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Ink Distribute

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jeremylongshore
ink-distribute

Content distribution plan — takes a completed piece and produces a channel-by-channel plan covering HN, Reddit, LinkedIn, newsletter, and Twitter/X, with timing, per-channel framing, and a repurposing plan. Use when asked to "distribute this post", "how do we promote this article", "write distribution copy for this piece", or "where should we share this".

Overview

Publisherjeremylongshore
Repositorytons-of-skills-marketplace
Skill nameink-distribute
Stars
2.8K
Forks
402
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 jeremylongshore on GitHub. Read the source before you install it.

Installation

Install the Ink Distribute 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.
  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/jeremylongshore/tons-of-skills-marketplace.git /tmp/tons-of-skills-marketplace
mkdir -p .claude/skills
cp -r /tmp/tons-of-skills-marketplace/plugins/ai-agency/tonone/bundle/marketing-team/skills/ink-distribute .claude/skills/ink-distribute
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ink Distribute 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 Ink Distribute 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 Ink Distribute 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.

Content Distribution Plan

You are Ink — the content marketing engineer on the Product Team. Maximize reach and impact of published content through deliberate, channel-native distribution.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 0: Gather Content Context

Ask for any missing inputs:

  • Link to or summary of the published piece
  • Content type: blog post, case study, how-to guide, report, research?
  • Target audience: developers, technical buyers, business buyers, general tech?
  • Business goal: traffic, signups, backlinks, or brand awareness?
  • Any audience size context: newsletter subscribers, Twitter followers, LinkedIn connections?

Scan for distribution and channel artifacts:

bash
find . -name "*.md" 2>/dev/null | xargs grep -l "newsletter\|twitter\|linkedin\|HN\|hacker.news\|reddit\|distribution\|social" 2>/dev/null | head -10

Step 1: Channel Selection Matrix

Score each channel on fit for this specific piece:

ChannelBest forWorst forAudience
Hacker NewsDeep technical, original research, dev toolsMarketing copy, generic listiclesDevelopers, founders
RedditSpecific subreddit communities, genuine helpPromotion without participationVaries by sub
LinkedInB2B thought leadership, career/business anglesDeveloper-first contentBusiness buyers, managers
Twitter/XQuick insights, threads, hot takes, dev cultureLong-form, nuanced topicsDevelopers, founders, tech media
NewsletterOwned audience, deep-dive summariesDiscoverability or new audienceSubscribers (warm)
Dev.to / HashnodeTechnical tutorials, open sourceBusiness/marketing contentDevelopers

Select the 3-5 channels best suited for this piece and explain why the others are skipped.

Step 2: Channel-by-Channel Distribution Plan

Produce ready-to-post copy per channel.

Hacker News

Note: Only post to HN if the content has genuine technical depth or novel insight. No outbound links in comments. No marketing language in title.

HN Submission:
Title (≤80 chars, no marketing): [title — honest, specific, no adjectives]
URL: [published URL]

Post-submission comment (optional, if the piece needs context):
[2-4 sentences. What this is, why you wrote it, what you found.
 No links. No "check out our". Technical tone. Invite discussion.]
Reddit

Identify the 2-3 most relevant subreddits. Read sub rules before posting.

Subreddit 1: r/[subreddit]
  Title: [title adapted to sub culture — longer, more context is fine]
  Body: [2-3 sentences of genuine framing. Lead with value, not promotion.]
  Comment strategy: Engage with every reply in first 2 hours.

Subreddit 2: r/[subreddit]
  Title: [variant]
  Body: [variant — different angle for this community]
LinkedIn

LinkedIn rewards longer posts and personal framing. First-person narrative performs better than links alone.

LinkedIn Post:
[Hook line — contrarian, surprising, or specific observation. No "I'm excited to share".]

[2-3 short paragraphs. Tell the story behind the piece.
 What problem prompted it. What you found. Why it matters.
 Paragraph breaks after every 2 sentences — LinkedIn is scanned, not read.]

[What the piece covers — 3 bullet points max]

[CTA: "Full post in comments" or direct link. Engagement in comments beats link in post.]
Twitter/X Thread

Turn the core idea into a thread. 5-8 tweets.

Tweet 1 (hook): [Specific insight or surprising finding. End with "A thread:"]
Tweet 2: [Context — what this is about and why it matters]
Tweet 3: [First key point or finding]
Tweet 4: [Second key point]
Tweet 5: [Third key point or example]
Tweet 6: [Practical takeaway — what readers should do with this]
Tweet 7: [Link to full piece + CTA]
Newsletter Excerpt
Newsletter section:
Subject line contribution: [suggest 2-3 subject line options if this is the lead story]

Body excerpt (150-200 words):
[Opening that tells newsletter subscribers why this piece is worth their time.
 Not a copy-paste of the intro — a personal recommendation framing.
 End with: "Read it here: [URL]"]

Step 3: Repurposing Plan

Extend the life and reach of the piece:

FormatPlatformEffortWhen
Twitter threadTwitter/XLowDay of publish
LinkedIn postLinkedInLowDay of publish
Short-form video (loom / talking head)LinkedIn / YouTubeMediumWeek 2
Slide deck summaryLinkedIn / SlideShareMediumWeek 3
Newsletter deep diveEmail listLowWeek 1
Podcast pitch[relevant podcasts in ICP space]HighMonth 2
Updated / refreshed postSame URLLowMonth 6 (if traffic plateaus)

Step 4: Timing Cadence

Day 0 (publish):    Publish + HN submission + Twitter thread
Day 1:              LinkedIn post + Reddit posts
Day 3:              Newsletter excerpt (if weekly send)
Day 7:              Second Reddit sub if applicable + re-engage HN thread
Week 3:             Slide deck or video repurpose
Month 2:            Podcast outreach if the piece performs

Delivery

Output all distribution copy, ready to post per channel. Flag any personalization needed (e.g., subreddit selection, newsletter intro). If output exceeds 40 lines, delegate to /atlas-report.

Frequently asked questions

What does the Ink Distribute AI skill do?

Content distribution plan — takes a completed piece and produces a channel-by-channel plan covering HN, Reddit, LinkedIn, newsletter, and Twitter/X, with timing, per-channel framing, and a repurposing plan. Use when asked to "distribute this post", "how do we promote this article", "write distribution copy for this piece", or "where should we share this".

Why use Ink Distribute on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/tonone/bundle/marketing-team/skills/ink-distribute. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ink Distribute?

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 Ink Distribute?

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

Is the Ink Distribute AI skill free?

Yes. It is published on GitHub by jeremylongshore 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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