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Workflows First

Welcome back to Workflows First!

Featuring:

  • Make Claude challenge your idea: 12 skills, in the order you'd use them

  • A two-week validation sprint you can copy

  • Try this today: one prompt that stress-tests an idea, no install needed


A glowing light bulb on a workbench under an interrogation-style desk lamp, surrounded by sticky notes with question marks, a magnifying glass and a paper prototype.

Your idea, cross-examined

12 Claude skills for entrepreneurs and innovators moving from an interesting idea to a credible first launch.

Give Claude an idea for a business, and you can leave the conversation with a name, a landing page, and a remarkably convincing explanation of why it should exist.

You may still have no idea whether anyone wants it.

That's the part of AI-assisted entrepreneurship I keep coming back to. Making an idea look real has become much easier. Deciding whether it deserves your next month of work still takes judgment.

I want Claude involved earlier, while the idea is awkward and the assumptions are exposed. Who has this problem? What are they doing about it today? What would make them switch? Which part of my plan is supported by evidence, and which part am I simply excited about?

Skills can make those questions a repeatable part of the work.

Here are 12 worth considering, arranged around the decisions a founder or innovation team has to make. The same workflow fits a new service, a course, or an internal initiative. Skip the software-building skills if your first experiment needs only a conversation and a spreadsheet.

First, understand what you're installing

A skill is a reusable set of instructions built around a file called SKILL.md. It can also bundle reference material, templates, and scripts. Claude Code loads a skill when your request matches it, and some skills are designed for you to call explicitly.

Skills preserve a method, not your project. Your customer evidence and decisions still need to be saved and kept current somewhere. Skills also cost context: Claude keeps each installed skill's short description in view and loads the full instructions only when the skill is used. Installing everything is rarely a useful starting point. Anthropic explains the mechanics here.

The installation steps at the end are for Claude Code on your own computer. The prompts are my suggested applications of each skill, using a fictional product: a service that helps small consulting firms turn meeting notes into client proposals. None of the examples is a tested business result.

Start with the assumption most likely to sink the idea

1. grill-me — Make the idea survive questions

Matt Pocock's grill-me describes itself as "a relentless interview to sharpen a plan or design." It works for nontechnical decisions, too. You start it yourself (Claude won't trigger it on its own), and it doesn't save a project record for you.

I'd use it before writing a product plan, and ask Claude to focus on the answers that would change your decision.

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I want to help small consulting firms create proposals from meeting notes. Challenge who would buy this, how often the problem occurs, and why their existing tools are insufficient. Push back on unsupported answers. Keep a clear distinction between what I know and what I need to investigate.

When the session ends, ask Claude to save the unresolved assumptions to a file. That list becomes your research agenda.

2. customer-research — Find the problem in customers' words

Corey Haines's customer-research analyzes interviews, surveys, reviews, and support conversations, and helps plan new research. It can also walk you through mining public sources such as forums and competitor reviews, which helps when you don't have customers yet.

Bring actual material. A convincing imaginary customer is still imaginary.

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Review these interview notes. Identify recurring problems, current workarounds, and evidence that people have spent time or money trying to solve them. Attach each finding to its source. Separate requests for faster drafting from complaints about scope, approvals, and pricing.

That distinction could change the product. You might find that writing proposals is manageable, while getting agreement on what belongs in them causes the delay.

3. competitor-profiling — Understand what you must beat

Competitor-profiling builds structured, comparable profiles from competitor URLs, and it's written to label inferences separately from sourced facts. It's designed around connected research tools: Firecrawl to read competitors' sites and DataForSEO for search metrics. If you haven't connected an SEO data source, those metrics should come back as unavailable, not estimated.

❝

Compare these three proposal tools using their current product pages and documentation. Include pricing, intended customers, and the workflow each supports. Then compare our idea with the manual alternative: a shared template and a competent assistant. Label unverified gaps.

The manual alternative matters. People already have a way of getting through the day. Your product has to earn the disruption of changing it.

Turn what you learned into a smaller, sharper offer

4. brainstorming — Explore different ways to solve it

Brainstorming, from Jesse Vincent's Superpowers project, helps clarify a request, compare approaches, and develop a design before anything gets built.

Use it to widen the solution space, then narrow your first commitment.

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Compare three ways to solve the problem supported by these interviews: a template kit, a service delivered manually, and a software product. Explain what each could teach us in two weeks. Recommend the smallest useful experiment, including what we should leave out.

A manual service may reveal the exceptions and judgment calls your future software will need to handle. That learning has value even if the service itself never scales.

5. product-marketing — Write down who it's for

Product-marketing creates a shared context document covering the audience, problem, alternatives, positioning, and other basics. Run it early: the other marketing skills in this list look for that file before asking you questions, so you stop repeating yourself.

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Build our product context from the research. Define one initial customer segment, the triggering problem, the outcome we can credibly deliver, and why someone might choose us. Mark assumptions clearly. Include who this first version will not serve.

For our example, "consulting firms" is still broad. "Independent consultants who send several custom proposals a month and have no operations support" gives you a specific person to find and an offer to test.

6. pricing — Decide what you're asking people to buy

Pricing helps you work through packaging, the unit you charge for, and the price itself.

Start with how the buyer receives value. Then check whether delivery can make economic sense.

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Compare a per-proposal service, a monthly subscription, and a template purchase. Use the costs and interview evidence I supplied. Include my delivery time and likely revision work. Identify what we need to learn from a paid pilot before choosing a permanent model.

Claude can organize the tradeoffs. Willingness to pay is something you learn from prospective buyers and actual transactions.

Make something a customer can react to

7. copywriting — Make the promise understandable

Copywriting covers landing pages and other marketing copy, built from your audience, offer, objections, and available proof.

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Write a short landing page for our pilot. Explain who it helps, what the customer provides, what they receive, and what happens next. Use language from the interviews. Do not invent testimonials, time savings, or customer counts. Clearly describe which work is delivered manually.

If the page needs three paragraphs to explain the basic offer, revisit the offer. More persuasive adjectives won't fix an unclear promise.

8. frontend-design — Give the idea a usable shape

Anthropic's frontend-design provides guidance for intentional interface design, including layout, typography, and visual direction.

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Create a simple prototype showing the three steps of the service: submit notes, review the proposed scope, and approve the proposal. Use sample data. Label simulated behavior. Make the next action obvious on a phone.

The aim is to learn where someone hesitates. Watch a prospective customer use it before you explain every button. Their questions can expose assumptions a polished presentation would hide.

9. webapp-testing — Check that the basic journey works

Anthropic's webapp-testing tests local web applications using Python and Playwright. It needs those installed, a browser it can drive, and an app it can reach.

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Test the local prototype from first visit through confirmation. Check empty input, long notes, validation errors, and mobile-sized screens. Report what you actually tested, what failed, and which parts remain simulated.

A working form is a prerequisite for learning from signups. These checks don't tell you the idea is useful, or that the product is ready for every production risk.

Launch a learning process

10. launch — Find the first people who should try it

Launch helps plan a release, including channels, early access, waitlists, and follow-up.

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Plan a limited pilot for this customer segment. We have five hours a week and a $200 experiment budget. Choose two realistic ways to reach prospects, explain why they fit, and draft an invitation. Include onboarding and a feedback conversation. Prepare the materials for review.

Those are illustrative constraints, not a recommended budget. Give Claude your real limits. A launch plan that assumes a marketing department is of little use to someone building after work.

11. analytics — Define what counts as progress

Analytics helps design and check measurement. For a small pilot, the right system may be a spreadsheet.

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Define the minimum tracking needed to evaluate this pilot. Follow qualified prospects through signup, first completed proposal, payment, and repeat use. Include delivery time and revisions. Explain which decision each measure supports.

Plan this before launch so you can observe the whole journey. A signup shows interest. Coming back with another real proposal is a different, and potentially more useful, signal.

12. ab-testing — Choose an experiment your audience can support

The ab-testing skill structures hypotheses, metrics, sample sizes, and test plans.

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Given our traffic and baseline conversion rate, assess whether a meaningful A/B test is feasible. State the assumptions and required sample. If we cannot support one, propose customer interviews or a manual offer test, and explain the limits of what we could conclude.

A few enthusiastic responses can justify another small experiment. They can't tell you how an entire market will behave. Keep the conclusion proportional to the evidence.

A two-week way to use this

Here's a suggested cadence for a small validation exercise. Customer availability and product complexity may stretch it.

  • Days 1–3: Challenge the idea and review existing evidence. Speak with prospective users about recent examples of the problem. Save what would make you change direction.

  • Days 4–5: Compare alternatives, choose one audience, and define a small offer. Set your spending limit and the evidence you need to justify continuing.

  • Days 6–9: Create the minimum demonstration or manual service. Put it in front of prospective users and observe what happens. Fix anything that blocks the experiment.

  • Days 10–14: Run the pilot, review customer behavior and delivery effort, and choose whether to continue, change the offer, or stop.

For an internal initiative, replace "payment" with an appropriate commitment: a team volunteering to pilot it, an owner allocating time, or a sponsor approving the next experiment. Be explicit about what that commitment does and doesn't prove.

Installation notes for Claude Code

New to Claude Code? Start with Anthropic's setup guide. Access depends on your plan or API arrangement, and usage and connected services can incur charges.

For the npx commands below, install Node.js first. The skills CLI currently requires Node.js 22.20 or later (check yours with node --version). Run the commands in your regular terminal from your project folder. They select Claude Code explicitly and install to that project by default; add -g only if you want a skill available across all your projects.

Start with the marketing skills you need. For research and positioning:

npx skills add coreyhaines31/marketingskills -a claude-code --skill customer-research competitor-profiling product-marketing

As the project develops, add the rest:

npx skills add coreyhaines31/marketingskills -a claude-code --skill pricing copywriting launch analytics ab-testing

For the two Anthropic skills:

npx skills add anthropics/skills -a claude-code --skill frontend-design webapp-testing

For grill-me: Matt Pocock's repository offers two install routes; for this, I'd use the Claude Code plugin. Run this in your regular terminal:

claude plugin install mattpocock-skills@claude-plugins-official

It installs the whole collection, including the underlying grilling skill that grill-me calls. Copying only the small grill-me file would leave that dependency out. Pick one route, though: installing both makes each skill appear twice. If you later use its engineering workflows, follow the repository's setup instructions.

For brainstorming: run this inside an interactive Claude Code session:

/plugin install superpowers@claude-plugins-official

Superpowers installs a broader development workflow, so use it when you want that structure. After installing either plugin, restart Claude Code if prompted, type /, and pick the skill from the menu. Plugin skills can carry a prefix, such as /superpowers:brainstorming.

Installing a skill doesn't connect your analytics account, supply research data, or install every runtime it needs. Read the linked instructions and inspect third-party scripts before running them.

Source note: Skill names, described capabilities, and installation syntax were checked against Anthropic's documentation and the creators' repositories on November 2, 2026. This is a documentation-based selection, not a claim of hands-on benchmarking. The workflow and example prompts are Workflows First's suggested applications. Repositories and commands can change.

Try this before you install anything

Open Claude, describe one idea you're considering, and paste this prompt:

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Help me decide whether this idea deserves a small experiment. Start with the uncertainty most likely to change that decision. Ask me for evidence, challenge my assumptions, and identify a cheaper way to learn. Distinguish facts, hypotheses, and unknowns. After we work through the questions, summarize the smallest useful test, its cost limit, and what result would make me stop or change direction.

You can do this in an ordinary conversation. A skill becomes valuable when you want to reuse and improve the method.

For me, that's where this gets interesting: using AI to make a difficult decision explicit while there's still time to change it.

What are you considering building, and which assumption would you most want challenged?

Hit reply with a sentence or two.

— Tom

Workflows first. Tools second.


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