twitter-thread-creation

A step-by-step method for planning and writing Twitter threads with help from AI and review by a person. A Twitter thread is a series of connected posts published together.

In plain words
What is it for?
Use it to brainstorm thread topics, outline posts, write drafts, and review short educational content before publishing.
Why use it?
It provides a repeatable way to choose a topic, create an opening that earns attention, organize the information, and add personal judgment.

Cursor rule

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/jondoescoding/jondoescoding-coding-rules/twitter-thread-creation
Clone the repo
git clone --depth 1 https://github.com/jondoescoding/jondoescoding-coding-rules
Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 1,732 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01732
Opus 5 $0.00000 $0.00866
Sonnet 5 $0.00000 $0.00346
Haiku 4.5 $0.00000 $0.00173

Measured yesterday against content hash 02b13ec3a792, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

twitter-thread-creation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

templates/cursor-rules/writing/twitter-thread-creation.mdc · 254 lines

How it starts

The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Content Creator's Guide for Viral Twitter Threads

Overview

This guide helps you systematically prompt AI to create high-performing Twitter threads that consistently get 100+ likes. Built for content creators using a human-in-the-loop approach.


Step 1: Topic Ideation Prompt

Initial Prompt Template:

I'm a content creator looking to create viral Twitter threads. 

Generate 10 thread topics that would appeal to:
- [Your target audience 1]
- [Your target audience 2] 
- [Your target audience 3]
- [Your target audience 4]

Topics should be:
- Timely and relevant
- Personally relatable
- Educational but accessible
- Controversy-free but engaging

Format as: "Topic: [Brief description] - Hook potential: [1-10]"

Human Review Step:

  • Pick the topic with highest hook potential that you're genuinely excited about
  • Consider your recent experiences or learnings you can add personal insight to

Step 2: Thread Structure Planning

Structure Prompt Template:

Help me plan a Twitter thread about: [CHOSEN TOPIC]

Create an outline with:
1. Hook tweet (with 3 variations to test)
2. Preview tweet (what readers will learn)
3. 5-8 main content tweets (one key point each)
4. Personal insight tweet (story/experience)
5. Call-to-action tweet

For each tweet, include:
- Main message
- Suggested formatting (bullets, emojis, line breaks)
- Engagement elements (questions, relatable moments)

Target thread length: 7-10 tweets total
Tone: Conversational, helpful, authentic

Human Review Step:

  • Ensure the flow tells a complete story
  • Verify you have personal experiences to share for the insight tweet
  • Adjust length if needed (shorter often performs better)

Step 3: Hook Optimization

Hook Refinement Prompt:

I need to perfect the hook for my Twitter thread about: [TOPIC]

Current hook options:
[PASTE THE 3 VARIATIONS FROM STEP 2]

Create 5 additional hook variations that:
- Start with curiosity/intrigue
- Include numbers or specific outcomes when possible
- Promise clear value
- Use power words (without being clickbait-y)
- Are under 280 characters

Also suggest an eye-catching visual idea for the first tweet.

Read the full file on GitHub · 254 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 254 lines · 0 tokens per session scan A 02b13ec3a792

Subscribe to this mod's changes

twitter-thread-creation is a cursor rule published in the GitHub repository jondoescoding/jondoescoding-coding-rules (2 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,732 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.