by yanhua1010 · Claude Skill · ★ 382
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通用、模块化的自媒体内容生产与经营 Skills / A modular, tool-agnostic self-media content skill suite
| Stars | 382 |
| Forks | 51 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 58.5601173248145/100 |
| Last Updated | 2026-08-23 |
| Created | 2026-07-22 |
| Platforms | claude-code, python |
| Est. Tokens | ~7k |
These tools work well together with self-media-content-workflow for enhanced workflows:
Looking for a self-media-content-workflow alternative? If you're comparing self-media-content-workflow with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
微信公众号 AI 运营助手 | 选题、写稿、审稿、排版、配图、发布全流程 Skill，支持 OpenClaw / Claude Code / Cursor / Codex
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HeyClaude (formerly Claude Pro Directory) is a searchable collection of pre-built AI skills, agents, MCP serve
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self-media-content-workflow is 通用、模块化的自媒体内容生产与经营 Skills / A modular, tool-agnostic self-media content skill suite. It is categorized as a Claude Skill with 382 GitHub stars.
self-media-content-workflow is primarily written in Python. It covers topics such as agent-skills, ai-agents, claude-code.
You can find installation instructions and usage details in the self-media-content-workflow GitHub repository at github.com/yanhua1010/self-media-content-workflow. The project has 382 stars and 51 forks, indicating an active community.
self-media-content-workflow is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to self-media-content-workflow on Agent Skills Hub include wechat-article-skills, content-pipeline, affiliate-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: