Build a GPT and ship to the OpenAI GPT Store

The GPT Builder is gated on a paid ChatGPT plan: Plus, Team, or Enterprise. Free accounts can chat with public GPTs but cannot create one. If you're on Plus from a personal account, double-check the workspace you'll publish under, switching workspaces post-publication forfeits the rating history on that GPT.

The biggest mistake first-time GPT builders make is shipping a 'general assistant for X.' GPTs that win the GPT Store solve one narrow job extremely well. Before you open the Builder, write a 1-page spec: the user, the job, the inputs they'll paste, the output they should get, and the 3-5 things this GPT will refuse to do.

Help the user write a tight 1-page GPT spec.

Ask them, one question at a time:
1. Who is the user (role + context, not a demographic)
2. What's the single job this GPT does for them
3. What does the user paste in (3 example inputs)
4. What does the GPT return (exact format)
5. What's out of scope (3-5 things it should refuse)

Output the spec as a Brief surface section titled "GPT spec v1". Don't write instructions yet, that's the next step. The spec is the source of truth for everything that follows.

Instructions are the system prompt. They're capped at 8000 characters and they leak: assume any user can extract your full instructions with a clever message. Don't put secrets here, put them behind a custom Action with auth instead. Conversation starters are the 4 chips users see when they open the GPT, treat them as the GPT's marketing copy.

Read the GPT spec from the Brief.

Draft the GPT instructions following this structure:
1. Identity (one sentence: "You are X. You help Y do Z.")
2. Behavior (3-5 bullets on tone + format + step-by-step approach)
3. Refusals (the 3-5 from the spec, verbatim)
4. Output format (markdown rules, length, headings)
5. Escalation ("If the user asks for something you can't do, suggest they...")

Constraints: under 8000 characters. No secrets, treat the instructions as public. Don't include API keys, customer names, or proprietary internal info.

Then write 4 conversation starter chips, each one a real example input from the spec, max 50 chars each.

Output as a Brief section titled "Instructions v1".

GPTs can attach up to 20 files (max 512 MB each, 2M token retrieval index). Knowledge is overrated for most GPTs: the model is already good at the underlying domain. Only attach knowledge files when the GPT needs proprietary content the base model doesn't know: your product docs, internal SOPs, a specific dataset.

Actions let your GPT call your API (or any HTTPS API) mid-conversation. They're defined by an OpenAPI 3.1 schema you paste into the Builder. Most beginner GPTs don't need an Action, but if your GPT writes to a database, queries live data, or hits a paid API, you need one. The schema is the contract: get it wrong and the model invents calls that 404.

Read the user's existing API (codebase or OpenAPI doc).

Generate an OpenAPI 3.1 schema for a GPT Action that wraps it. Constraints:
1. Each operation needs an operationId in camelCase, that's how the model addresses it.
2. Each operation needs a 1-line summary, the model uses it to decide when to call.
3. Parameters: explicit names, types, descriptions. The model invents nonsense if descriptions are vague.
4. Response: a clear schema, not "object". The model formats the response based on the schema.
5. Auth: Bearer or OAuth. Include the security scheme in the schema.

Output the YAML or JSON schema as a Brief section titled "Action schema v1". Then list 3 example user prompts that would trigger each operation, so the user can test from the Builder.

Builder Profile verification is the gate that filters spam GPTs out of search. Until your profile is verified, your GPT shows up only via direct link, not in Store browse or search. Verification ties your real name (or company) to the GPT and requires you to verify a domain you own.

The GPT Store has 7 main categories: Writing, Productivity, Research, Education, Lifestyle, Programming, DALL-E. Each category has its own ranking pool, picking the right one is half the discovery battle. Your listing has a name (40 char), description (300 char), and the 4 conversation starters from earlier. There's no separate listing description from the in-chat experience, so the same starters do double duty.

Submitting is one click in the Builder: Configure -> top-right -> Save -> Publish to GPT Store. Review takes 24-72 hr typical. First-time submissions reject ~20-30% of the time, almost always for the same handful of reasons: brand-name policy, similar-to-existing-GPT, missing privacy policy on an Action, or instructions that promise capabilities the GPT can't deliver.

The GPT Store ranks on early conversation volume + completion rate + ratings. A GPT that gets 50 conversations in the first 48 hours ranks above one that gets 5, even if the second is technically better. Day-of distribution comes from your network: X / Bluesky, Reddit (r/ChatGPT, r/SideProject), Product Hunt, your newsletter.

Draft the launch-day distribution copy for this GPT.

Output:
1. A 1-page landing site copy (1 hero sentence, 3 bullets on what it does, 1 try-it CTA)
2. A 5-tweet launch thread, 1 example input per tweet
3. A 200-word r/ChatGPT post (community-friendly, no marketing fluff)
4. A 200-word Product Hunt tagline + first comment
5. A pre-launch email to send 20-50 close contacts the day before

Constraints: no superlatives. No "revolutionary." Lead with the one job the GPT does.

Once live, the Builder shows a basic analytics dashboard: conversations per day, average length, top conversation starters used. Read this every day for the first 2 weeks: a high-volume GPT with a 1-message average conversation has a tone or refusal problem. The OpenAI revenue program is currently US-only, opt-in via Builder Profile, and pays based on engaged conversations from ChatGPT Plus users.