agentleFS
Sign inStart free
cocyuhaococyuhao/my-ai-skills-library/personal-data-harvester/SKILL.md

personal-data-harvester

Skill1 starsChanged 6 months agoNo licenceView on GitHub

Autonomously collect and structure a user's personal content history from Chinese and international platforms (豆瓣, 小红书, B站, 微信读书, 抖音, Kindle, etc.) using browser automation, local file parsing, and system share-sheet intake. Use this skill whenever the user wants to: build a personal knowledge base from their consumption history, sync reading/watching/collecting records into a local database, set up an automated pipeline to continuously harvest their data from social or reading platforms, or feed their content history into an AI agent for analysis. Trigger even if the user just says "帮我把豆瓣数据导进来", "同步我的读书记录", or "抓取我收藏的内容" — any phrase implying cross-platform personal data ingestion should use this skill.

  • Installs packages

2 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free