Write Starter Questions That Lead to Useful Work

A useful conversation starter for an expert AI skill names a reader’s situation, asks for a concrete result, and supplies or requests the information your method needs. It should make the first step easier without promising an outcome the skill cannot deliver. Give readers a small set of distinct starting points rather than a long list of topics.

“Ask me anything about my book” describes a large possibility space. “Help me choose one photograph for the opening page of my family album” gives the reader something to do.

The examples below are original design exercises for a fictional author’s method. They have not been run through a model or tested with readers. They show how to move from an interesting question to a usable starting request, and how to evaluate the resulting conversation before publishing the starter.

The reader-facing starter is an invitation. The skill’s underlying instructions should carry the method: what to ask, how to evaluate the answer, which mistakes to avoid, and when to stop. A reader should not have to paste your entire framework into every request.

Viven’s documentation makes a useful distinction between an expert’s core instructions and the suggested questions shown when someone opens a chat. Its guidance recommends starters tied to the expert’s job and to things people actually ask. That is product-design guidance from one provider, not evidence that its interface improves reader outcomes. Viven’s behavioral-cues documentation.

For your skill, write the expected next action before polishing the button label. If a reader chooses “Find my strongest example,” should the assistant ask for a draft, a description of the audience, or several candidate examples? The starter and the method should agree.

You can offer a short label with a fuller request underneath, or place a copyable example in your welcome guide. Use whatever the delivery interface supports. Do not assume that every AI client displays the same starter buttons or sends the same text when selected.

In a discussion about starting conversations with AI, u/Imogynn described a simple opening pattern:

“Here's the situation”

“Here's what I want”

That is an individual practice, not a validated formula. It is nevertheless a useful editing question for an author: can the reader tell the assistant both of those things from your starter? Original conversation-opening comment.

A starter does not always need to contain the situation itself. It can begin an intake: “Help me select a story for my album. First ask who will read it.” What matters is that the next exchange collects information your method uses.

Anthropic’s support guidance recommends clear requests, sufficient context, smaller steps for complex tasks, and follow-up clarification. Apply those principles without making your reader fill out a lengthy form before experiencing any value. Claude’s prompting guidance.

Imagine an author named Rosa whose book teaches families to create small photo albums with meaningful captions. Her method has three decisions: choose the audience, select details that serve the story, and distinguish remembered facts from uncertainty.

The skill is intended to help with those decisions. It cannot identify unknown people with certainty, recover missing memories, or establish who owns an image. The starter questions should stay inside the method’s useful scope.

These three entry points cover different reader states: someone choosing where to begin, someone with material to revise, and someone checking a draft. They are not three phrasings of the same broad question.

Before: “How do I make a better photo album?”

The question could produce an essay about design, printing, storage, or storytelling. It does not tell the assistant which decision is holding the reader up.

After — short label: “Choose a story for my first album.”

Copyable example request:

Use Rosa’s album-planning method. I want to make a six-page album for my adult daughter about summers at her grandparents’ house. I have photos of the garden, the kitchen table, and a trip to the lake. Help me choose one story that fits six pages. Ask what I want her to remember before suggesting a sequence.

The reader supplies the audience, material, and size constraint. The method still has something meaningful to ask: the purpose of the album. A recommendation made before that answer would skip the author’s first decision.

An expected first response might ask, “What do you most want your daughter to remember about those summers?” That is an illustrative response target, not output from a test. After receiving the answer, the skill could compare two possible story directions against the stated purpose.

The success check is specific: does the proposed sequence serve one chosen story within six pages? A long list of album ideas is not the same result. Nor is an emotional narrative built from details the reader never supplied.

For a real author, replace the fictional method name and example with your own supported workflow. Keep a complete example available so readers can see what useful input looks like without wondering how to fill in several unexplained brackets.

Before: “Write a moving caption.”

“Moving” says something about tone but nothing about what is true. It can invite a polished story that exceeds the available memory.

After — short label: “Draft a caption from what I remember.”

Copyable example request:

Use Rosa’s caption method. The photo shows my grandfather at the kitchen table with a blue mug. I remember that he did the crossword there most mornings, but I do not know the year of the photo. Write two caption options under forty words for my daughter. Keep the year unknown and do not invent what he was thinking or saying.

This request includes enough facts to do useful work immediately. It also marks a boundary: the missing date should stay missing. The assistant should not interrogate the reader about unrelated details merely because the method includes an intake elsewhere.

A possible illustrative caption is: “Grandad at the kitchen table, blue mug beside him. I remember him doing the crossword here most mornings. I don’t know which year this photograph was taken.” The wording is original sample copy, not a recovered family memory or a tested model answer.

The check is whether the caption preserves the supplied facts and the uncertainty, stays within the length limit, and fits the intended reader. A warmer sentence is not automatically better if it adds an unsupported anecdote.

The starter can work from a typed description. Do not require a photo upload unless the chosen workflow actually needs one and you have explained the relevant sharing conditions. Giving a reader a lower-effort route can also reveal whether the obstacle is the writing decision or the mechanics of uploading material.

Before: “Is my album good?”

This invites broad reassurance and makes it hard for the reader to use the answer. What should “good” mean for this album?

After — short label: “Check my opening page before I print.”

Copyable example request:

Use Rosa’s album-review method. My album is for my daughter and should show how ordinary summer routines made the grandparents’ house feel welcoming. My opening caption is: “Every summer was perfect, and everyone loved being together.” The photo shows three people eating breakfast. Review the caption for a specific observed detail, a clear link to the album’s purpose, and claims broader than my evidence. Suggest one revision and ask me for a detail if needed.

The request gives the assistant criteria rather than asking for approval. It also supplies an example with an intentional weakness: “every” and “everyone” claim more than the photo description establishes.

The expected next move is to identify the unsupported generalization and ask for a remembered detail or propose a cautious revision. It should not decide what every family member felt. It should not certify the whole album from one caption.

A practical outcome is a revision the reader understands: which claim changed, which detail supports the new wording, and what still needs checking. That is more useful than a numerical score with no explanation.

Look for the questions readers already ask after a talk, in a workshop, or in support. Remove identifying details and ask permission where needed before turning a private situation into a public example. Keep the decision structure that made the question useful.

In a discussion among people doing chatbot-evaluation work, u/AstarteHilzarie described starting with an actual need:

“I used to start with something that I actually needed to do and go from there.”

The context was paid annotation work, not a study of book readers. The relevant idea is to begin with plausible work rather than an impressive-looking prompt. Original practitioner comment.

A starter earns its place when you can name the reader situation, the input they can reasonably provide, and the next useful result. If two starters require the same information and lead to the same result, combine them. If a popular question falls outside your method, write a clear boundary or an appropriate referral instead of stretching the skill’s claim.

Before publishing a starter, run the exact text through the supported reader route. Record the skill version, client, date, and supplied inputs. Compare the behavior with your expected first step rather than judging only how polished the answer sounds.

Try a version with one important detail missing. Does the assistant ask for it or invent it? Try a correction: the album is for a cousin, not a daughter. Does the next recommendation reflect the change? Try a request outside scope, such as identifying an unknown person from appearance. Does the workflow stay within the boundaries you set?

Those are proposed tests, not results for Rosa’s fictional skill. They help you discover whether the invitation and the method work together. Use how to write an agent skill to repair the underlying instructions when a starter exposes a gap.

After launch, ask readers whether the starter helped them reach a useful result. A click tells you someone chose it; it does not tell you whether the work was completed. Keep the prompts that lead into the method’s strongest tasks, and revise the ones that consistently need explanation.

If you want help finding those first tasks in your book, visit Skillfully and choose Book onboarding. Bring three questions readers already ask and the work you want each conversation to produce.