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Headlines

Community
notque
headlines

Generate headlines, titles, and subject lines: charge, volume, tighten.

Overview

Publishernotque
Repositoryvexjoy-agent
Skill nameheadlines
Stars
443
Forks
50
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 notque on GitHub. Read the source before you install it.

Installation

Install the Headlines 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/notque/vexjoy-agent/tree/main/skills/content/headlines
  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/notque/vexjoy-agent.git /tmp/vexjoy-agent
mkdir -p .claude/skills
cp -r /tmp/vexjoy-agent/skills/content/headlines .claude/skills/headlines
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Headlines 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 Headlines 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 Headlines 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.

Headlines

Generate headlines, article titles, social posts, and email subject lines from a brief or draft. Four phases: find the charge, generate volume across named moves, tighten survivors, output per format. Core rule: volume over polish -- breadth beats optimization because word-level features predict winners weakly.

Phase 1: FIND THE CHARGE

Identify the single most compelling tension or stake in the material.

  1. Read the brief, draft, or topic statement in full.
  2. List every tension candidate: surprise, reversal, cost, conflict, a number that changes the picture, a stake the reader holds.
  3. Pick ONE -- the charge. Write it as one sentence naming who is affected and what is at stake.
  4. Test: would a reader who saw only this sentence want the rest? A topic label ("Kubernetes networking") fails; a live tension ("DNS resolved yesterday, fails today, nothing changed") passes.

Gate: Charge is one sentence, names a specific tension, is true to source. A weak charge produces 20 weak headlines.

Phase 2: GENERATE VOLUME

Produce 15-25 candidate headlines spread across these ten named moves. Write fast; judge later.

The Ten Headline Moves

MoveReflexExample
Curiosity gapOpens a question only reading can close"The One-Line Nginx Default That Took Our API Down"
SpecificityCarries the concrete detail into the headline"CoreDNS Returns NXDOMAIN for Internal Services After Upgrading to 1.31"
StakesNames what the reader loses or gains"Your Postgres Backups May Be Silently Unrestorable"
ContrastTwo true things that should not coexist"Local Build Passes, Cloudflare Deploy Fails -- Same Commit"
QuestionAsks what the reader already wonders"Is Your Standup Meeting Just a Status Email With Legs?"
How-toPromises a capability, named precisely"How to Cut Go CLI Startup From 400ms to 40ms"
NumberCount or measurement as the spine"Three Config Lines That Halved Our CI Bill"
Voice-of-readerPhrased in the reader's own words"I Rotated the API Key and Production Still Worked. That's the Problem."
News pegAnchored to a current event"What the AWS Outage Reveals About Your Single-Region Bet"
Negative spaceLeads with what is absent or refused"The Test Suite Had No Test for the Thing That Broke"

Rules:

  1. Cover at least 6 of the 10 moves. Tag each candidate with its move.
  2. Keep every candidate anchored to the Phase 1 charge.
  3. Pull concrete material from the brief: numbers, names, error messages, dates.

Gate: 15-25 candidates, each tagged, at least 6 moves represented. Fewer than 15 means the charge is under-mined -- return to the brief.

Phase 3: TIGHTEN

Select and sharpen 3-5 survivors.

  1. Score every candidate 1-5 on: specificity, tension, accuracy to the brief. Sum the three.
  2. Keep the top 3-5. Require move diversity -- two candidates from the same move compete for the same reader reflex; keep the stronger one.
  3. Tighten each survivor:
    • Cut filler; front-load the charge into the first 3-4 words.
    • Replace any vague noun with the concrete one from the brief.
    • Verify every claim against the brief. The headline promises only what the content delivers.
  4. Drop any survivor that needs a hedge to stay accurate. Promote the next by score.

Gate: 3-5 survivors, each accurate, each from a distinct move where possible.

Phase 4: OUTPUT PER FORMAT

Adapt survivors to the formats the task needs.

FormatConstraintAdjustment
Article title~60-70 chars; sentence caseFull charge; specificity over wordplay
Social postPlatform length; standaloneAdd the stake or number; end with pull, not summary
Email subject line~30-50 charsFront-load the charge; cut articles and qualifiers first

Per-platform specs from content-engine (references/platform-specs.md) win on length when both apply.

Output format:

markdown
## Headline Options

**Charge**: [one-sentence charge]

### Article titles
1. "[title]" -- [move]
2. ...

### Social posts
1. "[post]"

### Subject lines
1. "[subject]"

**Recommendation**: [pick one, one sentence why]

Gate: Each requested format has 2+ options. Recommendation given with reasoning.

Integration

  • writing: when the writing voice pipeline's hook scores below 8, the HOOK-GATE agent may run Phases 1-3 here against the article body to surface the concrete detail the opening should lead with.
  • content-engine: supplies titles and subject lines for pipeline output; content-engine owns per-platform format specs.
  • Standalone: usable directly on any brief, draft, or topic.

Error Handling

ErrorCauseSolution
Brief has no tensionInput is a topic label or flat release notesAsk for the one fact that surprised the author, the cost of the problem, or what changed. If none exists, produce plain utilitarian titles.
All candidates sound the sameGeneration stayed in 1-2 movesWalk the move catalog in order; force one candidate per unused move.
Accurate headlines feel flatCharge is weak, not the wordingReturn to Phase 1. Find a sharper tension or report that the brief needs a stronger finding.

Frequently asked questions

What does the Headlines AI skill do?

Generate headlines, titles, and subject lines: charge, volume, tighten.

Why use Headlines on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/notque/vexjoy-agent/tree/main/skills/content/headlines. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Headlines?

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 Headlines?

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

Is the Headlines AI skill free?

Yes. It is published on GitHub by notque 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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