twitter-post — Руководство по созданию эффективных твитов

--- name: twitter-post description: Write a Twitter/X post or thread based on research findings or a given topic. Use this skill when asked to create tweets, X posts, or social media threads. --- # Twitter/X Post Skill ## Single Tweet Format - Maximum 280 characters - Lead with the most compelling point - Use numbers or data when possible - End with a link placeholder or call-to-action - 1-2 hashtags max (optional) ## Thread Format (for longer content) - **Tweet 1**: Hook + preview of what's coming (e.g., "A thread on X:" or "Here's what I found:") - **Tweets 2-N**: One idea per tweet, numbered (1/, 2/, 3/) - **Final tweet**: Summary + call-to-action + link - Keep each tweet self-contained (people share individual tweets) - 4-8 tweets is the sweet spot for engagement ## Tone - Concise and punchy - Opinionated takes perform better than neutral summaries - Use plain language -- no corporate speak - Contrarian or surprising angles get more engagement ## Tips - Front-load the value (no throat-clearing or preambles) - Use line breaks within tweets for readability - Avoid hashtags in threads (they look spammy) -- save them for single tweets - Numbers and lists catch the eye in a feed ## Example Single Tweet ``` AI agents that manage their context window well outperform those with 10x more tools. The secret isn't more capabilities -- it's smarter context engineering. ``` ## Example Thread ``` Thread: What makes AI agents actually work in production? 🧵 1/ It's not the model size. It's context management. The best agents treat their context window like RAM -- offloading to filesystem, summarizing aggressively, loading info on demand. 2/ Subagents are the key to scaling. Instead of one agent doing everything, delegate to specialists. The main agent only sees the summary, not 50 intermediate tool calls. 3/ Skills > giant system prompts. Progressive disclosure: load detailed instructions only when the task needs them. Your agent's prompt stays clean until it matters. 4/ Memory needs structure. Semantic (facts), episodic (experiences), procedural (rules) -- route them to different backends so they persist appropriately. 5/ The takeaway: the best agent architectures are about information flow, not raw capability. What patterns are you using? Reply with your favorite agent architecture trick. ```