No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by publora · MCP Server · ★ 51
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is skills safe to install? View the security audit →
Publora Skills: post to 10 social networks from your AI agent Official skills from the Publora team. Nine files that teach Claude Code, Codex, Cursor, OpenClaw or any skills-aware agent how to publish and schedule posts on LinkedIn, X, Instagram, Threads, TikTok, YouTube, Facebook, Bluesky, Mastodon and Telegram through the Publora MCP server. Your agent drafts, you approve, Publora publishes. One integration instead of ten platform APIs, each with its own auth, media pipeline and rate limits. Install Get an API key at [app.publora.com/dashboard/api](https://app.publora.com/dashboard/api
| Stars | 51 |
| Forks | 6 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.3482062942458/100 |
| Open Issues | 3 |
| Last Updated | 2026-10-12 |
| Created | 2026-03-24 |
| Platforms | claude-code, codex, mcp, python |
| Est. Tokens | ~15k |
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skills is Official Publora skills for AI agents: post and schedule to LinkedIn, X, Instagram, Threads, TikTok, YouTube, Facebook, Bluesky, Mastodon and Telegram from Claude Code, Codex, Cursor or OpenClaw throu. It is categorized as a MCP Server with 51 GitHub stars.
skills is primarily written in Python. It covers topics such as agent-skills, ai-agents, bluesky.
You can find installation instructions and usage details in the skills GitHub repository at github.com/publora/skills. The project has 51 stars and 6 forks, indicating an active community.
skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to skills on Agent Skills Hub include awesome-ai-agent-skills, agent-skills, agent. 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: