加载评分数据

按优先级获取表现数据：

Profile 中的历史数据：检查 === EASEL ACCOUNT PROFILE === 标记，读取 performance_data 路径指向的历史帖子数据
用户提供数据：询问用户是否有历史帖子导出数据（各平台创作者中心/后台可导出 CSV/Excel，或整理成 JSON 数组）
通用基准：以上都没有时，使用 references/fallback-benchmarks.md 中的基准数据

第三步：分析高表现帖子

互动分与 Top 10% 筛选交给脚本，LLM 只做特征提炼。 由 scripts/score.py 完成（复用 ../../shared/scripts/social_stats.py 的 engagement_score）。

有历史/用户数据时，把帖子整理成 JSON 数组（每条含点赞与评论字段），调用：

bash
python3 skills/openclaw/skill-post-scorer/scripts/score.py top --input history.json
python3 skills/openclaw/skill-post-scorer/scripts/score.py top --input history.json --top-pct 5

脚本自动：按 互动分 = 点赞 + 评论×3 逐条计算（字段兼容 likes/reactions/点赞、 comments/评论）、按互动分降序、算出 Top N% 门槛与分布（均值/中位数/最高/最低）、样本量不足警告。LLM 拿到脚本输出的 Top 帖子后，提取其共性特征：

开头钩子类型（提问、数据、故事、反常识）
文本长度和段落节奏
格式特征（列表、分隔、emoji 使用）
行动号召（CTA）类型
主题分类
句式节奏（长短交替、断句频率）

无历史数据时跳过本步，直接用 references/fallback-benchmarks.md 的通用模式特征。

第四步：五维评分

按 5 个维度打分，每项 1-10 分，总分 50 分。

评分标准详见 references/scoring-criteria.md。

维度	评判重点
钩子强度	前两句是否能阻止滑动，制造好奇或共鸣
声音匹配度	是否契合账号一贯的语气、人设和表达习惯
价值密度	每段是否提供具体洞察，而非空泛陈述
结构与格式	排版是否适配目标平台的阅读习惯
发布就绪度	能否直接发布，还是需要润色或补充

评分纪律：

诚实评分，不做讨好
除非帖子确实匹配 Top 10% 的模式特征，否则不给 8 分以上
有真实数据时用数据说话，没有时明确标注"基于通用基准"

第五步：输出评分卡

按照上方「输出」部分的格式输出评分卡，包含：

五维分数（含进度条可视化）
总分和判定结论
针对最弱维度的具体改进建议

判定标准：

40-50：优秀，直接发布
30-39：值得发布，建议优化标注的弱项
20-29：需要修改，重点改进最弱的 1-2 个维度
< 20：建议重写

更细分档（含各边界档的判定措辞）见 references/fallback-benchmarks.md，两处口径一致。

第六步：提供改写服务

输出评分卡后，主动提出：

是否需要我改写得分最低的部分？

如果用户同意，针对最弱维度进行定向改写，保留其他部分不变，改写后重新评分对比。

Profile 感知

有 Profile

读取 voice / tone 字段，作为「声音匹配度」的评判标准
读取 platform 字段，调整「结构与格式」的平台适配规则
读取 performance_data 字段指向的历史数据文件，用真实数据替代通用基准
读取 topics / niche 字段，评估内容是否在账号定位范围内

无 Profile

「声音匹配度」退化为通用可读性评估
「结构与格式」使用通用社媒最佳实践
使用 references/fallback-benchmarks.md 中的基准数据
评分卡末尾附注："如提供账号 Profile（含历史表现数据），评分将更精准"

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 Skill Post Scorer AI skill do?

Why use Skill Post Scorer on TypingMind?

Because you install it once and use it with any model. Skill Post Scorer 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 Skill Post Scorer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-post-scorer. 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 Skill Post Scorer?

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 Skill Post Scorer?

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

Is the Skill Post Scorer AI skill free?

Yes. It is published on GitHub by ZJU-REAL under the Apache-2.0 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

帖子表现评分

输入

输出

执行步骤

第一步：获取帖子

第二步：加载评分数据

第三步：分析高表现帖子

第四步：五维评分

第五步：输出评分卡

第六步：提供改写服务

Profile 感知

有 Profile

无 Profile

Bundled files

Frequently asked questions

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