Agent skill

Skill Community Ops

by ZJU-REAL in ZJU-REAL/Easel

评论区运营与舆情危机应对:为一批评论生成分层回复模板(赞美/提问/求购/杠精/黑粉) 与分级处理规则,从评论中挖掘选题反哺内容,负面事件时做危机分级 + 声明草稿 + 统一口径。

Apache-2.0Auto-check passedTesting & QA

Install Skill Community Ops

skills CLI
$ npx skills add ZJU-REAL/Easel --skill skill-community-ops -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ZJU-REAL/Easel skill-community-ops --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/openclaw/skill-community-ops .claude/skills/skill-community-ops && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
skill-community-ops
GitHub stars
3.4k
Token cost
~700 tokens
SKILL.md length
183 words
Files
6 (incl. references)
Skills in repo
114
Repo updated
First seen
Licence
Apache-2.0

At a glance

评论区运营与舆情危机应对:为一批评论生成分层回复模板(赞美/提问/求购/杠精/黑粉) 与分级处理规则,从评论中挖掘选题反哺内容,负面事件时做危机分级 + 声明草稿 + 统一口径。

  • Works in 5 steps: 读… → 每类给 2-3 条可套用的回复模板(用 [占位符]… → 按… → …
  • Tasks that involve Quality gates
  • SKILL.md covers 三种模式, 输入, 模式 A:评论回复策略 and 模式 B:评论区选题反哺, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Skill Community Ops is an agent skill from ZJU-REAL/Easel. 评论区运营与舆情危机应对:为一批评论生成分层回复模板(赞美/提问/求购/杠精/黑粉) 与分级处理规则,从评论中挖掘选题反哺内容,负面事件时做危机分级 + 声明草稿 + 统一口径。 当用户说"回复评论"、"评论区运营"、"评论怎么回"、"钓评论"、"引导互动"、 "评论区选题"、"舆情"、"危机公关"、"差评"、"黑粉"、"被骂了"、"道歉声明"、 "统一口径"、"负面缠上来了"、"翻车了怎么办"时触发。 和 skill-quality-gate 的区别:quality-gate 是发布前合规质检, community-ops 是发布后的评论互动与危机响应。

Its SKILL.md is about 700 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `EASEL-META.md`, `references/crisis-grading.md` and `references/platform-comment-ecology.md`).

It sits in Testing & QA, covering Quality gates. The repository describes itself as: An open-source AI agent for social media — discover trends, create content, publish everywhere, and learn what works across Xiaohongshu, Douyin, Zhihu, Bilibili, and more.🎨一个开源的… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Quality gates

Example prompts

  • “负面缠上来了”
  • “翻车了怎么办”
  • “/skill-community-ops”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. 读 references/reply-playbook.md「一、五类评论分层话术库」,按五类归类用户给的评论:普通赞美 / 专业提问 / 求购买求链接 / 杠精抬杠 / 黑粉恶意差评。
  2. 每类给 2-3 条可套用的回复模板(用 [占位符] 表示品牌名、产品、链接等,不写死具体 case)。
  3. 按 references/reply-playbook.md「二、分级处理规则」给出处置分级:必回 / 引导私信 / 置顶 / 冷处理 / 删除拉黑,并说明每条评论归入哪级、为什么。
  4. 按目标平台调语气:读 references/platform-comment-ecology.md 对应平台段(小红书亲和、B站梗感、知乎专业、抖音短平快、微博快节奏、公众号克制)。
  5. 输出:分类回复模板表 + 分级处置清单 + 平台语气提示。

What it can do on your machine

Read from SKILL.md and the folder at commit 278f420. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skill Community Ops loads about 700 tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 75 tokens; SKILL.md has 183 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
When it runs · the whole SKILL.md, loaded when a task matches
~700
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ZJU-REAL/Easel at commit 278f420, republished under its Apache-2.0 licence (© ZJU-REAL). 183 words, ~700 tokens.

Download SKILL.mdSave it as .claude/skills/skill-community-ops/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
skill-community-ops
description
评论区运营与舆情危机应对:为一批评论生成分层回复模板(赞美/提问/求购/杠精/黑粉) 与分级处理规则,从评论中挖掘选题反哺内容,负面事件时做危机分级 + 声明草稿 + 统一口径。 当用户说"回复评论"、"评论区运营"、"评论怎么回"、"钓评论"、"引导互动"、 "评论区选题"、"舆情"、"危机公关"、"差评"、"黑粉"、"被骂了"、"道歉声明"、 "统一口径"、"负面缠上来了"、"翻车了怎么办"时触发。 和 skill-quality-gate 的区别:quality-gate 是发布前合规质检, community-ops 是发布后的评论互动与危机响应。
layer
publish

评论区运营与舆情危机应对

发布后的运营层能力:回复评论、从评论挖选题、负面事件时分级响应。三种模式,命中哪个做哪个。

三种模式

模式触发场景核心产出
A 评论回复策略有一批评论要回 / 问"评论怎么回"分层回复模板 + 分级处理规则
B 评论区选题反哺问"评论区能挖什么选题" / 给了一堆评论3-5 条下一步选题建议
C 舆情危机应对出现负面事件、差评风波、被黑危机分级 + 声明草稿 + 统一口径 + 红线 + 时效

一次请求可能命中多个模式(如"评论区吵起来了,帮我回一下顺便看要不要出声明")。先判定模式,再按对应流程执行。若输入模糊,先问清"是要回评论、挖选题、还是处理负面"。

输入

字段必填说明
评论内容模式 A/B 必填一批真实评论,或"我这类内容常收到 XX 类评论"的场景描述
负面事件描述模式 C 必填发生了什么、在哪个平台、扩散到什么程度、有无实锤
目标平台推荐小红书 / 抖音 / B站 / 微博 / 公众号 / 知乎,决定调性
品牌人设/红线可选无 Profile 时可手动提供,用于定语气和口径

模式 A:评论回复策略

  1. 读 references/reply-playbook.md「一、五类评论分层话术库」,按五类归类用户给的评论:普通赞美 / 专业提问 / 求购买求链接 / 杠精抬杠 / 黑粉恶意差评。
  2. 每类给 2-3 条可套用的回复模板(用 [占位符] 表示品牌名、产品、链接等,不写死具体 case)。
  3. 按 references/reply-playbook.md「二、分级处理规则」给出处置分级:必回 / 引导私信 / 置顶 / 冷处理 / 删除拉黑,并说明每条评论归入哪级、为什么。
  4. 按目标平台调语气:读 references/platform-comment-ecology.md 对应平台段(小红书亲和、B站梗感、知乎专业、抖音短平快、微博快节奏、公众号克制)。
  5. 输出:分类回复模板表 + 分级处置清单 + 平台语气提示。

模式 B:评论区选题反哺

  1. 通读评论,按 references/topic-mining.md「一、评论聚类维度」聚类出高频诉求、重复疑问、争议点、许愿、吐槽。
  2. 统计每类出现的信号强度(高频 / 中频 / 零星但尖锐)。
  3. 按 references/topic-mining.md「二、评论转选题公式」把高价值聚类转成 3-5 条具体选题建议。
  4. 每条选题给:选题标题方向 + 来自哪条/哪类评论 + 为什么值得做 + 建议形式(图文/视频/合集)。
  5. 输出:评论聚类摘要 + 3-5 条选题建议卡。

模式 C:舆情 / 危机应对

  1. 读 references/crisis-grading.md「一、危机三级分级标准」,按事件性质、扩散度、是否有实锤、是否触及安全/法律/伦理底线,判定:🟢 可忽略 / 🟡 需回应 / 🔴 需正式声明。给出判定依据(命中了哪几条标准)。
  2. 按判定档位取对应产出:
    • 🟢 可忽略 → 给"不回应/轻回应"的判断理由 + 内部监测建议(盯什么信号会升级)。
    • 🟡 需回应 → 按 references/crisis-grading.md「三、回应话术框架」出评论区/私信回应话术草稿。
    • 🔴 需正式声明 → 按「四、正式声明结构」出声明草稿(含事实陈述、担责、措施、承诺四段)。
  3. 出「对外统一口径」:一句话核心立场 + 3-5 条 Q&A 应答口径,确保团队对外说法一致(references/crisis-grading.md「五、统一口径」)。
  4. 出「红线清单」:此次绝对不要做的动作(references/crisis-grading.md「六、危机红线」,如删评控评、甩锅、情绪化对线、大规模拉黑)。
  5. 出「响应时效建议」:按档位给黄金响应窗口(references/crisis-grading.md「七、响应时效」)。
  6. 输出:危机分级结论 + 话术/声明草稿 + 统一口径 + 红线清单 + 时效建议。

Profile 感知

有 Profile 时:

  • 读 preferences.md(要做的/不做的/合规底线)→ 回复语气与危机口径贴合品牌人设,不越红线。
  • 读 style.md / identity.md → 回复模板的用词、称呼、梗的尺度对齐账号风格。
  • 读 platforms.md → 自动确定主攻平台的评论调性,无需再问。
  • 危机口径遵守 preferences.md「合规底线」,声明不承诺做不到的事。

无 Profile 时:

  • 退通用模式,回复模板用中性友好语气,占位符留给用户填品牌信息。
  • 询问或默认目标平台,按平台通用调性走。
  • 危机应对用行业通用稳妥口径,末尾提示"提供 Profile 可让口径贴合品牌人设与红线"。

规则

  1. 模板一律用 [占位符],不写死具体品牌/产品/人名的 case。
  2. 危机分级必须给出判定依据,不能只给结论。
  3. 声明草稿只承诺能兑现的措施,不写空话套话,不做虚假承诺。
  4. 不建议任何删评控评、水军刷屏、恶意对线等违规或损害长期信任的动作。
  5. 回复与口径符合目标平台评论生态,不生搬其他平台调性。

© ZJU-REAL, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/openclaw/skill-community-ops of ZJU-REAL/Easel.

  • SKILL.md
  • EASEL-META.md
  • references/crisis-grading.md
  • references/platform-comment-ecology.md
  • references/reply-playbook.md
  • references/topic-mining.md

Open the folder on GitHubat commit 278f420

Compare with similar skills

Skill Community Ops next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skill Community Ops compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skill Community Ops this skillZJU-REAL/Easel3.4k—~700Automated safety check: PassApache-2.0
Feature Plannerserendipity1004/cc-feature-implementer176—~2.4kAutomated safety check: PassNone
Ccg Workflowfengshao1227/ccg-workflow5.9k—~2.3kAutomated safety check: PassMIT
Conducty Checkpointrobertbarclayy/conducty176—~1.5kAutomated safety check: PassMIT
Mission Plannerjdforsythe/forge151—~3.5kAutomated safety check: PassMIT
Quality Gate0xNyk/lacp305—~382Automated safety check: PassMIT

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Categories

Questions about Skill Community Ops

What does Skill Community Ops do?

评论区运营与舆情危机应对:为一批评论生成分层回复模板(赞美/提问/求购/杠精/黑粉) 与分级处理规则,从评论中挖掘选题反哺内容,负面事件时做危机分级 + 声明草稿 + 统一口径。. Skill Community Ops is an agent skill from ZJU-REAL/Easel.

When should I use Skill Community Ops?

Skill Community Ops fits situations like: tasks that involve Quality gates.

How do I install Skill Community Ops in Claude Code?

Run `npx skills add ZJU-REAL/Easel --skill skill-community-ops -a claude-code`. Or copy the skill folder (skills/openclaw/skill-community-ops in ZJU-REAL/Easel) into .claude/skills/skill-community-ops in your project. Claude Code loads it when a task matches its description.

How do I install Skill Community Ops in Codex?

Run `npx skills add ZJU-REAL/Easel --skill skill-community-ops -a codex`. Or copy the skill folder (skills/openclaw/skill-community-ops in ZJU-REAL/Easel) into .agents/skills/skill-community-ops in your project. Codex loads it when a task matches its description.

Can I use Skill Community Ops in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ZJU-REAL/Easel --skill skill-community-ops -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-community-ops, .gemini/skills/skill-community-ops, .github/skills/skill-community-ops and .opencode/skills/skill-community-ops in your project.

What does Skill Community Ops need to run?

SKILL.md names no scripts, command-line tools or credentials: Skill Community Ops is instructions for the agent only.

Does Skill Community Ops access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Skill Community Ops safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Skill Community Ops use?

Skill Community Ops is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skill Community Ops use?

About 700 tokens (SKILL.md is roughly 2.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.4k tokens, read only when the agent opens those files.

What are the alternatives to Skill Community Ops?

Skills that share tags, products or a category with Skill Community Ops: Feature Planner (serendipity1004/cc-feature-implementer, 176 stars), Ccg Workflow (fengshao1227/ccg-workflow, 5.9k stars), Conducty Checkpoint (robertbarclayy/conducty, 176 stars) and Mission Planner (jdforsythe/forge, 151 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Community Ops?

ZJU-REAL (a GitHub organization) maintains it in ZJU-REAL/Easel, which has 3,376 GitHub stars. The repository holds 114 skills in this directory. The repository was last updated on October 9, 2026.

Source: ZJU-REAL/Easel on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.