CRAFT Content report
Newsletter Builder: your result
This answer uses a made-up example company. Change the details above and press Run to see your own result.
Newsletter Builder
Build a newsletter with subject lines to test
For content and demand gen teams. The decision: what goes in this issue, and which subject line do we test?
Give it a topic and the action you want readers to take, and get subject lines to test, opening hooks, the newsletter itself, a checklist to run before you send and tips on when to send.
What you get
This sample is a made up example, built from the inputs behind Fill in an example. It shows part of one section of the answer.
Subject Lines (A/B Test These)
The subject above is the first option. Test it against these three:
Where do you stand with automated resolution rate?
- Preview text: This issue is about AI agents in customer support.
Automated resolution rate and accuracy on an evaluation set: what to check
- Preview text: Inside: the question you will hear and what to check in your own operation.
Questions to ask your team about automated resolution rate
See the full example answer or run it with your own details.
Result
When a tool is not enough: if the decision needs more than one answer, talk it through in a call. Book 45 minutes with Shashwat.
What next? Work with Shashwat Try another tool See all 85 tools and skills
Example answer
Generated on 2 November 2026 from this branch, with the inputs behind Fill in an example. Your own inputs give a different result.
CRAFT Content report
Example: Newsletter Builder
Show the full result
Newsletter issue draft
Subject: AI agents in customer support
Preview: For teams in AI native, the numbers to watch are automated resolution rate and accuracy on an evaluation set.
This issue is about AI agents in customer support.
For teams in AI native, the numbers to watch are automated resolution rate and accuracy on an evaluation set.
Here is what is in this issue: the question you will hear and what to check in your own operation.
1. The question you will hear
Teams in AI native often say: "AI gets answers wrong". A fair way to settle it is to agree an evaluation on your own history before go-live, with a person approving any action that moves money or changes a record.
2. What to check in your own operation
Put these two questions to your own team this week. First, "How would you judge that an answer is right: who reviews it today and against what?" Second, "Where does the data the AI needs live, and what may leave your environment?" Whatever the answers, write down where you stand today on automated resolution rate and accuracy on an evaluation set, so that the next change has a number to beat.
If this made you think, you can register for our support automation webinar.
Button: Register for our support automation webinar
Subject Lines (A/B Test These)
The subject above is the first option. Test it against these three:
Where do you stand with automated resolution rate?
- Preview text: This issue is about AI agents in customer support.
Automated resolution rate and accuracy on an evaluation set: what to check
- Preview text: Inside: the question you will hear and what to check in your own operation.
Questions to ask your team about automated resolution rate
- Preview text: AI agents in customer support.
Opening Hooks (Pick One)
Hook 1: Question
Which cases or decisions would you trust an AI to handle first, and which never?
Notes for you
- Link the button to the page or the reply address that does what the call to action says.
Sector Notes: AI native
Sector: read from your inputs as AI native. Business model: not stated. Tell us how you charge and the plan will adjust.
Billing dependent steps are conditional: trials, seats and recurring renewals require a subscription; a statement of work requires a services contract; site or link commitments require connectivity billing. Confirm the applicable choice before using those steps.
- Readers in AI native are usually Head of Customer Experience, Chief Technology Officer, Head of Data and AI. They watch automated resolution rate, accuracy on an evaluation set, escalation rate, handling time.
- Terms this audience uses: resolution rate, evaluation set, human in the loop, guardrails, accuracy, hallucination.
- Objections the sector file lists, and how to settle each: "AI gets answers wrong" (Agree an evaluation on the buyer's own history before go-live, with a person approving any action that moves money or changes a record); "Data privacy" (state exactly where data is processed and stored, what is used for training (if anything) and how it can be deleted); "We can build this on a model API ourselves" (Compare the full cost of building and maintaining evaluation, guardrails and integrations, not the model price); "Cost grows with volume" (show the cost per resolved case against the cost of handling it today, using the buyer's own volumes).
- A proof point that lands: Results on an evaluation set built from the buyer's own history, then live results with human review switched on.
What this draft was built from
| Setting | Value |
|---|---|
| Topic | AI agents in customer support |
| Product | not given |
| Segment | practitioners |
| Type | educational |
| Tone | conversational |
| CTA Goal | register for our support automation webinar |
To sharpen this, give: key points (it would change the sections, which now come from the sector's own objection, measures and questions instead of your points); your product (it would change the closing paragraph and every place the draft names what you sell).
When a tool is not enough: if the decision needs more than one answer, talk it through in a call. Book 45 minutes with Shashwat.
How to read the answer
The tool turns your Topic, CTA goal, and Key points into a Newsletter issue draft with a subject line, preview text, numbered sections, a call-to-action button, three A/B Subject Lines, Opening Hooks, and Sector Notes. If you leave Key points blank, the numbered sections fall back to standard sector objections and measures, and any number in your text without a named source in the same line is flagged under Notes for you. Treat the draft as a structural outline and replace the [Add your link] placeholder and any unsourced number before sending.
What to do next
- Founder: Pick the strongest hook from Opening Hooks and rewrite the intro in your own voice with a real story from your week.
- CEO: Check Notes for you to confirm every figure in the issue names its source and measurement period before the newsletter goes to subscribers.
- CMO: Choose two options from Subject Lines (A/B Test These) and make sure the Previous topics field was used so this issue does not repeat recent angles.
- CRO: Pull the Sector Notes proof shape and buyer vocabulary into a short forwardable note that reps can send to active prospects after the issue ships.
- Demand generation head: Put the real destination URL into [Add your link], set up the A/B subject line test in your email platform, and track clicks on the call-to-action button.
Why come back
Come back for every weekly or monthly newsletter issue, pasting your last three topics into Previous topics so the builder keeps your angles fresh and flags any unsourced numbers in your new notes. The tool applies the same fixed rules every time. It does not call an AI model, and this site does not keep what you enter.
Who is the Newsletter Builder tool not ideal for?
- Anyone who cannot give the inputs listed above, because the answer is built only from them.
- Teams that want finished copy in their brand voice: each tool returns a structured draft to edit, with placeholders wherever your inputs did not supply a fact.
- Anyone who needs research or quotes gathered for them: the tools do not look anything up. They work from the story and facts you give, and anything they add themselves is marked as an example, a suggestion or a placeholder.
How do I use the Newsletter Builder tool with an AI assistant?
Add CRAFT Content once (see Use it in Claude, ChatGPT or Gemini), then ask in plain words. Here is a prompt built from the tested example:
My role is not stated. Ask me for my role first. Use CRAFT Content's Newsletter Builder tool. topic: AI agents in customer support; CTA goal: register for our support automation webinar; audience segment: Practitioners; newsletter type: Educational; tone: Conversational. If this tool is unavailable, ask me to open its web page; do not invent its output. In Gemini CLI or Antigravity, use the Helix GTM Suite skills package for related guidance, without claiming to run this connector.
How does the Newsletter Builder tool work?
You do not need to sign in. A web browser is enough, and the answer comes back in a second or two.
- Fill in the form above, or press Fill in an example.
- Press Run Newsletter Builder.
- Read the result on this page, then copy it and edit it before you use it.
It applies fixed rules in the CRAFT Content code to the inputs above and returns text. It does not call an AI model, does not look anything up, and does not store what you type. The web form and the AI assistant connector run the same tool code, so the same input gives the same answer in both.
For developers
MCP tool name: newsletter_builder. REST: POST https://craft-content.gtmhelix.com/api/tools/newsletter_builder with this JSON body (see How it works):
{
"input": {
"topic": "AI agents in customer support",
"cta_goal": "register for our support automation webinar",
"audience_segment": "practitioners",
"newsletter_type": "educational",
"tone": "conversational"
}
}
Choose your app
Run a Helix tool in your browser, then take the result to ChatGPT, Claude or Gemini. Connectors work with supported plans in Claude, ChatGPT, Cursor, VS Code and Windsurf. The Helix GTM Suite skills package supports Claude Code, Gemini CLI, Antigravity, Cursor and VS Code, and is available through skills.sh. Each plugin has its own installation steps, below or on its own page.
Connector setup guides · Skills package setup guide · Find the skills on skills.sh