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Promote

Community
oliver-kriska
promote

Generate X/Twitter release promotion posts with ASCII tables and CodeSnap rendering. Use when writing release posts, promotion tweets, plugin announcements, or preparing social media content for new versions.

Overview

Publisheroliver-kriska
Repositoryclaude-elixir-phoenix
Skill namepromote
Stars
565
Forks
45
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by oliver-kriska on GitHub. Read the source before you install it.

Installation

Install the Promote 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/oliver-kriska/claude-elixir-phoenix/tree/main/.claude/skills/promote
  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/oliver-kriska/claude-elixir-phoenix.git /tmp/claude-elixir-phoenix
mkdir -p .claude/skills
cp -r /tmp/claude-elixir-phoenix/.claude/skills/promote .claude/skills/promote
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Promote 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 Promote 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 Promote 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.

/promote — Release Promotion Post Generator

Generate data-driven X/Twitter posts for plugin releases with ASCII cards ready for CodeSnap screenshots.

When to use

Run /promote vX.Y.Z after tagging a release. Optionally add a title: /promote v2.8.0 "LiveView Streams Overhaul".

Output

All files go to scratchpad/x-posts/{version}-release.md (create directory if needed).

The output file contains three sections:

  1. ASCII Card — box-drawing table for CodeSnap screenshot
  2. Tweet Thread — 3-5 tweets in proven format
  3. CodeSnap Command — exact CLI command to render the card
  4. Fact-Check — every claim with verifiable data source

Execution Flow

Step 1: Gather Data

Collect these metrics (all are verifiable commands — run them, don't estimate):

MetricHow to get it
File count + insertions/deletionsgit diff --stat {prev-tag}..{tag}
Skill countls plugins/elixir-phoenix/skills/ | wc -l
Agent countls plugins/elixir-phoenix/agents/*.md | wc -l
Iron Law countGrep for numbered Iron Laws in CLAUDE.md
Eval scoresmake eval-all (run it, report actual numbers)
Changelog entriesRead CHANGELOG.md for this version's section
Before/after metricsDepends on release — look for quantifiable changes

The strongest posts have before/after comparisons. Look for changes in CHANGELOG.md that have measurable deltas (line counts, counts of affected files, error rates, coverage numbers).

Step 2: Write the ASCII Card

The card is the visual centerpiece — it gets screenshotted via CodeSnap and attached to tweet 1.

Rules:

  • Exactly 72 characters wide (including borders) — consistent with past posts
  • Use Unicode box-drawing: ┌─┐│└┘╞═╡╤╪╧ for borders and separators
  • Include: version + title, headline stats, before/after table, repo URL
  • The table content comes from Step 1 data — pick the 3-5 most impressive changes
  • VERIFY ALIGNMENT: After writing the table, run a Python script to check every line has the same visual width. Off-by-one errors are the most common problem — em dashes (—) and arrows (→) are single-width but easy to miscount. Every line between the top ┌ and bottom └ borders must be exactly 72 visual characters

Also save the ASCII card as a separate .txt file at scratchpad/x-posts/{version}-table.txt for CodeSnap input.

See ${CLAUDE_SKILL_DIR}/references/templates.md for the proven card format and past examples.

Step 3: Write the Tweet Thread

Follow the hook → findings → details → CTA structure. Read ${CLAUDE_SKILL_DIR}/references/templates.md for proven tweet patterns.

Thread rules (from analytics on 7 posts, 6.9K-9.9K views):

  • Tweet 1 (Hook): Version + one compelling sentence about what changed. Include headline stats (files changed, skills, agents). Repo link here — not in a reply. Add #ElixirLang #ClaudeCode hashtags.
  • Tweet 2-3 (Findings): The specific changes with numbers. Use numbered lists. Before/after metrics are the highest-performing content type.
  • Tweet 4-5 (Details/CTA): Additional changes + soft CTA ("Try it and let me know how it feels"). Link to release page.
  • Max 5 tweets — casual readers drop off after 4-6. If you have more content, cut the least impactful items.

Voice and tone:

  • Data-heavy, transparent, no-hype — this is the proven #1 strength
  • Write like a builder sharing real numbers, not a marketer
  • Concrete numbers over adjectives ("32/40 descriptions rewritten" not "improved many descriptions")
  • Never mention API costs or token prices — subscription user, cost per call is irrelevant

Step 4: CodeSnap Command

Output the exact command to render the ASCII card as an image. The card .txt file from Step 2 is the input.

Use the config file at scratchpad/x-posts/codesnap-claude-dark.json (dark gradient, tight margins, no watermark):

codesnap -f scratchpad/x-posts/{version}-table.txt \
  -o scratchpad/x-posts/{version}-card.png \
  --config scratchpad/x-posts/codesnap-claude-dark.json \
  --title "claude-elixir-phoenix {version}" \
  -l text

Then render and verify the image looks correct by reading the output PNG.

Step 5: Fact-Check

Every claim in the tweets must have a corresponding entry in the fact-check section:

markdown
## Fact-Check

- File stats: `git diff --stat {prev}..{tag}` (output: N files, +X/-Y)
- Eval scores: `make eval-all` output — N skills avg X.XXX, N agents X.XXX
- [claim]: [exact command or file:line that proves it]

If a claim can't be verified with a command or file reference, flag it as UNVERIFIED and suggest rewording.

Bundling Strategy

When deciding whether a release warrants its own post:

  • Standalone post: Major features, impressive before/after metrics, new capabilities
  • Bundle with next release: Bug fixes, description tweaks, minor config changes
  • Skip entirely: Patch releases with <5 files changed and no user-facing changes

The v2.6.1 post (37 likes, 1.4K views) vs v2.6.0 (150 likes, 5.5K views) demonstrates this — back-to-back releases dilute signal. When in doubt, wait and bundle.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Promote AI skill do?

Generate X/Twitter release promotion posts with ASCII tables and CodeSnap rendering. Use when writing release posts, promotion tweets, plugin announcements, or preparing social media content for new versions.

Why use Promote on TypingMind?

Because you install it once and use it with any model. Promote 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 Promote in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oliver-kriska/claude-elixir-phoenix/tree/main/.claude/skills/promote. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Promote?

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 Promote?

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

Is the Promote AI skill free?

Yes. It is published on GitHub by oliver-kriska 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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