How to Get Your ChatGPT Plugin Discovered by Customers

Confirm the public release using its exact name and direct directory URL. A personal or workspace plugin is a different distribution route. A colleague seeing it in your workspace does not prove that a customer outside the workspace can access it. Check the description against the customer's job. If the plugin checks service scope, say which service decisions it helps with. A broad promise to transform business productivity leaves the customer guessing what to ask. Keep the publisher identity and support route recognisable. A customer following a link from your website should understand that they have reached the intended business integration. Fix that first impression before attributing a poor result to algorithmic placement.

Put the listing link at a point where the customer already has a suitable task. A service page can introduce a coverage check; an existing-customer help page can explain an authorised status lookup. The example prompt should match the capability that will run. A generic banner asking people to try AI may attract curiosity without intent. A clearer invitation tells a customer what they can complete: check whether this provider supports their equipment category and location. Review the connection requirements from the customer's account. If sign-in is needed, explain what information it unlocks and why. An internal test account with broad access will not reveal whether the normal connection journey is understandable.

Tool selection is a different problem from listing discovery. Someone can have the plugin installed and still ask a request its metadata does not describe clearly. OpenAI's metadata guide recommends evaluating direct, indirect and negative prompts. Use that idea to build a labelled test set for your actual business task. For the service-fit example, a direct prompt names the provider and asks about a category. An indirect prompt describes the supported decision without naming the tool. A negative prompt asks for general advice or a capability the plugin does not offer. Record whether the correct tool ran and whether the inputs were valid. The goal is useful selection within the supported scope. Broadening the description until the tool runs for unrelated questions can create a different problem.

A selected tool can return poor information. A coverage answer may omit the relevant suburb, rely on an old record or confuse service capability with a confirmed appointment. Define task completion independently of tool invocation. For a coverage check, the customer should receive a supported result, its limits and the appropriate next step. For a status lookup, the answer should reflect the authorised record and update time. Use customer feedback and operational outcomes alongside permitted, disclosed technical metrics. Do not collect raw conversations or personal profiles merely to fill a dashboard. Choose evidence proportionate to the task being assessed.

Start with a proposed set of 15 prompts: five direct, five indirect and five negative cases. That is an editorial test design, not a required review count. Keep it separate from any public-submission test cases. Include the language customers use. A facilities manager may describe a machine informally or omit the suburb initially. A test written only in the internal catalogue's terminology will miss those cases. Save expected behaviour with each prompt. For a missing suburb, clarification may be correct. For general repair advice, no tool call may be correct. A test that rewards every activation cannot identify those distinctions.

If users cannot find the listing, review distribution and listing clarity. If they connect but the wrong tool runs, review names, descriptions and task boundaries. If the right tool returns the wrong answer, review the source and handler. Change one relevant element and repeat the same cases. Otherwise a better result cannot be attributed to the edit. Keep the test context, account access and product surface recorded so comparisons remain interpretable. A proposed experiment might replace an internal category name with a customer description while leaving the schema unchanged. If it improves valid selections without increasing unrelated calls, retain it. If the source mapping is wrong, copy changes will not fix the returned fact.

Use the service pages, onboarding material and support replies your customers already encounter. Give staff a short explanation of when to offer the plugin and when a phone call or form is more appropriate. For existing customers, one concrete example can be enough: find the current stage of a request after connecting the relevant account. Keep the alternative service route available if they do not want to connect. Measure entry points where supported and disclosed. A customer following a website link is different from a customer finding the directory unaided. Avoid presenting all accepted requests as incremental demand; some may have shifted from a familiar channel.

An illustrative report might record 40 relevant listing-link visits, 18 connections, 12 supported task attempts and nine completed outcomes. These numbers are hypothetical and do not establish what your plugin will achieve. The value is in the questions each stage raises. Why did some customers not connect? Why did three supported attempts fail? Which completed outcomes required staff follow-up? Those questions lead to practical fixes. A small prompt experiment is not a universal recommendation ranking. User context, available capabilities and platform behaviour can differ. Describe exactly what was tested before drawing conclusions about discoverability.

Does publishing guarantee recommendations? No. Plan around access and distribution you can verify. Enhanced opportunities are selective. Should we put more keywords in tool descriptions? Describe the supported task accurately and test selection. Keyword volume alone does not establish useful behaviour. What should we measure first? Check listing access, connection success, correct selection and completed customer tasks separately.

Sources checked on 5 October 2026. The four-stage measurement plan and figures are original proposed examples. 13labs plugin development starts with the customer outcome, then connects the capability, distribution and operating process needed to fulfil it.