Agent skill

WeChat Article Topics and Titles

by aiworkskills in aiworkskills/wechat-article-skills

Researches topics, titles, digests and series plans for WeChat Official Account articles; used on its own only to revise titles or digests that already exist.

Apache-2.0Auto-check passedWriting & Content

SKILL.md written in Chinese; this summary is our English description.

Install WeChat Article Topics and Titles

skills CLI
$ npx skills add aiworkskills/wechat-article-skills --skill aws-wechat-article-topics -a claude-code

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

GitHub CLI
$ gh skill install aiworkskills/wechat-article-skills aws-wechat-article-topics --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/aiworkskills/wechat-article-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/aws-wechat-article-topics .claude/skills/aws-wechat-article-topics && 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
aws-wechat-article-topics
GitHub stars
672
Token cost
~1.3k tokens
SKILL.md length
226 words
Files
6 (incl. references)
Skills in repo
9
Repo updated
First seen
Licence
Apache-2.0

At a glance

Researches topics, titles, digests and series plans for WeChat Official Account articles; used on its own only to revise titles or digests that already exist.

  • Works in 5 steps: 文章目录:main 已建好目录且内含 article.yaml →… → 选题卡片 → topic-card.md → 调研摘要 → research.md → …
  • Rewriting the title of a WeChat article that already has a draft
  • SKILL.md covers 能力披露(Capabilities), 路由, 配置检查 ⛔ and 四种输入模式, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

This skill supports editors and content operators who run a WeChat Official Account. It covers hot-topic research, topic planning, headline writing, digest writing and scheduling a series of articles. Used by itself it is meant only for changing an existing title or digest, such as asking for a new headline or a rewritten summary; new topics, series plans, trend chasing and any multi-stage job from writing to publishing are handed to the suite's main skill, `aws-wechat-article-main`.

Each request is sorted into one of four input modes: a specific topic, a field without a topic, no direction at all, or a series or column plan. The skill runs a setup check first, then confirms that `article_category`, `target_reader` and `default_author` are filled in `.aws-article/config.yaml`, asking you for any that are missing and never copying them from drafts. Research uses web search and page fetches with different goals per mode, and results are saved as files such as `topic-card.md`, `research.md` and a series `plan.md`.

It needs no credentials and calls no interface that requires one; checking already published articles needs WeChat credentials and belongs to the publish skill. The only shell step is a local script, `article_init.py`, that writes YAML. Reference files cover branches, output format, research strategy and title presets. The skill is one of a nine-skill suite that is meant to be installed together, and its text is in Chinese.

When your agent uses it

  • Rewriting the title of a WeChat article that already has a draft
  • Improving the digest of an existing WeChat article
  • Planning a topic or a series for a WeChat Official Account, via the suite's main skill

Example prompts

  • “Rewrite the title of this article, I want something less clickbait.”
  • “The digest feels flat. Rewrite it for our account's target readers.”
  • “Give me a few new headline options for the AI agents article in topic-card.md.”

Requirements

  • `.aws-article/config.yaml` with `article_category`, `target_reader` and `default_author`
  • Web search and page fetch available in the host agent
  • Python for the local `article_init.py` helper

Workflow steps

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

  1. 文章目录:main 已建好目录且内含 article.yaml → 不要改目录名,直接往里写。否则创建 {drafts_root}/{YYYYMMDD}-{标题slug}/(drafts_root / series_root 以 config.yaml 为准)。
  2. 选题卡片 → topic-card.md
  3. 调研摘要 → research.md
  4. 系列模式:系列规划 → {series_root}/{系列slug}/plan.md
  5. article.yaml:同目录若无、或已定题信息需更新,本步必须创建或补全(publish_completed: false;标题、摘要与用户选定一致时写入)

What it can do on your machine

Read from SKILL.md and the folder at commit ca036f7. 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 (its code samples are bash).

    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

WeChat Article Topics and Titles loads about 1.3k tokens when it runs, and up to ~4.7k if it reads all its reference files. Until then it costs about 68 tokens; SKILL.md has 226 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.7k

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 aiworkskills/wechat-article-skills at commit ca036f7, republished under its Apache-2.0 licence (© aiworkskills). 226 words, ~1,250 tokens.

Download SKILL.mdSave it as .claude/skills/aws-wechat-article-topics/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
aws-wechat-article-topics
description
公众号选题|爆款标题|热点追踪|系列策划 — 公众号 AI 选题与标题生成,覆盖热点调研、选题策划、起标题、写摘要、系列排期。面向自媒体编辑、内容运营。触发词(**单独触发仅限对已有标题/摘要的修改**):「改标题」「换个标题」「重起标题」「优化标题」「标题再想想」「换个标题试试」「改摘要」「重写摘要」「优化摘要」「摘要再优化下」。新做选题、起新标题、策划系列/内容日历、追热点都请走 aws-wechat-article-main;需要多环节串联(写+审+排+配图+发)也走 main。
homepage
https://aiworkskills.cn
url
https://github.com/aiworkskills/wechat-article-skills

选题与标题

公众号选题 & 爆款标题 AI 助手 —— 热点追踪、选题调研、起标题、写摘要、系列排期一次搞定。

套件说明 · 本 skill 属 aws-wechat-article-* 一条龙套件(共 9 个 slug,入口 aws-wechat-article-main)。跨 skill 的相对引用依赖同一 skills/ 目录,建议一并 clawhub install 全套。源码:https://github.com/aiworkskills/wechat-article-skills

能力披露(Capabilities)

本 skill 主要由 Agent 驱动(对话式选题调研、标题生成),脚本层只用于更新本篇元数据。

  • 凭证:无
  • 网络:Agent 可能使用 web_search / web_fetch(宿主内置能力,非本 skill 脚本层发起)。本 skill 不调任何需要凭证的接口——查已发布文章要微信凭证,那是 publish 的事
  • 文件读:.aws-article/config.yaml、本篇 article.yaml、.aws-article/products/{产品名}/*.md(选题涉及用户业务时必读)
  • 文件写:本篇目录下 topic-card.md、research.md、article.yaml;系列模式下 {series_root}/{系列slug}/plan.md
  • shell:只可能调 {python} {baseDir}/../aws-wechat-article-publish/scripts/article_init.py(纯本地写 YAML,不联网)

路由

要成文并发到公众号、或「今天发什么」需整条编排 → aws-wechat-article-main。本 skill 单独触发仅限已有标题/摘要的修改。

配置检查 ⛔

任何操作前先按 首次引导 · 检测顺序 执行,通过后才继续(或用户明确书面确认「本次不检查」)。

四种输入模式

模式触发条件示例
A. 明确选题用户给了具体话题「写一篇 AI Agent 的文章」
B. 有方向给了领域但没具体题目「AI 最近有什么好写的」
C. 无方向只说要选题「这周写什么」「帮我找几个选题」
D. 系列策划提到系列/专栏/连载「做个 AI 入门系列」「写 10 篇专栏」

工作流

选题进度:
- [ ] 第1步:⛔ 配置检查
- [ ] 第2步:⛔ 全局账号三键
- [ ] 第3步:⛔ 归类 A/B/C/D(先于任何联网调研)
- [ ] 第4步:调研
- [ ] 第5步:生成选题
- [ ] 第6步:生成标题与大纲
- [ ] 第7步:⛔ 展示并等用户选
- [ ] 第8步:落盘(topic-card.md + research.md + article.yaml)

一条龙下哪几步可以省、单独使用时要补什么,见 branches.md「一」。

第2步:全局账号三键 ⛔

在调用 web_search、调研或与用户确认方向之前,打开 .aws-article/config.yaml,检查 article_category、target_reader、default_author 是否 trim 后均非空。任一项缺失:逐项询问用户,取得当轮明确答复后写回该文件。

禁止从 article.yaml 或其它草稿擅自抄录填充。与 main「2) 全局账号约束」 一致。

第3步:归类 A/B/C/D ⛔

在联网调研之前先与用户对齐:是已有具体主题、只有大致领域、完全没想法,还是要做系列/专栏。

用户本条消息已说清(直接给出话题、或明确说「这周帮我找几个选题」)→ 简短确认即可,不必重复盘问。

禁止:用户仍处于「只说找选题、没说领域/偏好」的模糊状态时就开始联网调研——搜出来的东西没有收敛方向,只会浪费一轮。

第4步:调研

先读 .aws-article/config.yaml:选题边界、topic_direction、update_frequency、账号定位以它为准。本篇目录已有 article.yaml(例如已定题)时一并读 title / digest,避免与后序冲突。

选题涉及用户自身业务时须读业务资料库,口径见 branches.md「三」。

用 web_search 搜 + web_fetch 深读,为选题提供数据支撑:

模式调研目标
A竞品文章怎么写、数据支撑、独特角度
B该方向近期热点、读者关注什么
Cconfig.yaml 的账号定位、topic_direction 与近期热点
D知识体系拆解、竞品系列分析、读者学习路径

各模式的搜索策略与搜索词模板见 references/research-strategy.md。

第5步:生成选题

数量用 config.yaml 的 update_frequency 控制:周更约 3–5 个,日更略多,月更略少;无配置时按对话约定。

模式生成规则
A围绕用户主题,给 3-4 个不同切入角度
B/C筛 3-5 个选题,标类型(🔥热点 / 🌲常青 / 📚系列)
D规划系列总线 + 拆出每篇选题(见 branches.md「四」)
第6步:生成标题与大纲

每个选题出一张选题卡片:标题候选(3-5 个,混合风格)、切入角度、大纲预览、工作量评估、摘要候选。输出模板见 references/output-format.md。

标题风格的加载优先级与多候选收敛规则见 branches.md「二」;内置 5 种风格(悬念/干货/数字/反问/故事)见 references/title-presets.md。

摘要候选要能独立成立:它会进 article.yaml 的 digest,显示在后台文章列表里。别写成正文开头那段的复述——正文首个 > 导语是另一段文字,两者逐字相同的话读者等于同一段读两遍(review 会拦这一条)。

第7步:展示并等用户选 ⛔

必须停下来等用户操作。 展示所有选题卡片后提示:

请选择:
- 输入编号(如 1)→ 选定该选题
- 「调整 + 意见」→ 按意见修改后重新展示
- 「重新选」→ 换一批选题
- 「组合 1+3」→ 融合多个选题
- 系列模式:「先写第 N 篇」→ 按该篇进入写稿

禁止:不等用户选就继续写稿;假设用户会选某一个;跳过展示直接进下一步。

第8步:落盘

用户确认后:

  1. 文章目录:main 已建好目录且内含 article.yaml → 不要改目录名,直接往里写。否则创建 {drafts_root}/{YYYYMMDD}-{标题slug}/(drafts_root / series_root 以 config.yaml 为准)。

  2. 选题卡片 → topic-card.md

  3. 调研摘要 → research.md

  4. 系列模式:系列规划 → {series_root}/{系列slug}/plan.md

  5. article.yaml:同目录若无、或已定题信息需更新,本步必须创建或补全(publish_completed: false;标题、摘要与用户选定一致时写入):

    bash
    {python} {baseDir}/../aws-wechat-article-publish/scripts/article_init.py <本篇目录> --title "…" --digest "…"

→ 交给 aws-wechat-article-writing。须已具备 .aws-article/config.yaml,本篇目录建议已有 article.yaml。

分支与细则

一条龙 vs 单独使用、预设候选池收敛、业务资料库、系列策划、文末推荐链接归谁做 → references/branches.md。

过程文件

文件说明
.aws-article/config.yaml全局账号与选题/文风约束;选题全程以之为准
article.yaml本篇元数据与 publish_completed;新建本篇须 false
topic-card.md选题卡片(标题、摘要、角度、大纲)
research.md调研摘要(搜索发现、竞品分析、数据点)

© aiworkskills, 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/aws-wechat-article-topics of aiworkskills/wechat-article-skills.

  • SKILL.md
  • references/branches.md
  • references/output-format.md
  • references/research-strategy.md
  • references/title-presets.md
  • skill.json

Open the folder on GitHubat commit ca036f7

Compare with similar skills

WeChat Article Topics and Titles 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.

WeChat Article Topics and Titles compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
WeChat Article Topics and Titles this skillaiworkskills/wechat-article-skills672—~1.3kAutomated safety check: PassApache-2.0
WeChat Account Topic and Title WriterBigPengSays/bigpeng-hot-gzh266—~501Automated safety check: PassMIT
WeChat Article Title Strategistliucongg/liucong-skills248—~471Automated safety check: PassApache-2.0
Money Contentiamzifei/show-me-the-money1k—~9.6kAutomated safety check: PassCustom licence
37 Social Caption Globalminhnv0807/ai-business-skills609—~2.2kAutomated safety check: PassMIT
Social Media Pro Maxcriptogus/agent-evolve-network288—~1.6kAutomated safety check: PassCustom licence

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Works with

Questions about WeChat Article Topics and Titles

What does WeChat Article Topics and Titles do?

Researches topics, titles, digests and series plans for WeChat Official Account articles; used on its own only to revise titles or digests that already exist. This skill supports editors and content operators who run a WeChat Official Account. It covers hot-topic research, topic planning, headline writing, digest writing and scheduling a series of articles.

When should I use WeChat Article Topics and Titles?

WeChat Article Topics and Titles fits situations like: rewriting the title of a WeChat article that already has a draft; improving the digest of an existing WeChat article; planning a topic or a series for a WeChat Official Account, via the suite's main skill.

How do I install WeChat Article Topics and Titles in Claude Code?

Run `npx skills add aiworkskills/wechat-article-skills --skill aws-wechat-article-topics -a claude-code`. Or copy the skill folder (skills/aws-wechat-article-topics in aiworkskills/wechat-article-skills) into .claude/skills/aws-wechat-article-topics in your project. Claude Code loads it when a task matches its description.

How do I install WeChat Article Topics and Titles in Codex?

Run `npx skills add aiworkskills/wechat-article-skills --skill aws-wechat-article-topics -a codex`. Or copy the skill folder (skills/aws-wechat-article-topics in aiworkskills/wechat-article-skills) into .agents/skills/aws-wechat-article-topics in your project. Codex loads it when a task matches its description.

Can I use WeChat Article Topics and Titles 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 aiworkskills/wechat-article-skills --skill aws-wechat-article-topics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aws-wechat-article-topics, .gemini/skills/aws-wechat-article-topics, .github/skills/aws-wechat-article-topics and .opencode/skills/aws-wechat-article-topics in your project.

What does WeChat Article Topics and Titles need to run?

SKILL.md names no scripts, command-line tools or credentials: WeChat Article Topics and Titles is instructions for the agent only. Our summary lists: `.aws-article/config.yaml` with `article_category`, `target_reader` and `default_author`; Web search and page fetch available in the host agent; Python for the local `article_init.py` helper.

Does WeChat Article Topics and Titles 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 WeChat Article Topics and Titles 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 WeChat Article Topics and Titles use?

WeChat Article Topics and Titles 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 WeChat Article Topics and Titles use?

About 1.3k tokens (SKILL.md is roughly 5k 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 3.5k tokens, read only when the agent opens those files.

What are the alternatives to WeChat Article Topics and Titles?

Skills that share tags, products or a category with WeChat Article Topics and Titles: WeChat Account Topic and Title Writer (BigPengSays/bigpeng-hot-gzh, 266 stars), WeChat Article Title Strategist (liucongg/liucong-skills, 248 stars), Money Content (iamzifei/show-me-the-money, 1k stars) and 37 Social Caption Global (minhnv0807/ai-business-skills, 609 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains WeChat Article Topics and Titles?

aiworkskills (a GitHub user) maintains it in aiworkskills/wechat-article-skills, which has 672 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 23, 2026.

Source: aiworkskills/wechat-article-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.