Oxygen Linkedin Marketing logo

Oxygen Linkedin Marketing

Community
timscheuerai
oxygen-linkedin-marketing

Run OXYGEN LinkedIn content and warm-signal motions through Posts, Publishing, Signals, Tables and bounded Sequences.

Overview

Publishertimscheuerai
Repositorylinkedin-funnel
Skill nameoxygen-linkedin-marketing
Stars
60
Forks
20
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 timscheuerai on GitHub. Read the source before you install it.

Installation

Install the Oxygen Linkedin Marketing 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/timscheuerai/linkedin-funnel/tree/main/skills/oxygen-linkedin-marketing
  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/timscheuerai/linkedin-funnel.git /tmp/linkedin-funnel
mkdir -p .claude/skills
cp -r /tmp/linkedin-funnel/skills/oxygen-linkedin-marketing .claude/skills/oxygen-linkedin-marketing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oxygen Linkedin Marketing 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 Oxygen Linkedin Marketing 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 Oxygen Linkedin Marketing 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.

Connect content to a useful next step

Read the author's context and the runtime contract. Use linkedin-copywriter for the actual grounded draft; this skill handles native delivery and engagement workflows.

For the bundled content-to-pipeline setup, read the LinkedIn kit. It links the author's scaffold, Notion board, native watcher, qualification template, DM framework and downloadable funnel.

WorkNative surface
Draft artifact and owned post dataPosts
Review, schedule and broadcast deliveryPublishing
Durable viewers, followers, connections and engagementSignals
Working qualification/enrichment rowsTables
New DM and warm follow-up cadenceSequences
Existing-thread replyMessages / Unibox

For daily engagers of named public LinkedIn profiles, prefer the native one-table Profile Watcher. Get real profile URLs, preview the current configuration and per-cycle credit cap, and preserve the returned hash. Creating or resuming it starts paid recurring collection; it is not the disabled three-table blueprint. Keep a stable create request ID across ambiguous retries.

Add qualification only after inspecting the actual table columns and the user's company/persona rubric. The bundled prompt reads existing evidence and has a separate paid AI run. Calibrate a bounded sample before auto-run. Hold missing required enrichment, keep company and person fit independent, and retain the exact engager's source-post attribution. Watcher collection, qualification, resource delivery and Sequence enrollment are separate operations; do not imply one automatically performs the next.

Discover the chosen motion with oxygen capabilities search "LinkedIn content and warm engagement" --json, then hydrate only its commands. Public/third-party research uses the current native public-research catalog where available; connected-account actions have their own limits and scope. Do not silently substitute another provider.

For a lead-magnet post, verify the resource URL and promise. Inspect the exact author/account, copy, media and schedule before requested publication. Record the Post and Publishing IDs and read back delivery state.

For comment-to-resource or network capture, inspect the capture window, dedupe keys, pagination and freshness. Separate capture from auto-enrollment. A standing outreach grant must specify the eligible cohort, destination Sequence, limits and stop conditions. Engagement alone does not establish fit or permission for broader outreach.

Owned-post public comments belong to the Publishing community queue. Check its freshness before trusting an empty queue. Use the native reply preview and content-bound approval action; do not manufacture approval or retry an unknown external effect.

For analytics, inspect current owned-post summary/detail commands. Read coverage and freshness alongside totals; null means unavailable. Preserve source/post/event IDs through qualification and Sequence results. Monitoring belongs to hosted subscriptions or Workflows.

Return the draft/published state, resource URL, captured/qualified/held counts where available, and native object links. Avoid equating post reach with attributable pipeline.

Frequently asked questions

What does the Oxygen Linkedin Marketing AI skill do?

Run OXYGEN LinkedIn content and warm-signal motions through Posts, Publishing, Signals, Tables and bounded Sequences.

Why use Oxygen Linkedin Marketing on TypingMind?

Because you install it once and use it with any model. Oxygen Linkedin Marketing 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 Oxygen Linkedin Marketing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/timscheuerai/linkedin-funnel/tree/main/skills/oxygen-linkedin-marketing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Oxygen Linkedin Marketing?

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 Oxygen Linkedin Marketing?

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

Is the Oxygen Linkedin Marketing AI skill free?

Yes. It is published on GitHub by timscheuerai 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇