How do I install the Twitter Post skill?

Run npx skillmds@latest add tomevault-io/twitter-post in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Twitter Post safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Twitter Post?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Twitter Post free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Twitter Post?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Twitter Post by tomevault-io — Agent Skill

Name: Twitter Post
Author: tomevault-io

File contents

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.

Converted and distributed by TomeVault — claim your Tome and manage your conversions.

---name: twitter-postdescription: 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. Use when this capability is needed.---# 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.```---> Converted and distributed by [TomeVault](https://tomevault.io/claim/langchain-ai) — claim your Tome and manage your conversions.

Frequently asked questions

Twitter Post