story-short-analyze:短篇网文拆文 skill for OpenClaw
What this skill does
短篇网文拆文。拆解爆款短篇小说(番茄短篇 / 故事会 / 知乎盐选 / 追妻 / 世情 / 重生 / 虐渣等通俗题材)的故事核、结构、情感线、反转设计、写作手法、共鸣层次。单一全量拆解管道:跑完 Stage 2-6 产出完整拆文报告,落盘到 拆文库/{书名}/,下游 story-short-write 同时读拆文报告 + 情节节点 + 写作手法 + 原文 + _meta.
The story-short-analyze:短篇网文拆文 skill is part of the Creative & Writing category — creative and writing skills for content, social posts, and media. You can install it on its own or alongside other creative & writing skills from the OpenClaw catalog.
How to install the story-short-analyze:短篇网文拆文 skill
The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:
- Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
- Open the in-app Skills panel.
- Search for
story-short-analyzeand click Install. - The skill activates automatically when an incoming message matches its description.
Install from the command line
If you already run the OpenClaw CLI, add the story-short-analyze:短篇网文拆文 skill with a single command:
openclaw skills add story-short-analyze
This pulls story-short-analyze from ClawHub and installs it into ~/.openclaw/skills/story-short-analyze/. Restart the OpenClaw gateway afterwards so the new skill is discovered.
How to use the story-short-analyze:短篇网文拆文 skill
Once installed, the story-short-analyze:短篇网文拆文 skill activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.
Turning video into a finished short
story-short-analyze:短篇网文拆文 works with video. Getting from there to something postable is a separate job: ViralMint — an open-source video pipeline — reframes to vertical, cleans the audio, cuts dead air, burns animated captions, and exports a version sized for TikTok, Reels, and Shorts.
It runs as an MCP server, so an OpenClaw agent can drive it from the same chat you already use: ask for a short, and the render comes back finished. See how to connect a video pipeline to your agent.
Manual install (advanced)
If you prefer manual installation:
- Click the Download skill .zip button above to grab
story-short-analyze-1.1.22.zipdirectly from our S3 mirror. - Unzip into
~/.openclaw/skills/story-short-analyze/(create the directory if it does not exist). - Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.
Frequently asked questions
How do I install story-short-analyze:短篇网文拆文?
Install story-short-analyze:短篇网文拆文 in the OpenClaw Easy desktop app by opening the Skills panel, searching for story-short-analyze, and clicking Install. From a terminal you can run: openclaw skills add story-short-analyze. Either way the skill is placed in ~/.openclaw/skills/story-short-analyze/.
Is the story-short-analyze:短篇网文拆文 skill free?
Yes. It is free to download and run through ClawHub, with no account or payment required. Each skill is published by its own author under its own licence — see its ClawHub page for the licence and source.
What does story-short-analyze:短篇网文拆文 do?
短篇网文拆文。拆解爆款短篇小说(番茄短篇 / 故事会 / 知乎盐选 / 追妻 / 世情 / 重生 / 虐渣等通俗题材)的故事核、结构、情感线、反转设计、写作手法、共鸣层次。单一全量拆解管道:跑完 Stage 2-6 产出完整拆文报告,落盘到 拆文库/{书名}/,下游 story-short-write 同时读拆文报告 + 情节节点 + 写作手法 + 原文 + _meta.
Related: more creative & writing skills
If the story-short-analyze:短篇网文拆文 skill looks useful, you may also want to check out other creative & writing skills in the OpenClaw catalog:
Skills in this catalog are community-contributed integrations published on ClawHub and distributed under their own open-source licences. Product and company names, and any third-party service a skill connects to, are trademarks of their respective owners; a listing here does not imply affiliation with, sponsorship by, or endorsement from them. This page does not distribute any third-party application. Rights holders can reach us at hello@openclaw-easy.com.
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Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models