القائمة
Use when you need to understand platform-specific conventions, algorithm behavior, content formats, or audience expectations for Instagram, TikTok, YouTube, X, or LinkedIn.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Use when analyzing why content performed well or poorly, doing post-mortem analysis, or comparing content performance.
Use when analyzing, evaluating, or generating hooks for short-form video or text posts.
Use when interpreting social media content — comments, captions, replies, DMs — and you need to understand tone, subtext, or cultural context beyond the literal words.
Use when adapting content from one platform to another, or advising on multi-platform content strategy.
Use when evaluating whether a trend is relevant, identifying emerging trends, or advising on trend participation timing.
Use when writing in a creator's voice, analyzing a creator's style, or maintaining consistency across content.
| name | platform-fluency |
| description | Use when you need to understand platform-specific conventions, algorithm behavior, content formats, or audience expectations for Instagram, TikTok, YouTube, X, or LinkedIn. |
This skill is a router. The deep platform knowledge lives in the reference files — this skill tells you when and how to use them.
Platforms differ on three axes. Knowing where a platform sits on each one shapes every recommendation.
Discovery mechanism:
Content lifespan:
Audience intent:
If the conversation involves a specific platform, read the .root file in this skill's directory for the repo path, then load {repo}/references/platforms/{platform}.md. If comparing platforms or adapting content across them, load both.
Every platform's audience can detect cross-posted content. Dead giveaways:
Native content consistently outperforms cross-posted content. When in doubt, adapt.
Don't give specific algorithm advice without loading the relevant platform reference — algorithms change frequently. Provide the framework (what signals matter, how distribution works) rather than specific numbers. If the reference's last_updated date is more than 6 months old, note that algorithmic details may have shifted.
If the reference can't be loaded, work with the mental model above and be upfront about the limitation.
