Twitter Thread Style logo

Twitter Thread Style

Community
dannote
twitter-thread-style

Write or revise X/Twitter developer announcement threads in the user's preferred style. Use for technical launch threads, project announcements, release threads, and threads with code screenshots/snippets.

Overview

Publisherdannote
Repositorydot-pi
Skill nametwitter-thread-style
Stars
57
Forks
4
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dannote on GitHub. Read the source before you install it.

Installation

Install the Twitter Thread Style AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dannote/dot-pi/tree/master/skills/twitter-thread-style
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dannote/dot-pi.git /tmp/dot-pi
mkdir -p .claude/skills
cp -r /tmp/dot-pi/skills/twitter-thread-style .claude/skills/twitter-thread-style
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Twitter Thread Style in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Twitter Thread Style on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Twitter Thread Style is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Twitter Thread Style

Use this skill to write developer-facing X/Twitter threads in the user's voice.

This is a generic style skill. Do not bake in one project's facts. Read the current task context, source material, or user notes first, then apply the style rules below.

Goal

Write a technical announcement thread that works in the timeline.

The reader should be able to understand the project from the first tweet, but the code snippets/screenshots should be what make them stop scrolling.

The thread should feel like a developer showing a real tool, not a company writing a launch page.

Voice

Prefer:

  • plain technical statements
  • concrete reasons the thing exists
  • direct comparison to a known tool/category when it helps
  • understated confidence
  • real tradeoffs
  • specific capabilities
  • attractive code snippets

Avoid:

  • slogan speak
  • marketing copy
  • generic hype
  • vague architecture-first explanations
  • buzzwords like “unlock”, “seamless”, “delightful”, “empower”, “revolutionary”
  • claims that sound bigger than the evidence
  • explaining internals before explaining why the reader should care

Bad tone:

text
This unlocks a delightful new developer experience for modern teams.

Better tone:

text
I wanted the same workflow, but without leaving the stack I already use.

Strict Tweet Shape

Each tweet must follow this shape:

  1. A short chunk of text.
  2. Then one or more code blocks.

Do not inline code in prose. No backticked identifiers inside the paragraph.

Bad:

text
Run `my_tool dev` and edit `pages/index.md`.

Good:

text
The dev server is one command.
bash
my_tool dev

A tweet can contain multiple code blocks. Use this to increase density.

First Tweet

The first tweet must be optimized for the timeline.

It should quickly answer:

  • what was released
  • what familiar category/tool it relates to
  • what makes it different
  • what the code feels like

The first sentence should be short and direct.

Good patterns:

text
I published PROJECT.
text
PROJECT is public.
text
FAMILY has a new member: PROJECT.

Then use a familiar anchor if possible:

text
It is like KNOWN_TOOL, but for STACK.
text
I wanted KNOWN_WORKFLOW, but with DIFFERENT_CONSTRAINT.

The hook should usually be capability-first, not positioning-first. Lead with what became possible, what shipped, what changed, or what the thing is in familiar terms.

Then show the best code snippet immediately.

Code Is the Hook

Prioritize snippets that look good as screenshots.

Good snippets usually show:

  • compact syntax
  • normal language constructs instead of wrapper DSL noise
  • typed schemas or validation
  • route generation
  • small configuration blocks
  • pipelines with readable aliases/imports
  • components/templates with attractive syntax
  • before/after transformation
  • one command install/build/dev flow

Use aliases/imports for readability when the language supports them.

Bad:

elixir
value =
  input
  |> Very.Long.Namespace.Module.step_one()
  |> Very.Long.Namespace.Module.step_two()

Better:

elixir
alias Very.Long.Namespace.Module

value =
  input
  |> Module.step_one()
  |> Module.step_two()

Avoid snippets that only show plumbing unless plumbing is the point.

Text Density

Keep prose short. Let code carry meaning.

A tweet should usually be:

  • 1 to 4 short prose lines
  • 1 to 3 code blocks

If the prose explains something the code already shows, delete the prose.

Architecture Comes Later

Do not lead with architecture unless the architecture is the product.

Bad early framing:

text
The split is intentional.
text
The system has three layers.

Better early framing:

text
The default workflow stays inside one toolchain.
text
The config is just normal language code.

Explain architecture through user-visible consequences:

  • fewer processes
  • fewer config files
  • clearer data flow
  • better integration with existing tools
  • less generated glue
  • safer boundaries

Comparisons

Use comparisons to explain, not to posture.

Good:

text
I wanted the KNOWN_TOOL workflow, but in STACK.
text
It sits in the same space as KNOWN_TOOL, but the API follows STACK conventions.

Avoid:

text
It is better than KNOWN_TOOL.

unless the next line proves a very specific point.

Concrete Driver

Do not explain a project with abstract positioning first. Explain the concrete driver.

Good drivers include:

  • a new capability
  • a familiar workflow moved into a different stack
  • a measurable improvement
  • a missing abstraction extracted from real work
  • a new release or integration
  • a personal itch or frustration

Examples of good driver shapes:

text
PROJECT can now DO_THING.
text
I wanted KNOWN_WORKFLOW, but in STACK.
text
I got roughly N× improvement by changing THING.
text
PROJECT now supports INTEGRATION.

Do not force every project into a personal-pain story. Pick the real driver for this announcement.

Story Arc

A good technical announcement thread usually follows this arc:

  1. Hook: project/category/difference plus best code.
  2. Concrete driver: what became possible, simpler, faster, extracted, or newly supported.
  3. Install or minimal usage.
  4. Main syntax/API.
  5. Data/configuration model.
  6. One or two advanced capabilities.
  7. Integration with the surrounding ecosystem.
  8. Honest limitations or current scope.
  9. Links, version, repository/package.

Do not put limitations in the first tweet unless the limitation is central to understanding the project.

Honesty

Be precise about what exists now and what is future work.

Avoid pretending a roadmap item is implemented.

Good:

text
This part is static for now. Runtime support needs a separate design.

Good:

text
The first version is small, but the core path works.

When Revising

If the user pushes back, treat it as style data.

Common meanings:

  • “Why should the end user care?” means the draft is too architecture-first.
  • “Too much slogan speak” means replace marketing phrases with concrete technical facts.
  • “No inline code” means prose must not contain backticked identifiers.
  • “Use alias for readability” means snippets should be screenshot-readable.
  • “Prioritize impressive code snippets” means move the best code earlier and shorten the explanation.
  • “Too specific” means abstract the rule; do not force one announcement pattern onto every thread.
  • “Generic skill” means remove project-specific facts and keep reusable style rules only.

Do not argue. Rewrite.

Output Format

Use numbered tweets.

Template:

text
1/

Short prose. No inline code.

```language
code block
```

```language
optional second code block
```

2/

Short prose.

```language
code block
```

Before finalizing, check:

  • Does the first tweet have a strong code snippet?
  • Is every tweet text-first then code?
  • Is there no inline code in prose?
  • Is the prose concrete rather than slogan-like?
  • Are code snippets readable as screenshots?
  • Did the thread explain why the reader should care before internals?

Frequently asked questions

What does the Twitter Thread Style AI skill do?

Write or revise X/Twitter developer announcement threads in the user's preferred style. Use for technical launch threads, project announcements, release threads, and threads with code screenshots/snippets.

Why use Twitter Thread Style on TypingMind?

Because you install it once and use it with any model. Twitter Thread Style is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Twitter Thread Style in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dannote/dot-pi/tree/master/skills/twitter-thread-style. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Twitter Thread Style?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Twitter Thread Style?

As many as you like. As long as a model supports skills, you can use Twitter Thread Style with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Twitter Thread Style AI skill free?

Yes. It is published on GitHub by dannote under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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