Jab Hook

Community

coreyhaines31

jab-hook

Gary Vaynerchuk's jab-jab-jab-right-hook framework applied to a personal portfolio rotation on X and LinkedIn. Jabs = build-in-public + educational (value). Hooks = promo (the ask). Each property in the user's configured portfolio (see `~/.config/makerskills/jab-hook/properties.yaml`) gets a hook at least once every ~3 weeks; jabs fill the rest. Drafts go into the user's Typefully workspace via MCP. Modes — plan (7-day plan), pick-next (single post), audit (coverage report), draft (specific post). Triggers on "/jab-hook," "what should I post," "plan my socials," "next promo," "next jab," "next hook," "social rotation," "promote [property]," "BIP post," "audit my socials," "what haven't I posted about."

Overview

Publisher	coreyhaines31
Repository	`makerskills`
Skill name	`jab-hook`
Stars	855
Forks	71
Bundled files	9
License	MIT
Links	Skill source Repository Homepage

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.
9 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by coreyhaines31 on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/coreyhaines31/makerskills/tree/main/skills/jab-hook
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.

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/coreyhaines31/makerskills.git /tmp/makerskills
mkdir -p .claude/skills
cp -r /tmp/makerskills/skills/jab-hook .claude/skills/jab-hook

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jab Hook 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 Jab Hook 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 Jab Hook 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.

/jab-hook — Jab-jab-jab-right-hook for a personal portfolio

Gary Vaynerchuk's framework applied to your configured portfolio: keep the feed mostly jabs (value — BIP + educational) so the hooks (promo) earn attention when they land. Drafts to your personal Typefully workspace.

One-time setup: see references/properties.md and references/typefully-config.md to configure your real portfolio + workspace. Personal config lives in ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/jab-hook/.

Mental model

N rotation slots (configured in ~/.config/makerskills/jab-hook/properties.yaml): one per property you want to promote on rotation
~2 promo posts/week → each property cycles every ~3 weeks at equal weight
Non-promo days: 50/50 build-in-public vs educational
Target weekly rhythm: ~2 promo + ~2–3 BIP + ~2–3 educational
Platforms: X + LinkedIn via your personal Typefully workspace

Step 1 — Pick the mode

Detect from the trigger:

User says	Mode
"plan my socials," "next week's posts"	plan
"what should I post," "next promo," "pick next"	pick-next
"audit my socials," "what's overdue," "what haven't I posted about"	audit
"draft a promo for X," "BIP post about Y," "educational about Z"	draft

If ambiguous, confirm.

Step 2 — Load context

Read references/properties.md — the 6 rotation slots and angle ideas
Read references/voice.md — the user's voice rules per platform
Read references/content-types.md — templates for promo / BIP / educational
Pull recent posts from your personal Typefully workspace:
- First run: call the Typefully MCP server's list-social-sets tool and ask which social set is your personal (X + LinkedIn). Save the ID to ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/jab-hook/typefully.yaml for future runs (schema in references/typefully-config.example.yaml — never save it inside the skill folder; upgrades wipe it).
- Call its list-drafts tool, filtered to the last 30 days
- Classify each as promo / BIP / educational by content
Compute days since last promo for each of the 6 slots

Step 3 — Mode logic

plan (7-day plan)

Slot the 1–2 most overdue properties as promo posts
Fill remaining 5 days with alternating BIP and educational (50/50)
Output as a table: Day | Type | Property/Topic | Hook | Draft summary
Don't stack two promo on consecutive days
After the user approves the plan, offer to draft each one in sequence

pick-next

Identify the most overdue property
If most overdue < 14 days, suggest a BIP or educational instead (whichever is less recent)
Draft 1 post; ask before syndicating

audit

Report: days since last promo per property, ordered by most overdue
Flag any property >21 days as overdue
Suggest the next 1–2 moves

draft

Skip rotation logic — draft the requested post
Use the right content-type template

Step 4 — Draft

Follow references/voice.md and references/content-types.md. Default: single post, one per platform (X version + LinkedIn version). Thread only if the second post earns its place.

Link placement (load-bearing): never put a URL in the body. Default is no link at all — let curiosity drive the click. When a link is needed, draft it as a first comment for LinkedIn (Typefully supports auto-comment) or a reply for X. The body always stands alone.

Optional: inspiration scan

For promo and educational posts, optionally scan inspiration accounts (references/inspiration.md) before drafting:

Pick 1–2 accounts whose audience overlaps with the property
Pull recent posts (agent-browser if it works on LinkedIn; otherwise ask the user to paste examples or fall back to their X/newsletter)
Extract structural patterns: hook openers, post length, line-break rhythm, CTA styles
Apply ONE pattern to the user's voice — never mimic phrasing
Log new patterns in ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/jab-hook/patterns.local.md (create if missing) so they accumulate — references/patterns.md documents the starter patterns and stays read-only

Skip inspiration scan when the user says "just draft it" or when iterating on an existing post.

Step 5 — Syndicate to Typefully

Ask: "Push to Typefully now? (X + LinkedIn, your personal workspace)"

If yes:

Read social set ID from ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/jab-hook/typefully.yaml (setup notes in references/typefully-config.md)
Call the Typefully create-draft tool once for X, once for LinkedIn (or once with both platforms if the social set spans both)
If the draft has a first-comment link, configure Typefully to add it automatically (LinkedIn auto-comment / X reply). If the MCP doesn't support auto-comment for one of the platforms, surface the comment text so the user can paste it after publishing.
Default to draft state (not scheduled) — the user reviews in Typefully UI before sending
Return the Typefully draft URLs

Composes with

paste — clean output for pasting into Typefully / LinkedIn / X manually if the MCP path doesn't fit
social-fetch — pull inspiration-account posts for structural analysis (replaces inline agent-browser)
second-brain — the Content Ideas wiki page hoppers hooks, frameworks, stories; /jab-hook drafts pull candidates from there
deep-research — when a promo needs a stat or citation the draft doesn't have yet
marketingskills:social — generic social frameworks, useful when teaching strategy vs shipping your own posts
marketingskills:copywriting — for hook / headline ideation when stuck

Notes on quality

1 promo per week per property is the floor, not the ceiling. Rotation compounds when it's predictable — 4 properties × 1 promo/week = 4 promo weeks/month. Educational + BIP + community fill the rest.
Never mimic phrasing from inspiration accounts. Extract structure (hook opener type, line-break rhythm, CTA style) and apply to your own voice. Voice is the moat; copying phrasing destroys it.
Links belong in first comments, not the body for LinkedIn + X. Documented in feedback_social_link_placement.md in your memory store (see below). Body posts with inline URLs get algorithm-suppressed on both platforms.
Draft state, not scheduled state. Every Typefully push defaults to draft — human review in the Typefully UI before publish is non-negotiable. Automated scheduling of unreviewed drafts has repeatedly produced posts the user regrets.
Reader-perspective framing. "You'll know X" not "we'll teach you X." "What you're guaranteed" not "what we'd guarantee."
Voice.local.md overrides the shipped voice.md. Personal voice rules never live in the public repo — always in ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/jab-hook/voice.local.md.
Cadence cap: 2 posts/day per platform, per account. More than that degrades reach + reads as spam.

Memory references

Your memory store is your agent's persistent memory if it has one (Claude Code's memory directory, for example), otherwise ${MAKERSKILLS_MEMORY:-${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/memory}/.

feedback_promo_voice.md in your memory store (if present) — conviction-coded CTAs + reader-perspective framing
feedback_social_cadence.md in your memory store (if present) — cadence cap (e.g., 2 posts/day per platform)

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 Jab Hook AI skill do?

Why use Jab Hook on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coreyhaines31/makerskills/tree/main/skills/jab-hook. 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 Jab Hook?

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 Jab Hook?

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

Is the Jab Hook AI skill free?

Yes. It is published on GitHub by coreyhaines31 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

/jab-hook — Jab-jab-jab-right-hook for a personal portfolio

Mental model

Step 1 — Pick the mode

Step 2 — Load context

Step 3 — Mode logic

plan (7-day plan)

pick-next

audit

draft

Step 4 — Draft

Optional: inspiration scan

Step 5 — Syndicate to Typefully

Composes with

Notes on quality

Memory references

Bundled files

Frequently asked questions

Related AI Skills

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